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            1. Showing posts with label social. Show all posts
              Showing posts with label social. Show all posts

              Friday, January 31, 2014

              A Design Lesson: Customers Don't Remember Everything They Experience

              My brother is an ophthalmologist in a small town in India. In his private practice, patients have two options to see him: either take an appointment or walk in. Most patients don't take an appointment due to a variety of cultural and logistics reasons and prefer to walk in. These patients invariably have to wait anywhere from 15 minutes to an hour and half on a busy day. I always found these patients to be anxious and unhappy that they had to wait, even if they voluntarily chose to do so. When I asked my brother about a possible negative impact due to unhappiness of his patients (customers) he told me what matters is not whether they are unhappy while they wait but whether they are happy or not when they leave. Once these patients get their turns to see my brother for a consultation, which lasts for a very short period of time compared to how much they waited, my brother will have his full attention to them and he will make sure they are happy when they leave. This erases the unpleasant experience from their minds that they just had it a few minutes back.

              I was always amused at this fact until I got introduced to the concept of experience side versus memory side by my favorite psychologist Daniel Kahneman, explained in his book Thinking, Fast and Slow and in his TED talk (do watch the TED talk, you won't regret it). While the patients waited the unpleasant experience was the experience side which they didn't remember and the quality time they spent in the doctor's office was the memory side that they did remember.

              Airlines, hotels, and other companies in service sectors routinely have to deal with frustrated customers. When customers get upset they won't remember series of past good experiences they had but they would only remember how badly it ended - a cancelled flight, smelly hotel room or production outage resulting in an escalation. Windows users always remember the blue screen of death but when asked they may not necessarily remember anything that went well on a Windows machine prior to a sudden crash resulting into the blue screen of death. The end matters the most and an abrupt and unrecoverable crash is not a good end. If the actual experience matters people will perhaps never go back to a car dealership. However people do remember getting a great deal in the end and forget the misery that the sales rep put them through by all the haggling.

              Proactive responses are far better in crisis management than reactive ones but reactive responses do not necessarily have to result in a bad experience. If companies do treat customers well after a bad experience by being truly apologetic, responsive, and offering them rewards such as free upgrades, miles, partial refund, discounts etc. people do tend to forget bad experiences. This is such a simple yet profound concept but companies tend not to invest into providing superior customer support. Unfortunately most companies see customer support as cost instead of an investment.

              This is an important lesson in software design for designers and product managers. Design your software for graceful failures and help people when they get stuck. They won't tell you how great your tool is but they will remember how it failed and stopped them from completing a task. Keep the actual user experience minimal, almost invisible. People don't remember or necessary care about the actual experiences as long as they have aggregate positive experience without hiccups to get their work done. As I say, the best interface is no interface at all. Design a series of continuous feedback loops at the end of such minimal experiences—such as the green counter in TurboTax to indicate tax refund amount—to reaffirm positive aspects of user interactions; they are on the memory side and people will remember them.

              In enterprise software, some of the best customers could be the ones who had the worst escalations but the vendors ended their experience on a positive note. These customers do forgive vendors. As a vendor, a failed project receives a lot worse publicity than a worst escalation that could have actually cost a customer a lot more than a failed project but it eventually got fixed on a positive note. This is not a get-out-of-jail-free-card to ignore your customers but do pause and think about what customers experience now and what they will remember in future.

              Photo courtesy: Derek 

              Friday, November 30, 2012

              Enterprise Software Needs Flow And Not Gamification

              I don't believe in gamifying enterprise applications. As I have argued before, the primary drivers behind revenue and valuation of consumer software companies are number of users, traffic (unique views), and engagement (average time spent + conversion). This is why gamification is critical to consumer applications since it is an effort to increase the adoption of an application amongst the users and maintain the stickiness so that the users keep coming back and enjoy using the application. This isn't true for enterprise applications at all. This is not only not true for enterprise applications, but gamifying enterprise applications is couterproductive that makes existing task more complex and creates an artificial carrot that does not quite work.

              A design philosophy that we really need for enterprise applications is flow. I am a big fan of Mihaly Csikszentmihalyi and his book "Flow: The Psychology of Optimal Experience." I would highly recommend you to read it. Mihaly describes flow as a series of autotelic experiences as an activity that consumes us and becomes intrinsically rewarding. The core intent of gamification is to make the applications a pleasure to use. What people really want is enjoyment and not just pleasure. They are different. Enjoyment is about moving forward and accomplishing something. Enjoyment happens due to unusual investment of attention. It comes from tasks that you have a chance to complete, has clear goals, provides feedback, and makes you lose your self-consciousness.

              All the gamification efforts by new innovative entrants that I see seem to be disproportionately focused on "edge" applications since it's relatively easy for an entrant to break into edge applications to beat an incumbent as opposed to redesigning a core application. But most users I know spend their lives using the core systems. They have no intrinsic or extrinsic motivation to use these systems. Integrate flow in these systems to create intrinsic rewards that creates autotelic experiences. Application designers have traditionally ignored flow since it's a physical element that is external to an application, but life and social status extend beyond the digital life and enterprise applications. You get to be known as that finance guy or that marketing gal who is really awesome at work and helps people with their problems to get work done. Needless to say, helping people and getting work done are intrinsically rewarding. Help these people with their core activities and make non-core activities as minimum or transparent as possible. If I am hiking, make my drive to the trail head as easy as possible but make my hike as rewarding as possible. That should be the design principle of how you integrate flow into enterprise applications. Also, focus on perpetual intermediaries; design applications to reduce or eliminate learning curve but introduce users to advanced features as they make progress to increase their productivity on performing repeated tasks. This helps create an intrinsic reward of having learned and mastered a system. As people learn new things they become more complex and unique human beings, and believe it or not, you can influence that in your design of your enterprise software that they spend their lives using it.

              Photo Courtesy: Mark Chadwick

              Friday, August 31, 2012

              Designing The Next-generation Review And Recommendation System

              It's unfortunate that despite of the popularity of social networks and plenty of other services that leverage network effects, the review and recommendation systems that are supposed to help users make the right decisions haven't changed much.

              Thumbs-up and thumbs-down or likes and unlikes signal two things: popularity and polarization. If a YouTube video has 400 thumbs-up and 500 thumbs-down it means that the video is popular as well as polarized, but it doesn't tell me whether I will like it or not. The star review system also signals two things - on average how good something is and whether it's significant or not. There are multiple problems with this approach. An item with 8 reviews, all 5 stars, could be really bad compared to an item that has 300 reviews with 3.5 stars. Star ratings alone, without associated descriptive reviews, wouldn't make much sense if there aren't enough people who have reviewed the item. Also, relying on an average rating alone could also be problematic since it lacks the polarization element. On top of it, the review and likes could be gamed.

              Pandora's as well as Netflix's recommendations are a good example of using collaborative filtering to fine tune recommendations based on user preferences. The system aggregates the overall likes and dislikes and combines that with your taste profile and a few killer algorithms to recommend what you might like. If designed well and if it has large user population, it does work. But, the challenges with such system are missing descriptive reviews and lack of ability to perform any analysis on it. If I dislike a song on Pandora, it doesn't mean the song is bad in the absolute sense. It simply means it doesn't match my taste profile. This isn't entirely true if I dislike a blender. In this case, a descriptive context is more meaningful such as I don't like this blender because it doesn't crush spinach well. People who care to make smoothies and crush ice may not care about this issue. But, these consumers have to wade through large number of reviews to determine the product fit.

              E-commerce sites review systems use the same descriptive as well as non-descriptive review systems, commonly used at all places on the internet, without any significant modifications, even if the expected investment of a user is much higher on their site. If I don't like a song, I can skip it. If I don't like a YouTube video, I can stop watching it and now if I don't like a movie I can stop streaming it. This does not apply in the traditional world of e-commerce. I absolutely need to make sure that I buy something that I like. Returning an item is a far more involved process than stop watching a movie. It's an exception, not a norm.

              Word of mouth and passive buying

              People shop in two ways: 1) they look for a specific product, research for it, and buy it. 2) they come across a product while not looking for it, like it, and buy it.

