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Cognitive Computing Systems: Want to build a great MVP? Pick your ingredients carefully

Over the last five articles I have hopefully presented a very strong business case for the value that a cognitive computing system like Herbie can bring to startup founder like Keith and his team. They have successfully collaborated up to this point and have developed a very strong product vision:

We believe that we can build a cognitive computing system that acts both as an early warning system for students “at-risk” of dropping out of high school and as a virtual education “doctor.” The system would be capable of diagnosing in real-time the reasons why a student is likely to drop out and then be able to specifically tell all relevant stakeholders what actions they could and should take to help the student qualify for graduation. Student Lifecycle Management is a key component to solving the graduation problem and it will be powered by a national cognitive computing system.

Now that we know what we want for dinner we need to talk about the recipe we want to use. The recipe I’m referring to in this case is the specific product features and benefits that will bring our solution to life. By leveraging all of the complex analytics completed up to this point and including the lessons learned from our direct customer interaction, Herbie is ready to help Keith develop and finalize one the last important steps before delivering the Minimum Viable Product (MVP): Documenting the product features list.

The recipe for your MVP is a list of the specific product features and benefits to your solution Click To Tweet

The product features list is a one-page document consisting of one or two sentence summaries of the top 10 (or fewer) features of the complete product vision. Essentially, this is the product development team’s contract with the rest of the company. The biggest challenge will be deciding what features will ship in what order. Developing the MVP will start the prioritization process.

The product features list is a 1 page document of the top features in your product vision Click To Tweet

Customers will be critical in guiding the process as they begin interacting with the earliest version of the MVP. You can think of features as the things that the engineering team is building, and the benefits as the problem you are solving for the customer. Your goal is to describe the specific product benefits as seen through the customer eyes (Something new? Better? Faster? Cheaper?) to then develop a “user story.”

A user story is a short narrative that explains what job the product will do. How will it solve a problem that customers are eager to fix, or fulfil a need they have? Ideally, the product solves a mission-critical problem, delivers a compelling, exciting customer benefit, or addresses an unspoken need:

  • Unfortunately, by the time a high-risk student reaches high school as a freshman, many lack both the academic and social skills necessary to see the long-term value of staying in school;
  • We lose as many as 55% by the time their class becomes seniors;
  • Educated workers are the basis of economic growth. They are especially critical as sources of innovation and productivity given the pace and nature of technological progress;
  • Studies show that the typical high school graduate will obtain higher employment and earnings — an astonishing 50% to 100% increase in lifetime income — and will be less likely to draw on public money for health care and welfare. They will also be less likely to be involved in the criminal justice system. Further, because of their increased income potential, the typical graduate will contribute more in tax revenue over their lifetime than if they had dropped out;
  • When the costs of investment to produce a new graduate are taken into account, there is a return of $1.45 to $3.55 for every dollar of investment, depending upon the educational intervention strategy. Under this estimate, each new graduate confers a net benefit to taxpayers of about $127,000 over their lifetime. This is a benefit to the public of nearly $90 billion for each year of success in reducing the number of high school dropouts by 700,000 — or something close to $1 trillion after 11 years;
  • All stakeholders who significantly impact an individual student’s decision to stay in school until graduation will receive real-time advice on how to effectively collaborate to minimize or eliminate the negative environmental elements that influence many to dropout prior to graduation; and
  • This transaction based omni-channel student lifecycle management cognitive computing system will be the tip of the spear that drives behaviors that will enable the US to achieve a national graduation rate of 90%+ by the year 2020.
A user story is a short narrative that explains what job the product will do Click To Tweet

Remember that at this early stage we are still in the process of developing hypotheses that we must test and validate with real customers. All that is required is to follow the customer discovery process with ideas that are reasonable educated guesses. The goal is to quickly move into building an effective MVP that you can put in front of your prospective market for immediate feedback and iteration.

Creating an MVP can increase development productivity between 14 – 95% while reducing costs by 7 – 29%. Being able to quickly bring a product to market, gather crucial feedback, and iterate on it in real-time is a formidable competitive advantage.

Creating an MVP can increase development productivity between 14-95% and reduce costs by 7-29% Click To Tweet

Do you feel comfortable with the process of defining your product features and benefits? Do you believe that Keith and Herbie have collaborated well up this point and come up with a great product vision? With the help of a cognitive computing system like Herbie, do you think that it is possible to achieve a national graduation rate of 90%+ by 2020?

Let me know what you think.

Can a cognitive system build the ‘perfect’ tech startup?

At this very second, somewhere in the world,  there are 3 new high tech startups opening up for business . At that very next second, there are 3 that are waving goodbye.  Every day 3 new high tech startups open for business and another 3 wave goodbye Click To Tweet To a tech insider this is hardly breaking news but to the casual observer it’s scary business. Everyone knows that “starting-up” is extremely risky, so imagine what it would be like if everyone suddenly had the ability to bring their “big idea” for changing the world to market in the shortest possible time, with the least amount of staff and at low cost. Even better, what if you could speak to an “advisor” that could definitively tell you within a few short weeks/months of being in business whether you were riding a “unicorn” or you were feeding a potential “money pit”. Imagine if an advisor could tell you whether you're riding a unicorn or feeding a money pit Click To Tweet This is the promise of the cognitive era, and that future is right around the corner.

