In the future, algorithms and users will do what your employees do today.
Every business is an engine. It needs to do a certain set of things repeatedly to create value. If you haven’t figured out that set of repeated operations, you probably haven’t created a scalable business yet.
Ford needs to repeatedly assemble cars, Google needs to repeatedly run its crawler, Facebook needs to repeatedly get users to interact with other users.
Every business goes through three stages:
Creating the engine: Early stage, figuring out the set of repeatable operations it needs to do to create value.
Oiling the engine: Rapid testing and iterating to refine and optimize the repeatable operations
Stepping on the gas: Scaling by repeating the repeatable operations
So this is the formula for building a business. You figure out how you are creating value. You identify a set of operations that repeatedly create value. You figure out a way to efficiently conduct these operations repeatedly.
There are three broad ways that businesses conduct these operations repeatedly and get things done:
Let’s think through the problem of navigating the web for the most relevant information for the day. Three companies try to solve this in three very different ways:
Yahoo: A bunch of editors decide the best content for the day
Google News: Algorithms decide the top news of the day
Twitter: Users’ tweets and retweets decide the top news of the day.
For those of us who read the earlier article on the three broad models for problem-solving, here’s the interesting part. These three approaches correspond exactly with the three models for problem solving.
A brief recap of the three approaches to problem solving
The ‘stuff’ approach: How can we create more stuff whenever the problem crops up?
The ‘optimization’ approach: How can we better distribute the stuff already created to minimize waste?
The ‘platform’ approach: How can we redefine ‘stuff’ and find new ways of solving the same problem?
Essentially, the three approaches to building a business now are:
The ‘stuff’ approach: Get employees to do the work
The ‘optimization’ approach: Get algorithms to do the work
The ‘platform’ approach: Get users to do the work
Depending on which approach you take, the way you build your company could vary significantly.
A platform thinking approach to building a business involves figuring out ways by which an external ecosystem of developers and users can be leveraged to create value. The iPhone app store does this, YouTube does this, and so does Wikipedia.
It’s important to note that we are talking about repeatable operations. Writing code is not a repeatable operation. It is a one-time infrastructural activity, similar to building out the assembly line or setting up the factory. The operations that the code automates (e.g. login management) are the repeatable operations.
Most problems that could be fully automated are already automated today. The next level of scale will come not by automating alone (and letting algorithms alone do the work) but by leveraging an ecosystem ( and letting algorithms synchronize disparate actions).
There are very few companies that compete purely on the strength of algorithms. Google is a rare example of a company whose competitive advantage lies in a set of very complex algorithms that it fiercely protects. Facebook, Twitter, YouTube etc. compete not on the strength of their algorithms but on the strength of their ecosystems. The algorithms are easily replicable but the ecosystems aren’t. Hence, building a business where the ecosystem scales the value creating operations is quite different from building a technology-only company.
Scale is achieved by making repeatable processes more efficient (faster/cheaper) and effective (accurate).
One of the ways to infuse platform thinking into your business is to look at a problem that is being solved manually, and repeatedly, and see if it can be solved by external users instead.
Facebook realized that it would have to translate its interface for every new foreign language. The norm was to do it with an in-house or outsourced translation team. Facebook chose to crowdsource it, building not just a more scalable model, but in many cases, better translations as well.
This is also demonstrated in the evolution of an online community. Quora started off with employees asking questions and answering them. Over time, it transitioned both these activities from the employees to the users.
The problem that comes with this, of course, is that you let out control and with that you need to build in checks and balances to ensure that no one is gaming the system. Quora and Reddit offer good examples of bringing in these checks and balances and scaling them along with the community.
What are the repeated chunks of work in my business?
The first part involves identifying the activities that need to be repeated to scale and expand the business.
Who is doing the work today?
Secondly, is the work being done manually or algorithmically? If so, can we bring in greater efficiencies (speed) or effectiveness (accuracy) by leveraging an ecosystem?
How can we get someone else to do that work?
Finally, users, like employees, need incentives. Fitting in the right organic and inorganic incentives forms an important part of relying on an external ecosystem to build value.
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