              The second way of shopping, passive buying, is as important as active buying. There are many companies with a business model built around this impulse or "serendipitous commerce", but they don't leverage collaborative filtering. I would happily read reviews of products written by my friends and people that I trust regardless of whether I'm looking for those products or not. Think of it as Disqus-style aggregated reviews by people that I trust in my social graph. This is like an online version of a cocktail party conversation where someone is raving about a new phone that he just bought. I'm not looking for a phone, but I might, in a few days. This could create new interest or expedite my decision process. This isn't done well in the online world.

              The word of mouth is still by far the best system for following recommendations. I invariably watch movies that my brother recommends to me and one of my friends will read all the books that I recommend to her. I have non-transactional relationship with my friends and family.

              Contextualized long tail 

              One of my favorite things, when I travel (leisure or business), is to try out at least one or two recommended Indian restaurants to see how Indian food compares from city to city and country to country (so far my vote for the best Indian food outside of India goes to London). While researching for a restaurant, I typically read all the reviews that I can find. Some reviewers are Indians and some are not. Also, for the reviews written by non-Indians, some are new to Indian food and some are not. In most cases people don't identify who they are and I end up guessing based on their username, description etc. These reviews, positive or negative, don't help me much to narrow down which restaurant I should try out.

              I have always found the best food at the most unusual places. All sophisticated recommendation systems would fall short of helping me find such an unusual place. These places are not the hits. They are the long tail. Getting to this long tail isn't an easy process - a lot of asking around, digging for reviews, trying out a few awful places etc.

              Privacy concerns and connected identities

              As the debate between anonymity and identity continues, there has been a little or no effort to get to the middle-ground, a connected identity. As a marketer I don't care who Jane is in its absolute sense but I am interested in what she likes and dislikes based on her collective and aggregated behavior across the Internet and beyond. This is not an easy system to build and consumers won't sign up for this unless there's a significant value for them. The popularity of social networks is an example where even if users are arguably upset about their privacy they still use it since the value that they receive far outweighs their concern. And remember the social networks follow the power laws. As more and more people use it the network becomes more and more valuable to the users.

              Why not design review and recommendation systems that are based on connected identities? Users don't want ads, the marketers do. If companies can focus on building good products, incentivize users to write reviews, and rely on great recommendation systems to connect the right users with right products they wouldn't need ads. The marketers are chasing the illusion of targeting the right users but the inconvenient truth is that it's incredibly hard to find those users and if they do find them, they don't really want ads. What they really want is value for their money. That is the inherent conflict between the marketers and end users.

              Using connected identities beyond reviews and recommendations

              Connected identities are also useful beyond reviews and recommendation systems. Comcast support is one of those examples where using connected identities could greatly improve their customer support.

              Comcast started using Twitter early on to respond to customers' support issues. It was a novel concept in the beginning and they really understood Twitter as an effective social media channel, but lately that model has turned out to be as bad as their phone customer support. When I tweet to @comcastcares someones gets back to me asking who I am and what issues I have. You follow me, I follow you, you DM me, I DM you my info, and after few minutes, we are nowhere close to resolving the issue. What if Comcast allowed me to attach my Twitter account to my Comcast profile? I will OAuth that, for sure. When I tweet, they exactly know who I am, what problem I am experiencing, and how they might be able to help me. This is an example of using a connected identity without compromising privacy. Comcast knows their customer's billing information; it's transactional information. But they attempt to use Twitter to communicate with you without connecting these two identities.

              I don't want to "like" Comcast or "follow" Comcast to be a victim of their spam and indifference. Comcast is easy to pick on, but there are plenty of other examples where connected identities could be useful.

              Users don't like to be sold at, but they do want to buy. Let's build the next-generation review and recommendation system to help them.

              Monday, June 25, 2012

              With Yammer, Microsoft Begins Its Journey From Collaborative To Social

              Confirming what we already knew, today Microsoft announced they are acquiring Yammer for $1.2 billion in cold cash. Here's a blog post by David Sacks, the CEO of Yammer.

              Microsoft doesn't report a revenue breakdown for their individual products but SharePoint is believed to be one of the fastest growing products with annual revenue of more than $1 billion. Regardless of how Microsoft markets and positions SharePoint, it has always been collaboration software and not really social software. Microsoft does seem to understand the challenges it faces in moving their portfolio of products to the cloud, including SharePoint. Microsoft also understands value of having end users on their side even though SharePoint is sold as enterprise software. Microsoft's challenges in transitioning to the cloud are similar to the ones faced by other on-premise enterprise software vendors.

              But, I really admire Microsoft's commitment by not giving up on any of these things. Skype's acquisition was about reaching those millions of end users and they continue to do that with their acquisition of Yammer. Going from collaborative to social requires being able to play at the grassroots level in an organization as opposed to a top down push and more importantly being able to create and leverage network effects. It's incredibly difficult to lead in with an on-premise solution retrofitted for cloud to create network effects. Native cloud solutions do have this advantage. Yammer will do this really well while helping Microsoft to strengthen SharePoint as a product and maintain its revenue without compromising margins. If Microsoft executes this well, they might unlock a solution for their Innovator's Dilemma.

              With Yammer, Microsoft does have an opportunity to fill in the missing half of social enterprise by transforming productivity silos into collaborative content curation. As a social enterprise software enthusiast, I would love to see it happen, sooner rather than later.

              At personal level, I am excited to see the push for social in enterprise software and a strong will and desire to cater to the end users and not just the decision makers.  I hope that more entrepreneurs recognize that enterprise software could be social, cool, and lucrative. This also strengthens market position for the vendors such as Box and Asana.

              It's impressive what an incumbent can do when they decide to execute on their strategy. Microsoft is fighting multiple battles. They do have the right cards. It's to be seen how they play the game.

              Wednesday, April 18, 2012

              4 Big Data Myths - Part II

              This is the second and the last part of this two-post series blog post on Big Data myths. If you haven't read the first part, check it out here.

              Myth # 2: Big Data is an old wine in new bottle

              I hear people say, "Oh, that Big Data, we used to call it BI." One of the main challenges with legacy BI has been that you pretty much have to know what you're looking for based on a limited set of data sources that are available to you. The so called "intelligence" is people going around gathering, cleaning, staging, and analyzing data to create pre-canned "reports and dashboards" to answer a few very specific narrow questions. By the time the question is answered its value has been diluted. These restrictions manifested from the fact that the computational power was still scarce and the industry lacked sophisticated frameworks and algorithms to actually make sense out of data. Traditional BI introduced redundancies at many levels such as staging, cubes etc. This in turn reduced the the actual data size available to analyze. On top of that there were no self-service tools to do anything meaningful with this data. IT has always been a gatekeeper and they were always resource-constrained. A lot of you can relate to this. If you asked the IT to analyze traditional clickstream data you became a laughing stroke.

              What is different about Big Data is not only that there's no real need to throw away any kind of data, but the "enterprise data", which always got a VIP treatment in the old BI world while everyone else waited, has lost that elite status. In the world of Big Data, you don't know which data is valuable and which data is not until you actually look at it and do something about it. Every few years the industry reaches some sort of an inflection point. In this case, the inflection point is the combination of cheap computing — cloud as well as on-premise appliances — and emergence of several open computing data-centric software frameworks that can leverage this cheap computing.

              Traditional BI is a symptom of all the hardware restrictions and legacy architecture unable to use relatively newer data frameworks such as Hadoop and plenty of others in the current landscape. Unfortunately, retrofitting existing technology stack may not be that easy if an organization truly wants to reap the benefits of Big Data. In many cases, buying some disruptive technology is nothing more than a line item in many CIOs' wish-list. I would urge them to think differently. This is not BI 2.0. This is not a BI at all as you have known it.

              Myth # 1: Data scientist is a glorified data analyst

              The role of a data scientist has exponentially grown in its popularity. Recently, DJ Patil, a data scientist in-residence at Greylock, was featured on Generation Flux by Fast Company. He is the kind of a guy you want on your team. I know of a quite a few companies that are unable to hire good data scientists despite of their willingness to offer above-market compensation. This is also a controversial role where people argue that a data scientist is just a glorified data analyst. This is not true. Data scientist is the human side of Big Data and it's real.

