“So, what’s your idea?”
If you’ve ever talked about starting a company, that is the first question you always hear. It’s a simple question, but implies that companies are built from ideas – moments of inspiration where you see something no one else has seen. In reality, that is almost never true. Almost every kind of business model has been tried at some point in history. With 7 billion people on Earth, chances are that there are a few people with the same ideas that you have.
What, then, are great companies built on? There are billion-dollar companies being started right now, somewhere, by someone who is most definitely not a billionaire yet. What is their secret?
Great businesses are built by solving problems. A problem is the difference between what a person wants/needs and what they can get today. Some example problems and the companies that were built to solve them:
Even video game companies are solving a problem – they help you avoid being bored and make you happy. Some of these might not seem like problems because they have been solved so well by these companies, but if that company disappeared the problem would reappear. Not all problems are created equal, as problems can range from minor inconvenience to life threatening. You can often tell the difference by understanding how much a person is willing to pay to make the problem go away. For example, someone might be willing to pay $0.99 for a mobile game to entertain them for a few hours, but they would pay thousands of dollars for a new chair that relieves their back pain.
Almost all problems have solutions that already exist but can be improved. For example, in the early days of the internet the biggest problem was how to find anything. Yahoo solved this problem with their directory. Then Alta Vista, et al, solved the problem more effectively with search engines. Then Google solved the problem even more effectively with a more advanced search engine. I expect sometime soon that there will be an even better solution, continuing the cycle of solution improvement and company creation.
If you can solve a difficult problem in a way that is cheaper, easier or better than existing solutions then you create value and can make money. The more acute the problem and the more valuable the solution the more money you can make in solving the problem.
But wait, you say, what about Snapchat and Facebook? They were started by teenagers and solve no obvious problems, yet have become huge! Well, the irony of life is that you don’t need to be aware of a problem (or how big it is) in order to solve it. In many cases, companies that are overnight successes hit upon problems that no one else was aware were problems (or that could be solved). No one understood a huge problem with existing social networks until Snapchat provided an alternative, surprising even the Snapchat team themselves. You can get lucky in this way, but it’s rare.
Starting from a problem provides a very useful framework for focusing your business as you grow. By always starting from the problem:
After you choose your problem, I suggest posting it somewhere prominently in your office. Reminding everyone on your team, day in and day out, what problem you are solving will bring focus to everything you do.
So, what problem are you solving?
This post originally appeard at Sean’s blog, “Sean On Startups.”
As social business matures, it creates exciting new engagement opportunities for customers, employees and partners. Forward-looking ompanies are leveraging this phoenomenon to reinvigorate their products and to engage their stakeholders. IBM has been a major proponent and adopter of social business. IBM Connect is a major event for showcasing social software and technologies. For this year’s IBM Connect, Social Engagement Center was one of the main attractions.
The Social Engagement Center at Connect demonstrated the power of a sophisticatd analytics engine, flexible and easy-to-setup views, eye-catching visualizations and the ability to integrate enterprise data alongwith social. Kudos to the MutualMind team that made it happen.
We also had the opportunity to support a very interesting competition: The annual “App Throwdown.” This was a competion among startups who had integrated with IBM products. This compeition took place on the big stage of third day’s opening general session. App Throwdown winners were selected based on “social votes” from the audience and MutualMind provided the results using its real-time analytics. Sandy Carter, GM of Ecosystem, was on stage to announce the winner. Watch the video of the event – MutualMind is mentioned at 1:09.
A Pair of Paradoxes (Paradoxi?)
When I worked on the Agency side, I frequently referred to “the PowerPoint Paradox.” This is the inerrant, often depressing reality that the most-often approved ideas aren’t necessarily the best, but the ones that look the best in a slide deck. It’s that the creative “value” of an idea isn’t measured in the free market of the Public, but a transaction between people working for the Brand (often former Agency types like me), and the Agency people they’ve hired. Rare was the client who would use experimentation and empirical evidence to evaluate an idea, and these were the relationships where you REALLY got to have fun.
The Codebase Paradox
Fast forward now to my work leading the roadmap and development of a technology platform, and I feel the same emotional tug — but this time with new players. We work in Big Data with all the appropriate capital letters, specifically, that from social media. And for what may very well be the first time in human history, the digital world is practically our oyster. Cloud computing, open source architectures, linguistic analysis and available data APIs have all matured at don’t-blink-or-you’ll-miss-it speeds, making practically any product or creation you can think of possible. So when you’re constantly bathed in this sea of possibility, its extremely easy to become enamored of the things that seem to push the limits of what can be done and find new frontiers.
Maybe label it the “and here’s how I did it!” factor — many of the offerings that seem to be the best products must involve an explanation of how it was done. It’s the data visualization or statistical correlation or semantic learning natural language sentiment entity detection processing nested algorithm that appears cool because it exists. I am NOT immune to this feeling, and I completely get it — when a developer has been working hours on end on a feature or product, you have to appreciate the effort, particularly when they tell you all the hoops they had to jump through to make it work.
But it’s here where the hard question must be asked: does more technical wizardry make a better product?
Reward the Decisions, not the Database.
Before sitting down to create ANY data product, teams that hope to have a shadow of success MUST agree to three truths:
These statements make us automatically — and radically — readjust the lens of judgement we use to evaluate What We Shall Build. If my job is to help a user make a better decision, it’s often the most simple products that get them there. In fact, if there is any technological tour de force to be accomplished, it’s often completely hidden from the user behind the fog of “it just works.” This flips the reward system entirely: products aren’t lauded for their complexity, but for their effectiveness.
Don’t. Be. Afraid.
My best advice for anyone else working with data day-in and day-out? Don’t be afraid of the red pen. In my Agency days we would also have “tissue sessions”: all the creative was printed and posted on big boards around the room, and we started tearing down what didn’t work. You couldn’t fight for your own “baby,” because we had one goal: making brand narratives more compelling, and hopefully, doing it for a client that wasn’t trapped by the PowerPoint Paradox.
Likewise, technology companies MUST make these decisions. They must look each other in the eye, swear a solemn pact to value the user, and be ready to build what they need — whether easy, hard, or somewhere in between.
For those of us who live and breath social data, we are well aware of the challenges that it represents. Over the last few years,
social data has rapidly moved as a novely to something that is now an essential component of business intelligence for organizations of all sizes and types.
Big Boulder Initiative, a concept that Gnip introduced in its annual Big Boulder conference, is one attempt at tackling these challenges. The mission is “To establish the foundation for the long-term success of the social data industry.”
Since the announcement, Gnip has hosted a number of meetings in different US cities, inviting customers, data providers and other stakeholders. Eric Swayne, Director of Product and Marketing at MutualMind participated in the San Francisco meeting. Here’s a peak into the discussion in that session.
Want to read more? Follow this link for a PDF document that provies a very good recap of the meetings and the action plan. Susan Etlinger, a participant in the San Francisco session, presented her viewpoints in a blog post about the big questions to be addressed. And if you’d rather watch a video, here’s a short clip.