In the story of Pinocchio, Jiminy Cricket acted as both his spiritual advisor and sage. Although it can’t mimic his personality (at least not yet), a cognitive computing system will be able to come close. It has the ability to listen to your questions, quickly sift through massive amounts of information to give you relevant answers, and continuously learn from the decisions you make so that its next answer is better. Imagine the power of having a “partner” that has access to every lesson learned by all the startups that ever existed. Lessons that they used to give you insightful advice at every stage of your building process. Your partner will help you evaluate your big idea, validate the need in the market, let you know if your idea can scale, and finally help you graduate to a fully functional enterprise.

Sound like a Tony Stark invention from the last Iron Man movie? The fantasy is not so far from becoming a reality. Very soon now, a well-designed enterprise cognitive system will be able to accomplish this and more.

It is common for most startups to stumble for months or even years trying to build the perfect product, identify their target audience and find the ideal business model, while simultaneously burning through mountains of cash and time as they go. There are many published “how to” manuals advocating a structured approach to creating a viable startup. One of the best is put forward by startup strategy specialists Steve Blank and Bob Dorf in the their tremendous reference guide “The Startup Owners’ Manual: The Step-by-Step Guide for Building a Great Company,” These guides offer an excellent methodology and terrific insights, but it’s extremely difficult to both absorb and leverage 1000’s of pages of detailed and actionable content while also executing a business in real-time. Consider the sheer volume of information involved, the expertise required to determine the veracity of the information, the variety of actions you could potentially pursue, and the velocity of change you would be required to manage, This is a key area where cognitive systems will clearly add value.

There are four phases that every startup must manage and navigate through in order to achieve success:

Customer Discovery: In this phase the business is not only trying to test the founder’s vision but also identify markets, customers, channels and pricing. Is there a market?

Customer Validation: A business model is identified and a startup sees whether it can actually sell its product or service. Is it repeatable and scalable?

Customer Creation: Once the business model has been tested, it’s time to scale. This involves building end-user demand and converting sales. What is the potential?

Company Building: Once a valid business model is found it’s time to graduate into a fully-fledged company. How can the operation scale?

The goal of a cognitive system is to proactively gather massive amount of information, offer active business insights and offer a clear path for a “founder” looking to quickly build a successful company.

A cognitive system can provide a clear path for a founder looking to build a successful company… Click To Tweet

As defined by Sue Feldman, founder and CEO of Synthexis, cognitive computing “allows people and machines to work together in easy, intuitive ways.” Cognitive systems learn at scale, reason with purpose, and interact with humans naturally. With massive amounts of information available at our disposable in structured and unstructured formats, cognitive computing enables people to effectively interact with and leverage that data.

In order to be effective in the startup world, a cognitive system must exhibit and offer four key capabilities:

It must be Adaptive: Being able to pivot your strategy as necessary to respond to rapidly changing market conditions is key to a startup. A cognitive solution will be able to monitor and predict these external changes and offer real-time advice on how to adapt.

It must enhance Interaction: There are many stakeholders (both people and technology) that must interact seamlessly in order for the business to grow. Being able to absorb and translate feedback in real-time is a key capability.

It must offer Iterative and Stateful feedback: By helping to identify operational business problems, proactively seeking supportive data to determine impact, and applying lessons learned from past actions to recommend “tweaks” in business strategy, it will significantly increase the chances of success for your enterprise.

It must provide Contextual Information: Being able to able to intuitively judge how complex elements could impact your business. For example, being able to understand how the use of certain words by internal and external stakeholders may affect your operations or how a seemingly simple change in government regulations could derail your expansion plans. These are the real actionable insights a startup needs to survive and thrive

The end goal is to translate these “capabilities” into an active support system for a founder seeking to build a solid and scalable organization. It must be able to act as an insightful “expert advisor” capable of successfully shepherding them though all four phases of the Blank and Dorf startup life cycle.

In the future I see cognitive systems capable of either producing the next “unicorn” or, even better, letting a founder know when it’s time to “turn out the lights” and say goodbye as soon as possible.

Over the course of the next four posts, I will expand on my vision on how cognitive systems will transform the high tech startup industry beginning with how to determine if there is a market for your idea.

Welcome to the cognitive era. Are you ready?

References

Blank & Dorf, “The Startup Owners’ Manual: The Step-by-Step Guide for Building a Great Company.”

http://www.cityam.com/220819/graphic-shows-just-how-many-startups-are-launched-worldwide-every-second

http://www.research.ibm.com/software/IBMResearch/multimedia/Computing_Cognition_WhitePaper.pdf

http://www.customermatrix.com/news-and-press-releases/news/159-wikipedia-definitions-what-is-cognitive-computing