              If you closely examine the skill set of people in the traditional BI ecosystem you'll recognize that they fall into two main categories: database experts and reporting experts. Either people specialize in complicated ETL processes, database schemas, vendor-specific data warehousing tools, SQL etc. or people specialize in reporting tools, working with the "business" and delivering dashboards, reports etc. This is a broad generalization, but you get the point. There are two challenges with this set-up: a) the people are hired based on vendor-specific skills such as database, reporting tools etc. b) they have a shallow mandate of getting things done with the restrictions that typically lead to silos and lack of a bigger picture.

              The role of a data scientist is not to replace any existing BI people but to complement them. You could expect the data scientists to have the following skills:

              • Deep understanding of data and data sources to explore and discover the patterns at which data is being generated. 
              • Theoretical as well practical (tool) level understanding of advanced statistical algorithms and machine learning.
              • Strategically connected with the business at all the levels to understand broader as well deeper business challenges and being able to translate them into designing experiments with data.  
              • Design and instrument the environment and applications to generate and gather new data and establish an enterprise-wide data strategy since one of the promises of Big Data is to leave no data behind and not to have any silos.

              I have seen some enterprises that have a few people with some of these skills but they are scattered around the company and typically lack high level visibility and an executive buy-in.

              Whether data scientists should be domain experts or not is still being debated. I would strongly argue that the primary skill to look for while hiring a data scientist should be how they deal with data with great curiosity and asking a lot of whys and not what kind of data they are dealing with. In my opinion if you ask a domain expert to be a data expert, preconceived biases and assumptions — knowledge curse —  would hinder the discovery. Being naive and curious about a specific domain actually works better since they have no pre-conceived biases and they are open to look for insights in unusual places. Also, when they look at data in different domains it actually helps them to connect the dots and apply the insights gained in one domain to solve problems in a different domain.

              No company would ever confess that their decisions are not based on hard facts derived from extensive data analysis and discovery. But, as I have often seen, most companies don't even know that many of their decisions could prove to be completely wrong had they have access to right data and insights. It's scary, but that's the truth. You don't know what you don't know. BI never had one human face that we all could point to. Now, in the new world of Big Data, we can. And it's called a data scientist.

              Photo courtesy: Flickr

              Friday, March 30, 2012

              4 Big Data Myths - Part I

              It was cloud then and it's Big Data now. Every time there's a new disruptive category it creates a lot of confusion. These categories are not well-defined. They just catch on. What hurts the most is the myths. This is the first part of my two-part series to debunk Big Data myths.

              Myth # 4: Big Data is about big data

              It's a clear misnomer. "Big Data" is a name that sticks but it's not just about big data. Defining a category just based on size of data appears to be quite primitive and rather silly. And, you could argue all day about what size of data qualifies as "big." But, the name sticks, and that counts. The insights could come from a very small dataset or a very large data set. Big Data is finally a promise not to discriminate any data, small or large.

              It has been prohibitively expensive and almost technologically impossible to analyze large volumes of data. Not any more. Today, technology — commodity hardware and sophisticated software to leverage this hardware — changes the way people think about small and large data. It's a data continuum. Big Data is not just about technology, either. Technology is just an enabler. It has always been. If you think Big Data is about adopting new shiny technology, that's very limiting. Big Data is an amalgamation of a few trends - data growth of a magnitude or two, external data more valuable than internal data, and shift in computing business models. The companies mainly looked at their operational data, invested into expensive BI solutions, and treated those systems as gold. Very few in a company got very little value out of those systems.

              Big Data is about redefining what data actually means to you. Examine the sources that you never cared to look at before, instrument your systems to generate the kind of data that are valuable to you and not to your software vendor. This is not about technology. This is about completely new way of doing business where data finally gets the driver's seat. The conversations about organizations' brands and their competitors' brands are happening in social media that they neither control nor have a good grasp of. At Uber, Bradly Voytek, a neuroscientist is looking at interesting ways to analyze real-time data to improve the way Uber does business. Recently, Target came under fire for using data to predict future needs of a shopper. Opportunities are in abundance.

              Myth # 3: Big Data is for expert users    

              The last mile of Big Data is the tools. As technology evolves the tools that allow people to interact with data have significantly improved, as well. Without these tools the data is worth nothing. The tools have evolved in all categories ranging from simple presentation charting frameworks to complex tools used for deep analysis. With rising popularity and adoption of HTML 5 and people's desire to consume data on tablets, the investment in presentation side of the tools have gone up. Popular javascript frameworks such as D3 have allowed people to do interesting things such as creating a personal annual report. Availability of a various datasets published by several public sector agencies in the US have also spurred some creative analysis by data geeks such as this interactive report that tracks money as people move to different parts of the country.

              The other exciting trend has been the self-service reporting in the cloud and better abstraction tools on top of complex frameworks such as Hadoop. Without self-service tools most people will likely be cut off from the data chain even if they have access to data they want to analyze. I cannot overemphasize how important the tools are in the Big Data value chain. They make it an inclusive system where more people can participate in data discovery, exploration, and analysis. Unusual insights rarely come from experts; they invariably come from people who were always fascinated by data but analyzing data was never part of their day-to-day job. Big Data is about enabling these people to participate - all information accessible to all people.

              Coming soon in the Part II: Myth # 2 and Myth # 1.

              Wednesday, December 14, 2011

              Design thinking: A New Approach To Fight Complexity And Failure

              Photo credit: String Theory by Michael Krigsman

              The endless succession of failed projects forces one to question why success is elusive, with an extraordinary number of projects tangling themselves in knots. These projects are like a child’s string game run amok: a large, tangled mess that becomes more convoluted and complex by the minute.

              IT projects fail all the time. Business blames IT, IT blames the system integrator (SI), who then blames the software vendor. After all this blaming and shaming, everyone goes back to work on another project without examining the project management methods and processes that caused the failure. And, so, they fail again.

              There’s no one definition of design thinking. It’s a mindset and set of values that applies both analytical and creative thinking towards solving a specific problem. Design thinking is about how you think and not what you know; it is about the journey and not the destination.

              Having followed Michael Krigsman’s analysis of IT project failures, it became evident that design thinking can play an important role in improving enterprise software development and implementation. 
              The design thinking approach offers a means to address the underlying causes of many project failures — poor communication, rigid thinking, propensity toward tunnel vision, and information silos.

              I have distilled important lessons from design thinking into six principles that can help stop project failures. Along the way, we will draw comparisons with Agile development, since that distinction is often a source of confusion when discussing design thinking.

              These six principles, based on design thinking, can help any project team operate more successfully.

              1. Put a multi-disciplinary team in charge

              You can’t pin down project failure on one person or one topic and yet we continue to use a person-centric method to manage projects. No one on a project team wants to fail. If you collectively put responsibility of the failure or success on the shoulders of the team and get them trained and motivated to think and behave differently you will mitigate much failure.

              Multidisciplinary teams champion the user, business, and technology aspects of a project in a more comprehensive manner than would otherwise be possible. Typically, an IT team talks to business stakeholders who then talk to end users, which creates communication gaps, delays, and inefficiency. Far better to create a single team that includes participants from all areas, creating a single unit that includes multiple perspectives.

              Try to staff your project team with “T-shaped” people, who possess a broad understanding and empathy for all the IT functions, but who also have deep expertise in one domain to champion that perspective. This approach can ensure that your solution is economically viable, technologically feasible, and delights the end users. A more balanced team also humanizes the project and its approach. Stay small and resist the temptation to set up very large teams. If you believe the “two-large-pizza-team” rule, those projects are team-driven and tend to be more successful. Start-ups can build something quicker because they are always short on people. As your group get bigger and bigger, other people tell you what to do and team members feel less connected to their work as it relates to the outcome.

