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How Lean Startup Techniques Can Work Even Better For Established Businesses

2016 August 31

In 2013, startup guru Steve Blank published an article in Harvard Business Review, titled Why The Lean Startup Changes Everything, in which he argued that, rather than follow the rigid concepts taught at business schools, entrepreneurs who seek to start a business take a much different path.

“Start-ups are not smaller versions of large companies,” he wrote. “They do not unfold in accordance with master plans. The ones that ultimately succeed go quickly from failure to failure, all the while adapting, iterating on, and improving their initial ideas as they continually learn from customers.”

That’s good advice for startups, but it also applies to anyone looking to bring a product to market and there’s no reason that established firms can’t follow it as well. In fact, Experian, the global data giant, has found that by leveraging its vast resources and deep customer relationships, lean startup techniques can be a great fit with its existing business.

Customer Development Before Product Development

One of the central tenets of Blank’s philosophy is that “no business plan survives first contact with the customer.” That’s why he urges startups to “get out of the building” and talk to potential customers before beginning product development in earnest. There’s no use going to engineers with detailed product specifications before you know what the customer wants.

For Experian, that’s relatively easy. It already has hundreds of customers in a wide range of industries and it regularly talks to them about issues they’re having. In fact, at Experian Datalabs, a unit the company set up specifically to pursue disruptive opportunities, they keep a running list of data problems that customers want them to solve.

A typical situation recently occurred at a meeting with a large bank, where one of the senior executives said, “You know we have a problem that’s really giving us trouble. We have a lot of newer businesses that come to us for credit and we need to do due diligence on them. So it’s an incredibly labor intensive process for us to verify whether they are a good credit risk.”

Eric Haller, Global Head at Experian DataLabs just smiles when he hears things like that. “We regularly sit down with our clients and try and figure out what’s causing them agita,” he told me, “because we know that solving problems is what opens up enormous business opportunities for us.”

The Minimal Viable Product

Experian DataLabs is an unusual organization. Part research lab, part skunk works, its purpose is to solve exactly the type of problems that the bank executive complained about. With dozens of PhD. level data scientists spread across three different continents, it can bring together an enormous amount of expertise to bear.

In the case of the bank, the team was able to put together a prototype and present it to the client within 90 days. It wasn’t perfect, the system could only identify 20% of the bank’s potential customers that had no discernable credit history, but that was enough to show the potential of their approach.

This is what is known in the lean startup world as a minimum viable product. Its purpose is not to wow anyone with exquisite design or top notch performance, but rather to test a hypothesis. In this case, Haller and his team only needed to know whether the customer would indeed be willing to pay for the product they had asked for.

Notice how much easier this process is for Experian than it would be for a startup. Haller didn’t need to work to get in the door, the bank was already a paying client. It also wasn’t hard to identify a need, the bank executive was almost literally crying out for a solution. Within weeks of presenting the prototype, Experian had a preliminary contract.

Iterate And Pivot

Another tenet of Blank’s philosophy is that you initially build a product for the few (or in Experian’s case, the one), not the many. It is the passionate early adopters who help you to gain traction, see what works and what else may be needed to make the product successful. This isn’t market research, but hands-on problem solving.

Once the DataLabs team validates the client’s interest—due to intellectual property issues it almost always asks for a signed agreement before going beyond the minimum viable product stage—it begins to co-develop the product according to the client’s specifications. This tends to be an iterative process, with a number of versions going back and forth.

In the case of the credit product described above, over the next 3 months new features were added, such as a more helpful user interface, integration with other systems like auditing and workflow management and customization options. Many of these improvements would not have been possible without the client’s input. Performance was also improved. Now the system was able to verify 50% of the “no hits” that were frustrating the bank.

It is at this stage that the new product is presented to at least one of the client advisory groups that Experian maintains in functional areas such as credit, fraud and marketing services to see if there is more general interest. The additional consultation also makes it possible to pivot to different functionality, customer segments or revenue models, if needed.

Rolling Out The Product

Once the product and the business model has been validated by Experian’s current customers and further input is taken from Experian’s client advisory groups and internal marketing staff, it is ready to be rolled out to the larger market. That’s when the rest of the Experian organization gets involved

Engineers scale up the technology to ensure that it can work in a larger environment. Product managers work on issues such as pricing, legal compliance and positioning. Sales staff are trained so that they can handle client questions and a promotional campaign is designed and executed. Every aspect of the product and the business model is refined and strengthened.

This process can take anywhere from three to twelve months, depending on how much integration needs to be done with Experian’s existing systems. That’s not particularly fast by the standards of a startup, but it’s not altogether slow either and it brings all the resources of a $4 billion company to bear, something that no startup can match.

In the case of the credit product, it will be formally rolled out this summer under the brand name BizVerify, about six months after the decision was made to move forward, which is about average for DataLabs projects. At the time of launch already has three paying clients and an army of salespeople with established relationships supporting it.

The Goliath Advantage

We tend to favor Davids over Goliaths and that’s especially true in business. There’s something uplifting about a billion dollar business being hatched in a garage or a coffee shop. Stuffy executives in boardrooms are far less romantic. Yet that shouldn’t blind us to the fact that startups make for such enticing stories precisely because they are so unlikely. Most fail.

Clearly, large enterprises have things that slow them down. They must serve the present. Things are expected of them. They have to keep customers, employees and other stakeholders happy. But while small, agile firms can move fast, larger enterprises have the ability to move deliberately. They have loyal customers and an abundance of resources.

What struck me when I spoke to the executives at Experian was how large firms can leverage these assets to make lean startup techniques far more effective. Customer relationships are already developed and capabilities are already in place. Another factor is scale itself. Startup firms usually only get to make one bet, but Experian DataLabs has a dozen or more disruptive projects going on a regular basis.

So Steve Blank was right. The lean startup does change everything. And not just for startups.

– Greg


A previous version of this article first appeared in Harvard Business Review

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