              2. Prepare for failure in the beginning

              I recommend kicking off the project with a “pre-mortem workshop.” Visualize all the things that could go wrong by imagining that the project has failed. This gives the team an opportunity to proactively look at risks and prepare to prevent and mitigate them. I have sat through numerous post-mortem workshops and concluded that the root causes of failures are usually the same: abstract concepts such as lack of communication, unrealistic scope, insufficient training, and so on. If that’s true, why do we repeat the same mistakes, causing failure to remain a common situation? Primarily because many people find it hard to imagine and react to abstractions, but can relate much better when these concepts are contextualized into their own situation.

              3. Be both vision- and task-driven

              Design thinking emphasizes storytelling, shared vision, and empathy towards all stakeholders involved in a project. On many projects, participants focus exclusively on their own individual tasks, thus becoming disconnected from the big picture.

              While design thinking strives to connect participants to the larger vision, Agile development can be very task-driven. Everyone gets a task without necessarily understanding the big picture, or vision, or even seeing the connection between his or her tasks and the final outcome. In this situation, a project can fail and people may not understand their role, thinking they failed due to someone else’s work. If participants don’t realize their tasks contributed to a failure, they won’t try to learn and change.

              On the other hand, vision-driven approaches are very powerful. People perform their tasks, but the story and vision persist throughout the project; the same story gets told by different people throughout the lifecycle of the project to avoid that big picture fading away. All the tasks have a bigger purpose beyond their successful execution. Even good project managers miss this point. At review meetings, it is important to evaluate what the team did right but also revisit the vision and examine how recent outcomes fit the overall story.

              4. Fail and correct then fail again

              Design thinking contradicts other methodologies that focus only on success. In design thinking, failing is not necessarily a bad idea at all; however, we fail early and fail often, and then correct the course. In many projects, people chase success without knowing what it looks like or expecting to fail; therefore, they do not learn from the process.

              One of the challenges with traditional project management is the need to pick one alternate and run with it. Turns out that you don’t know everything about that alternative and when it fails, due to the irreversible decision that you made, you can’t go back. Far better to iterate on a number of alternatives as fast as you can before deciding which one will work. This approach requires a different way of thinking and planning your project.

              5. Make tangible prototypes

              Agile proposed creating unstructured documentation as opposed to making structured requirement documents. But, unfortunately, that is not enough to solve many problems. One of the core characteristics of design thinking is to prototype everything, to make a tangible artifact and learn from it. The explorative process of making prototypes makes people think deeply and ask the right kind of questions. It’s said that “computers will never give a wrong answer but it will respond to a wrong question.” The prototypes encourage people to focus on what I want to know as opposed to what I want to say. This is very important during the initial design phase of the project.

              One of the biggest misconceptions about prototypes is that people think they are too complex to make and are overhead or a waste of time. This isn’t true at all. Prototypes can be as simple as a hand-drawn sketch on a paper or as complex as fully functional interactive interface. The fidelity of a prototype is based on what kind of questions you want answered. People tend to fill in gaps when they see something raw or incomplete whereas hi-fidelity prototypes can be too complete to solicit meaningful feedback. As I already mentioned, most people respond better to an artifact as opposed to an abstract document. Prototypes also make the conversation product-centric and not person-centric. They also help to get team members on the same page with a shared vision.

              6. Embrace ambiguity

              One of the problems with traditional project management methodologies is that they make people spend more time in executing the solution and less time on defining the problem. Design thinking encourages people to stay in the problem space as long as they can. This invariably results in ambiguity, which is actually a good thing.

              Ambiguity fosters abductive thinking — a mindset that allows people to explore what is probable with the limited information on their hands without concerns about proving or concluding that it actually works. It helps people define a problem in many different ways, eventually letting them get to the right problem they eventually should focus on.

              This also supports the emergent approach that design thinking advocates as opposed to a hypothesis-driven approach. In a hypothesis-driven environment, people tend to focus on proving a premise created by a small group people. Rushing to a solution without defining the problem, and having no emergent framework in place to include the insights gained during later parts of the project, certainly contributes to failure.


              Even the best methodology requires organizational commitment to success. For design thinking to work, it is also necessary to address these common organizational issues, each of which can impede progress and limit successful outcomes.

              Lack of C-level commitment: Although design thinking is applicable at all levels in an organization, executive management must bless it by publicly embracing and practicing design thinking. Top down initiatives and training only go so far.

              When the employees see their leaders practice design thinking they are more likely to embrace and practice it themselves. The same is true with adoption of social media and collaborative tools inside an organization. The best signal to your employees is by showing them a firm belief in the method by practicing it firsthand and sharing positive outcome.

              Resistance to change: People in any organization are usually fundamentally against change, even if they believe it’s a good thing. They don’t want to get out of their comfort zone and therefore practice the same methods that have resulted in multiple failures in the past. Changing behavior is difficult but fortunately design thinking can help.

              One of the ways I have taught design thinking is by taking people away from their primary domain and have them solve a very different kind of problem such as redesigning a ticket vending machine or a fast food restaurant. My team was hugely successful since it was a completely different domain and it didn’t interfere with their preconceived notion of how a project should be executed. People’s reservations are tied to their domain; they are willing to adopt a new method and new way of thinking if you coach them outside of their domain and then encourage to practice it in their comfort zone.

              Lack of industry backing: Despite being informal, undocumented, and non-standards-based methodology, Agile experienced widespread adoption. I would attribute this success to two things: a well-defined manifesto by lead industry figures and organizations publicly committing to adopt the methodology. Design thinking lacks these attributes.

              Even though industrial design companies such as IDEO has evangelized this approach, there’s still confusion around what design thinking actually means. This also makes it difficult to explain design thinking to a wider audience. If a few organizations publicly endorse design thinking, create a manifesto, and share the best practices to gain momentum, many of the adoption hurdles will go away.

              Lack of key performance indicator (KPI) frameworks: Design thinking faces the same challenge that most Enterprise 2.0 tools face: lack of measurable KPIs.

              For number-driven leaders, lack of a quantifiable framework to measure and monitor the impact of a new methodology is a challenge. Some leaders are good at adopting new ways of doing things and others are not. In these cases, isolate a project that you can’t measure and start small. Contain the risk but pick a project that has significant upside, to keep people engaged and motivated. You may still fail, or not achieve a desired outcome, but that’s what the design thinking is all about.

              It’s worth noting that Agile, as a software project methodology, has well defined quality and reliability KPIs such as beta defects, rejected stories during a scrum cycle, and the delta between committed and delivered stories.

              Fail early and course correct the next time. Remember that adoption and specific practice need correction and not the method itself. Don’t give up.

              FINAL THOUGHTS

              During my extensive work on design thinking - practicing, coaching, and analyzing — I often talk with people who believe that design thinking is merely a methodology or approach for “visual design.” This view is a false perception. Design thinking comprises a set of principles one can apply during any stage of the enterprise project lifecycle along with other project management methodologies. This approach is valid for the CEO and executive management all the way to the grass roots.

              Another common point of confusion is the distinction between design thinking and Agile methods of software development. The primary difference is that Agile offers a specific set of prescriptive processes while design thinking encapsulates a set of guidelines and general principles. Although not the same, the two approaches are highly complementary (even on the same project), because both recognize the benefits of using iterative work cycles to pursue customer-centric goals.

              Always remember that real people work on every project. The best methodologies are inherently people-centric and help participants anticipate likely causes of failure. Visualizing failure early in a project is an excellent means to prevent it from occurring. We’re all human and may make mistakes but certainly no one wants to fail.

              Design thinking can make potential failure a learning tool and not a final outcome.

              I had originally published this post as a guest blog post on Michael Krigsman's IT Project Failures blog

              Monday, June 6, 2011

              Social Shaming

              An interaction designer, Joshua Kaufman, had his MacBook stolen a few days back. He is a smart dude. He had installed an app called Hidden on his MacBook before it was stolen. He tracked down the thief and asked the Oakland PD to catch him. They said no. He was frustrated, obviously. He published all the details regarding the theft including the picture of the guy who stole his MacBook on his blog. This story went viral on Twitter and Facebook and made it almost impossible for the cops to ignore it. Oakland PD found the guy and arrested him. Since then the story has been picked up by many major media outlets and became sort of a sensation.

              Social shaming works.

              There's a fine line between peer pressure and social shaming. Many car dealerships in the US have a whiteboard that tracks which sales reps sold how many cars. They also ring a bell every time someone sells a car. It's a cheesy thing to do, but it sends a clear message to other people to be more aggressive; it's indeed a form of peer pressure. It's also an efficient technique to motivate the kids.

              In fact, it's one of the most important gamification elements.

              Public shaming has been used in many different ways e.g. send an email out to all the sales people with a list of people highlighted in red that haven't updated the CRM system. I know of a company that had a practice in place to publicly give a "D'oh! award" to a developer who broke the nightly build. Social shaming is essentially public shaming using social media. During my discussion with many enterprise social software vendors, analysts, and thought leaders I have repeatedly argued that changing end users' behavior is less likely to succeed unless there's a significant upside for the end users. What is more likely to work is codifying the real life end user behavior in the software that they use. Social shaming is one of those. One of the ways to achieve this could be by designing software that promotes radical transparency, signals one's successes to the other, and nudges them to excel without embarrassing them.

              Thursday, May 26, 2011

              Disruptive Cloud Start-Ups - Part 2: AppDirect

              Check out the first post of this series on NimbusDB, if you haven't already seen it. This post is about AppDirect. I met with Nicolas Desmarais, a co-founder and the CEO of AppDirect and had a long discussion regarding their current solutions and future strategy. AppDirect is an app store for small businesses. The developers can integrate their applications with AppDirect and AppDirect manages the experience of selling, provisioning, and billing with a 70-30 revenue split with the developers. They also have a white label app store solution that they sell to large customers such as ISPs who can sell these same applications to their customers.

              Let's get the things out of the way that I didn't like about them.

              The downside:

              The target market that comprises of small businesses is extremely difficult to reach to and to market to. This gets even more difficult when the company trying to market is a young start-up and the customers are "S" in SMB. These customers have very different kind of requirements. They look for simple solutions that are not very expensive and have predictable SLA with a clear local support model and not the ones that come with enterprise grade features such as end-to-end integration, single sign on etc. Intuit has owned this channel for a while via Quickbooks and their SMB marketplace (the partner platform) is a great example of selling go-to-market services to other ISVs. AppDirect will have to work much harder if they want to work this channel.

              So, why do I think they are disruptive?

              The upside:

              AppDirect is platform-agnostic. The developers can write applications in any language and run it on any platform as long as they integrate with AppDirect's end points (the APIs). The ISVs or PaaS providers have traditionally locked developers into their platform. That lock-in now goes away.

              Even though the telcos are not the most innovative companies, they are laggards with a pile of cash, a ton of customers, and good margins. I believe that telcos can be great enterprise software vendors for SMB. Instead of spending money on the marketing efforts, if AppDirect can convince the Telcos and ISPs to bundle their white label solution, it's a win-win situation. This business alone can make them profitable. What you need is a small number of large customers. Long tail can always be an added bonus.

              The team is talented and they have got a good product with some early customers. If they can execute on their vision and pivot as necessary, they're on to something,

              Check out their slides and presentation:

              Friday, January 28, 2011

              5 Tips To Become An Influencer On Twitter

              I have been answering quite a few questions on Quora. The most recent one was "What are 5 tips to becoming an influencer on Twitter?" This post is a version of my answer on Quora.

              Being an "influencer" means different things to different people, but I would attempt to describe this in the most general sense.
              1. Be unique: Twitter has very low signal to noise ratio. You don't get others' attention if you cannot differentiate yourself and your contribution. Be passionate about the topics that you care for and work hard to craft high quality tweets. Go through a brutal qualifying process to discard the weak draft tweets and post the ones that are of the highest quality. Treat your Twitter account as your personal brand and think what makes any brand stand out. As Seth Godin would say, be the purple cow.

              2. Be a great blogger: Let's not forget that Twitter is still a form of blogging; a microblogging. Ask yourself what makes a great blogger? Apply those qualities on Twitter such as extensive due diligence, passionate about your point of view, not afraid of picking up a fight when you think you are right, not afraid of taking criticism in public, ability to give constructive feedback, and importantly discovering, reading, and synthesizing the information. To blog and to tweet is the last mile to influence the people. There's plenty of legwork that happens before that.

              3. Converse with the influencers: Being surrounded by smart people makes you smart. This is not only true in real life, but it is also true in social media. Don't just follow the influencers, but try to understand why they are the influencers. Retweet their posts with your insights, thank them, and reach out to them with interesting stories, insights, and comments. Also, make an attempt to meet them in real life at tweetups and other networking events. At times, they are more open to meeting people than you might think.

              4. Hashtags: I cannot overemphasize the importance of following and tweeting the live events. Follow a few conferences remotely such as #tcdisrupt or #sxsw and be part of weird memes such as #lessambitiousbooks. Also, try following obscure events. This is how you will discover interesting people and people will discover you. Follow up with people, that you like, after the event. Don't be afraid of self-promotion as long as you are humble and adding value in the conversations and interactions.

              5. Cross-channel pollination: Twitter is one of many social media channels. Author your own Tumblr or Posterous blog, answer questions on Quora, post interesting pictures on Flickr and Instagram, and importantly, use the channels to direct people to follow you on Twitter. There are many different ways people find other people to follow on Twitter. Use the low impedance nature of Twitter to your advantage by converting all the social media interactions to have rich conversations with them on Twitter.
              You don't have to be an influencer in real life to be an influencer on Twitter. In fact, that's exactly the point. It's all about Twitter as a channel that empowers simple human-beings, that are not influencers of any kind, to do amazing things and become an influencer. Justin is a great example. He found Twitter and used the medium for what it was good for. Now, he has a book and a TV show. On the other hand, Eric Schmidt has 54 tweets but has 2.34 million followers, as of 01/27. I don't think of him as an influencer on Twitter. Is he an influencer in real life? Hell, yeah. There are also people like Padmasree and Chamillionaire that have effectively been using Twitter to amplify and extend their great influence in real life to social media.

              Tuesday, December 28, 2010

              Research Report: 2011 Cloud Computing Predictions For Vendors And Solution Providers

              This blog post was jointly authored by @Chirag_Mehta (Independent Blogger On Cloud Computing) and @rwang0 (Principal Analyst and CEO, Constellation Research, Inc.)

              As Cloud Leaders Widen The Gap, Legacy Vendors Attempt A Fast Follow

              Cloud computing leaders have innovated with rapid development cycles, true elasticity, pay as you go pricing models, try before buy marketing, and growing developer ecosystems. Once dismissed as a minor blip and nuisance to the legacy incumbents, those vendors who scoffed cloud leaders now must quickly catch up across each of the four layers of cloud computing (i.e. consumption, creation, orchestration, and infrastructure) or face peril in both revenues and mindshare (see Figure 1). 2010 saw an about face from most vendors dipping their toe into the inevitable. As vendors lay on the full marketing push behind cloud in 2011, customers can expect that:

              Figure 1. The Four Layers Of Cloud Computing

              General Trends
              • Leading cloud incumbents will diversify into adjacencies: The incumbents, mainly through acquisitions, will diversify into adjacencies as part of an effort to expand their cloud portfolio. This will result into blurry boundaries between the cloud, storage virtualization, data centers, and network virtualization. Cloud vendors will seek tighter partnerships across the 4 layers of cloud computing as a benefit to customers. One side benefit - partnerships serve as a pre-cursor to mergers and as a defensive position against legacy on-premises mega vendors playing catch up.

              • Cloud vendors will focus on the global cloud: The cloud vendors who initially started with the North America and followed the European market, will now likely to expand in Asia and Latin America. Some regions such as Brazil, Poland, China, Japan, and India will spawn regional cloud providers. The result - accelerated cloud adoption in those countries, who resisted to use a non-local cloud provider. Cloud will prove to be popular in countries where software piracy has proven to be an issue.

              • Legacy vendors without true Cloud architectures will continue to cloud wash with marketing FUD: Vendors who lack the key elements of cloud computing will continue to confuse the market with co-opted messages on private cloud, multi-instance, virtualization, and point to point integration until they have acquired or built the optimal cloud technologies. Expect more old wine (and vinegar, not balsamic but the real sour kind, in some cases) in new bottles: The legacy vendors will re-define what cloud means based on what they can package based on their existing efforts without re-thinking the end-to-end architecture and product portfolio from grounds-up.

              • Tech vendors will make the shift to Information Brokers: SaaS and Cloud deployments provide companies with hidden value and software companies with new revenues streams. Data will become more valuable than the software code. Three future profit pools willl include benchmarking, trending, and prediction. The market impact - new service based sub-categories such as data-as-service and analysis-as-a-service will drive information brokering and future BPO models.
              SaaS (Consumption Layer)
              • Everyone will take the SaaS offensive: Every hardware and system integrator seeking higher profit margins will join the Cloud party for the higher margins. Software is the key to future revenue growth and a cloud offense ensures the highest degree of success and lowest risk factors. Hardware vendors will continue to acquire key integration, storage, and management assets. System integrators will begin by betting on a few platforms, eventually realizing they need to own their own stack or face a replay of the past stack wars.
              • On-premise enterprise ISVs will push for a private cloud: The on-premise enterprise ISVs are struggling to keep up with the on-premise license revenue and are not yet ready to move to SaaS because of margin cannibalization fears,lack of scalable platforms, and a dirth of experience to run a SaaS business from a sales and operation perspectives. These on-premise enterprise software vendors will make a final push for an on-premise cloud that would mimic the behavior of a private cloud. Unfortunately, this will essentially be a packaging exercise to sell more on-premise software. This flavor of cloud will promise the cloud benefits delivered to a customer's door such as pre-configured settings, improved lifecycle, and black-box appliance. These are not cloud applications but will be sold and marketed as such.
              • Money and margin will come from verticalized cloud apps: Last mile solutions continue to be a key area of focus. Those providers with business process expertise gain new channels to monetize vertical knowledge. Expect an explosion of vertical apps by end of 2011. More importantly, as the buying power shifts away from the IT towards the lines of businesses, highly verticalized solutions solving specific niche problems will have the greatest opportunities for market success.
              • Many legacy vendors might not make the transition to cloud and will be left behind: Few vendors, especially the legacy public ones, lack the financial where with all and investor stomachs to weather declining profit margins and lower average sales prices. In addition, most vendors will not have the credibility to to shift and migrate existing users to newer platforms. Legacy customers will most likely not migrate to new SaaS offerings due to lack of parity in functionality and inability to migrate existing customizations.
              • Social cloud emerges as a key component platform: The mature SaaS vendors that have optimized their "cloud before the cloud" platform, will likely add the social domain on top of their existing solutions to leverage the existing customer base and network effects. Expect to see some shake-out in the social CRM category. A few existing SCRM vendors will deliver more and more solutions from the cloud and will further invest into their platforms to make it scalable, multi-tenant, and economically viable. Vendors can expect to see some more VC investment, a possible IPO, and consolidation across all the sales channels.
              DaaS & Paas (Creation and Orchestration Layers)
              • Battle for PaaS begins with developers: Winning the hearts and minds will drive the key goals of PaaS providers. As mobile, social, and cloud intersect, expect new battle lines to be drawn by existing vendors seeking entry in the cloud. The first platform to enable write once deploy any how will win. PaaS vendors will seek to incorporate the latest disruptive technologies in order to attract the right class of developers and drive continuous innovation into the platform.
              • Vendors must own the platform (both DaaS and Saas) to survive: ISV’s who give up on investing in their own cloud platform to other ISV’s will be relegated to second class citizens. Despite the tremendous upfront cost savings, these platform moves cut-off future revenue streams as the stack wars move to the cloud. For example, ISV’s will avoid Java to mitigate risk with Oracle or IBM. The ability to control information brokering services will be limited to the platform owner.
              • Tension between indirect channel partners and vendors in the cloud will only increase: Cloud shifts customer account control to the vendor. Partners who wholeheartedly embrace the cloud risk losing direct relationships with their customers. In the case of .NET development in Azure, greater allegiance by partners to Microsoft will result in less account control with Azure.
              • PaaS will be modularized and niche: New PaaS vendors will focus on delivering specific modules to compete with end-to-end application platforms. One approach - dominate niche areas int the cloud such as programming language runtimes, social media proxies, algorithmic SDK, etc. Expect more players to jump into fill big gaps in big data, predictive analytics and information management.
              • Mobile app development will move to the cloud: App dev professionals and developers want one place to reach the mobile enterprise to build, mange, and deliver. The app dev life cycles will follow the delivery models and device management will prove to be the keystone in ensuring the complete development experience. Vendors should expect the cloud to be the predominant delivery channel for mobile apps to end users. Success will require seamless management of extensions and disconnected support.
              IaaS (Infrastructure Layer)
              • Cloud management will continue to grow and consolidate: Cloud management tools saw significant growth and investment in the last couple of years. This trend will continue. Expect to see a lot more investment in this category as increasing customer adoption drives demand for tools to manage hybrid landscapes. Also expect consolidation in this category as several VC-backed start-ups seek profitable and graceful exits.
              • Cloud storage will be a hot cake: Explosive growths in information in many verticals for early adopters already factor into this fast-growing category. With more and more data moving to the cloud, customers can anticipate significant innovation in this category including SSD-based block storage, replication, security, alternate file systems, etc. Data-as-a-service and NoSQL PaaS category will further boost the growth.
              • NoSQL will skyrocket in market share and acceptance: Substantial growth in the number of NoSQL companies reflect an emerging trend to dump the infrastructure of SQL for non-transactional applications. The cloud inherently makes a great platform for NoSQL and that further drives the growth for data-as-a-service and storage on the cloud.

              The Bottom Line For Vendors (Sell Side)

              Cloud ushers a new era of computing that will displace the existing legacy vendor hegemony. Many vendors caught off guard by the shift in both technology and user sentiment must quickly make strategic course corrections of face extinction. Here are some recommendations for vendors making the shift to Cloud:
              1. Embrace, don't wait, don’t even hesitate: Which is worse; cannibalizing your margins or not having margins to cannibalize? Faster time to market and greater customer satisfaction will pay off. The move to cloud ensures a seat at the table for the next generation of computing.
              2. Begin all new development projects in the cloud: The rapid development cycles for cloud projects ensures that innovation will meet today’s time to market standards. Test out new projects in the cloud and experience rapid provisioning and elasticity. However, don’t forget to fail fast and recover quickly.
              3. Avoid investing in platform led apps: Apps should drive platform design not the other way around. Form really does follow function in the Cloud. Platform designs must focus on agility and scale. Apps prove out what’s really needed versus what’s theoretical. Plan for social, mobile, analytics, collaboration, and unified communications but deliver only when it makes business sense.
              4. Focus on developers, developers, and developers: Steve Ballmer is right. Success in the cloud will require bringing the developers with along on the PaaS journey. Don't make them wait until the platform is done. Otherwise, it may be too late for the company and developer ecosystem.
              5. Prioritize power usage effectiveness (PUEs): As with the factories during the last turn of century, IaaS will be the heart of delivery. Companies with the lowest cost of computing will win and be able to pass cost savings onto their customers or pocket the margin. Further, data center efficiencies do their part in green tech initiatives.
              6. Help customers simplify their landscape: Build compelling business cases to shift from legacy infrastructure to cloud efficiencies. Lead the race to optimize legacy at your competitor’s expense.
              Disclaimer: The views expressed in this post are mine and not of my current or past employers'. This is my independent blog.

              Monday, November 15, 2010

              10 Business Books In 2010

              These are the 10 business books published in 2010, that I would recommend you to read. Originally, I wrote this on Quora, in response to "What are must read business books of 2010?". Yes, I have read all of them, and no, they are not in any specific order.

              1) What the Dog Saw by Malcolm Gladwell

              I am a big fan of Malcolm Gladwell and his style. This is a compilation of his "The New Yorker" stories. Even though the articles are available on his website, this book makes it a great read.

              2) Cognitive Surplus by Clay Shirky

              The next time someone asks you how come people have so much time to blog, answer questions on Quora, or contribute to Wikipedia, ask them to read this book.

              3) The Big Short by Michael Lewis

              Want to know all about CDO and subprime mortgage and still be entertained? This is the book. Michael Lewis has great storytelling skills that makes serious and complex topics fun to read. I like this book as much as I liked Moneyball - http://amzn.to/b9YPx9

              4) Open Leadership by Charlene Li

              If you liked Groundswell - http://amzn.to/c8faH5 - you will like this as well. If you are interested in organizational transformation through social media, this will make a great read. Social media adoption can certainly make the leaders more credible, open, and transparent. Being a social media freak and an enterprise 2.0 strategist, I loved this book.

              5) Engage by Brian Solis

              This book is Seth Godin meet Social Media. It's a must-read if you are a marketer, trying to understand the impact of social media on your brand and working on engaging your customers using social media. Brian Solis has a fluid style with a lot of relevant examples.

              6) The New Polymath by Vinnie Mirchandani

              Vinnie is a great enterprise software analyst and a prolific blogger. I closely follow his work. This is an upbeat book that will excite the technologists as well as the business folks. If you think you have a stretch goal and want to change the world, this book will further stretch your stretch goals, and will give you a reason and purpose, to get out of bed every morning and run for it.

              7) Rework by Jason Fried

              I have followed 37Signals and Jason's blog. This book puts everything together with illustrations and a simple style making it easy to read, just like 37Signals. If you are itching to be an entrepreneur, this might make you take that leap. If you're starting out and want inspiration and design principles, this is the book. All design is re-design and so is this book.

              8) The Facebook Effect by David Kirkpatrick

              Some watch the movie, I prefer to read a book. The book is more accurate than the movie. Well, duh. David is a great writer, and he used the access that he had to Zuckerberg and Facebook, to produce a great book. It's quite insightful.

              9) Gamestorming by Dave Gray

              I love XPLANE. They do a great job and now they are part of Dachis group where I am expecting them to do even better. It's incredibly difficult to take complex concepts and simplify to communicate to any audience. The book outlines great approaches to accomplish the simplicity and facilitate learning, discovery, and decision making.

              10) Delivering Happiness by Tony Hsieh

              Zappos is a great company. I have learned a lot from its culture and from Tony's management style. This is a must-read, if you believe you want to excel in serving your customers and have your entire team live by those values.

              And this is the first 2011 book that you may want to read:

              Knowing Umair, this will be a great book.

              Tuesday, September 7, 2010

              A Laundromat Entrepreneur

              In my previous post “While Entrepreneurs Scale On The Cloud The Angels Get Supersized” I wrote about how cloud computing is disrupting the VC industry. Continuing on the thread of entrepreneurship I am seeing more and more entrepreneurs building applications who do not belong to any formal organization, start-up or otherwise. The definition of what used to be a start-up itself is changing, primarily because of two reasons - simple and easily accessible PaaS tools to design, run, and maintain applications on the cloud and access to a market place to sell the applications.

              We have been witnessing this trend for the mobile applications for a while - Android as well as iPhone and now iPad. I see the same pattern for the cloud-based applications. I have seen many useful, productive, and successful applications that are designed by individual developers with no affiliation to any organization.

              Google has done a great job in designing the tools for the developers to build applications that can run on their cloud and can be sold on their app store. This has democratized the application business to large extent that attempt to solve niche problems. At the same time the individual developers have started monetizing their work without going through an overhead of bootstrapping and running a company. While Google’s cloud platform is a generic one the application and stack specific PaaS providers such as Salesforce.com and Heroku are also attracting such developers. Intuit’s partner development platform is a great example of a channel platform that allows the entrepreneurs to market to an SMB segment, a very difficult segment to reach (a post on that later).

              All these trends, collectively, have introduced a new category of an entrepreneur. A laundromat entrepreneur.

              They are not full fledged start-ups but these individuals are also not developing just for fun. These businesses have steady revenue, positive cash flow, and require very little maintenance. The companies such as Help Me - located in Karachi, Pakistan - have created their business model to support such developers outsource customer support for their existing applications so that they can focus on building new applications. Some of these individual businesses could be worth a few million dollars.

              This is a very different business model that combines the best-of-breed with long tail. I am quite excited about this new category since that puts in the developers directly in charge of the product and takes them closer to the end users. I am curious to see the life cycle of these laundromats and how they get bought and sold. Many people that I have had discussions with claim that we could expect to see plenty of individuals who will own such a laundromat portfolio worth five to six million dollars.

              Attribution: I have shamelessly stolen the word “laundromat” from my friend Mike Ni after my discussion with him on cloud computing business models. I had told him that I would!

              The picture credit to Michael Valli

              Thursday, July 22, 2010

              The Missing Half Of A Social Enterprise

              In my previous post “Social CRM Is Only The First Half Of A Social Enterprise” I started the discussion on why social CRM is only the first half of a social enterprise and how we can go to the core and build a true social enterprise. Continuing the discussion on the missing half on a social enterprise this is the part 2.

              Transform productivity silos into collaborative content curation:

              The social software gets better as more people use it but we need more people to make it useful. There is no easy way out. As Andrew McAfee’s rightly put it Email is a 9x problem. There isn’t significant juice in standalone social software to gain broader adoption due to the endowment effect. There is a huge adoption barrier for standalone social software to be successful since it is not contextualized into a business process. The users simply see it as yet another tool that increases their cognitive overload.

              I suggest don’t go after social software that is designed to create a parallel universe. Instead design solutions that are contextualized within existing business processes and makes it very easy for the end users to curate existing content from several structured, semi-structured, and unstructured sources e.g. Email, Wiki, PowerPoint, ERP, CRM, SharePoint etc. The nature of the content could be any artifacts such as an invoice, purchase order, strategy document, pipeline report, documentation etc. Describing what collaborative content curation can actually do for enterprise software would require a blog post by itself. I suggest you read democratised curation by JP and "The Seven Needs of Real-Time Curators” by Scoble. But in nutshell if designed correctly it offers significant potential to help people find, nurture, and syndicate the enterprise content with collaboration on steroids. The users continue using the tools that they like. However suddenly these tools start feeling more and more social with collaborative on-ramps and off-ramps. Social media, cloud computing, and collaborative content curation will be peanut, butter, and jelly for a social enterprise.

              Use social tools to challenge and rethink management practices:

              Efficient tools are not a proxy for an efficient management. The tools of the past did bring the automation and productivity but did very little to influence the way the organizations are being managed. Adding social fabric to existing processes may bring in some additional benefits but a true social enterprise should thrive for the tools that completely make them rethink the management practices almost to the point to cause disruption.

              How about opening up the cost structure to the entire organization, democratize the decision making process, run bottom-line based prediction markets – not how much we will sell it for but what will it cost us to build it. It’s an endless list. This will be unsettling in the beginning for some but it would eventually yield great results.

              The generational shift is already ready for this disruption. The baby boomers are on their way out and the current mid-level and senior gen X managers will be replaced by the millennial very soon. Millennial is a born-social generation. As one millennial told my friend when asked what does career mean to him – “I want to have awareness of what’s going on around me, have micro-conversations on social tools, and create context. This context is my career”. Such philosophy will challenge the current management practices and put organizations in a difficult situation.

              But this is an opportunity as well. The organizations can completely rethink the management practices as they start their journey to be a true social enterprise. This is not just about asking a CEO to use a blog to communicate with the employees but to have a social-first attitude at every single step of the management.

              Earn your user base by leaning in with a consumer start-up mindset:

              One of the biggest differences between the enterprise and the consumer software is that the user is not a buyer in the enterprise software. Enterprise software vendors don’t attempt to win the end users since they don’t have to. The end users have no choice. I suggest that if you are an enterprise software company that designs social solutions lean in with a consumer start-up mindset where you really have to earn your user base.

              The cafeteria menu is my personal favorite example. One of my friends’ company spent $600k to redesign their intranet and the most popular page on the new Intranet is still the cafeteria menu that gets updated every week. Why not solve that problem? Provide cafeteria information that is fresh and accessible from mobile devices. Now, you have my attention. Add social and location-based functionality to help me find other employees to network and have lunch with. This is the new HCM. Well, not exactly, but you get the point.

              If you attempt to design an IT-driven top-down solution to enforce “socialness” it simply won’t work. You need to win your users to use your solutions even if, in theory, they don’t have a choice.

              Having fun and being productive should not be mutually exclusive.

              Friday, June 11, 2010

              Social CRM Is Only The First Half Of A Social Enterprise

              Social CRM has arrived. My fellow bloggers and analysts friends Jeremiah Owyang, Ray Wang, Esteban Kolsky, Paul Greenberg, Sameer Patel, Oliver Marks, Jeff Nolan, and countless others have done a great job in defining the attributes, characteristics, and value proposition of social CRM. The recent acquisitions - Lithium acquiring Scout Labs, Attensity acquiring Biz360, and Jive acquiring Filtrbox - have clearly indicated the market interest in social CRM. There are also tons of emerging start-ups in this domain solving specific problems in niche sub-categories of social CRM.

              However, social CRM is only the first half of a social enterprise.

              Let me be that idiot for a minute who over-simplifies enterprise software and its evolution. The traditional ERP, MRP, and SCM software were designed for automation and productivity to improve the bottom-line, scale the business, and make informed decisions. The CRM was essentially designed to sell and market better and eventually to support the customers whom you sold to. Then comes the social CRM that is designed as an extension of CRM to help understand customers better, have rich conversations with the customers, increase the impact of the brand, prevent customer churn etc.

              Unfortunately social CRM is only the half part of the equation primarily designed to influence the top-line of an organization. The other missing half is the social solutions that support the bottom-line of a company. Together they form a social enterprise. I don’t like the word “social business”. In case you didn’t get the memo, the business has always been social. What is not social is an enterprise. A combination of social CRM that supports the top-line and a set of solutions that supports the bottom-line can truly transform an enterprise into a social enterprise.

              Some vendors have attempted to introduce “socialness” in some of the edge applications but I believe there is a need to go to the core and build a true social enterprise. In my two part series I would like to share my thoughts on how this could be accomplished. This is part one.

              Focus on the means and not the end:

              I can talk about plenty of ERP processes but let’s discuss a specific process that is perceived my many people as dry and not social. It’s the “closing the books” financial process. I would encourage the folks, who think that the financial processes are not social, to spend some time in a large organization to observe and shadow the controllers and a CFO in the last few days and the first few days of a quarter. The software that “closes the books” is the very last step in the process, the end, designed to keep the CEO and CFO out of the jail. Everything that leads up to closing the books, the means, comprise tacit social interactions such as calling cost center managers for their numbers, asking for clarifications, communicate not to do certain things etc. The list goes on. This social system certainly works. However there is one problem – it is highly inefficient.

              This is where I see the opportunity to provide a social toolset designed for a specific process – a social vertical – to help all the stakeholders. The social tools should not be designed to replace the face-to-face interactions and should not just be limited to encode the interactions. Instead they should allow people to scale their social interactions, leverage discovery, and experience serendipity. The social tools become the context for the core processes.

              Find an internal business process that is inherently social where employees spend most of their time outside of a destination tool. Run with it.

              Don't fight the system, instead cater to emergent roles:

              As the nature of business changes the great organizations that are on forefront of this change are good about creating new roles that never existed before. Some the examples are Chief Sustainability Officer, Chief Privacy Officer, Chief Customer Churn Officer etc. Enterprise software vendors are often criticized as “pouring concrete into existing business processes”. It’s not a surprise that existing processes are hard to change and existing human behavior is even harder to change but providing a “social-first” experience to these new emergent roles could potentially trigger a positive change in an organization. The people in these new roles don’t typically have a rigid set of pre-defined processes and tools. That’s good news. Work with these people to identify how social software can enable some of these new business processes and functions. As a vendor you are likely to get more traction working with them against working with a CFO or a purchase manager.

              Turn involunteer collaboration into social interaction:

              Let’s be very clear that being collaborative does not mean being social. Unfortunately the existing collaboration tools help people collaborate once they have decided to collaborate. Well, duh. But when you think about it, if people get along well before they decide to collaborate they have a higher chance of success while they collaborate. The problem is that people neither have motivation nor time to find and get to know the folks that they might be required to work with. This is where social enterprise can do wonders.

              The solution that powers the social enterprise does not have to solve a specific business problem. Imagine an enterprise social network that has algorithms to find the like minded-people based on their skills, interest, extra curricular activities, the departments they work for, the cars they drive, the neighborhoods that they live in etc. The real advantage of using such a network is to bridge silos without having an explicit goal of collaboration. This is an antithesis of collaboration.

              You don’t collaborate with your neighbors before you socialize with them. You greet them, go to the block party, and have beer and BBQ. And then if you need to collaborate on chopping that tree you do so. It isn’t very different when it comes to enterprises. End of the day the enterprises have human beings that behave like, well, human beings.

              Coming up in the next post:

              Social enterprise enablement through collaborative content curation, democratizing the management, and earning instead of buying adoption.

              Thursday, April 22, 2010

              Disruptive Cloud Computing Startups At Under The Radar - NoSQL - Aspirin, Vicodin, and Vitamin

              It was great to be back at Under The Radar this year. I wrote about disruptive cloud computing start-ups that I saw at Under The Radar last year. Since then the cloud computing has gained significant momentum. This was evident from talking to the entrepreneurs who pitched their start-ups this year. At the conference there was no discussion on what is cloud computing and why anyone should use it. It was all about how and not why. We have crossed the chasm. The companies who presented want to solve the “cloud scale” problems as it relates to database, infrastructure, development, management etc. This year, I have decided to break down my impressions into more than one post.

              NoSQL has seen staggering innovation in the last year. Here are the two companies in the NoSQL category that I liked at Under The Radar:

              Northscale was in stealth mode for a while and officially launched four weeks back. Their product is essentially a commercial version of memcached that sits in front of an RDBMS to help customers deal with the scaling bottlenecks of a typical large RDBMS deployment. This is not a unique concept – the developers have been using memcached for a while for horizontal cloud-like scaling. However it is an interesting offering that attempts to productize an open source component. Cloudera has achieved a reasonable success with commercializing Hadoop. It is good to see more companies believing in open source business model. They have another product called membase, which is a replicated persistence store for memcached – yes, a persistence layer on top of a persistence layer. This is designed to provide eventual consistency with tunable blocking and non-blocking I/Os. Northscale has signed up Heroku and Zynga as customers and they are already making money.

              As more and more deployments face the scaling issues, Northscale does have an interesting value proposition to help customers with their scaling pain by selling them an aspirin or vicodin. Northscale won the best in category award. Check out their pitch and the Q&A:

              GenieDB is a UK-based start-up that offers a product, which allows the developers to use mySQL as a relational database as well as a key-value store. It has support for replication with immediate consistency. Few weeks back I wrote a post - NoSQL is not SQL and that’s a problem. GenieDB seems to solve that problem to some extent. Much of the transactional enterprise software still runs on an RDBMS and depends on the data being immediately consistent. The enterprise software can certainly leverage the key-value stores for certain features where RDBMS is simply an overhead. However using a key-value store that is not part of the same logical data source is an impediment in many different ways. The developers want to access data from single logical system. GenieDB allows table joins between SQL and NoSQL stores. I also like their vertical approach of targeting specific popular platforms on top of mySQL such as Wordpress and Drupal. They have plans to support Rails by supporting ActiveRecord natively on their platform. This is a vitamin, if sold well, has significant potential.

              They didn’t win any prize at the conference. I believe it wasn't about not having a good product but they failed to convey the magnitude of the problem that they could help solve in their pitch. My advice to them would be to dial up their marketing, hone the value proposition, and set up the business development and operations in the US. On a side note the founder and the CEO Dr. Jack Kreindler is a “real” doctor. He is a physician who paid his way through the medical school by building healthcare IT systems. Way to go doc! Check out their pitch and the Q&A:

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