Enterprise leaders are under pressure to perform and transform simultaneously—to keep business-as-usual running smoothly while also disrupting from within to drive results. This takes a certain mindset that is all too rare—and the beliefs that enable courage, innovative thinking and radically human communication. But it also requires new ways of working across the business.
“Things are moving more quickly today, and organizations need to build an innovation engine within their operational model,” says Bill Randall, a Senior Client Partner with Korn Ferry’s new Applied Enterprise Innovation team, which aims to help large APAC organizations innovate at speed and scale. “This is the ‘how’ that supports the perform-transform mental model.”
How transformation becomes business-as-usual
Leaders are looking for new ways to innovate at scale, but they face many problems. They are worried they’ll be disrupted before they begin shifting their own business, but they’ve also seen too many failed transformations. They want more ROI from their tech investments, but development teams feel handcuffed by slow policies, processes and culture.
“Innovation at scale is not about special people, special times, or special projects,” says Randall. “Innovation is about everybody’s everyday job and the core mechanisms we use to get business-as-usual done.”
Randall works with Senior Client Partner Eric Tachibana to help leaders implement a scientific model for business transformation. It’s a process that drives innovation across all products, not just one, and becomes intrinsic to the way everyone, across every level of the organization, does their work.
“The Working Backwards toolkit is a fast, cheap and powerful way to find out truths about your market,” says Tachibana. “And it can result in 10 to 15 big, game-changing ideas and thousands of small business improvements at any point in time.”
The core idea is to work backwards from the customer. It’s not a new idea, but as Randall observes, “organizations have lost their customer obsessiveness. Day Two administrative focus has taken over.”
The magic of the Toolkit, is that it is engineered into everyone’s day job. And that makes it a unique approach in the field.
“You don’t need to work with thousands of employees to make them customer-obsessed or entrepreneurial—they become customer-obsessed as a by-product of simply using the tools,” he says. “This is the scaling, democratizing magic of the model’s mechanisms.”
Mechanisms to drive innovation at scale
Two elements underpin the Working Backwards Toolkit: mechanisms and mindsets. Mechanisms are experimental tools grounded in the scientific method.
“A scientist looks for patterns and generates a hypothesis to try to explain them,” notes Tachibana. “They then design experiments to validate or invalidate that hypothesis. If enough experiments validate the hypothesis, it’s escalated to a theory. If the hypothesis is invalidated, the scientist goes back to observation and pivots to a new hypothesis.”
While the scientific method looks at natural phenomena and asks questions about the laws of nature, the Working Backwards Toolkit explores economic markets and asks questions about product-market fit.
Specifically, the Working Backwards Toolkit helps teams to discover three things before making big investments:
- Customer validation: Does the customer exist and do they have the problem we think they do?
- Solution validation: Can we design a solution that will delight the customer?
- Business validation: Can we make money as a business by solving this problem?
“Most leaders tend to jump straight into solution mode,” explains Randall. “One of the things they find most eye-opening in this process is customer validation. They don’t usually dive into the deep behavioral issues or needs that actually drive customers.”
Tachibana says most new product failures are due to issues that could be identified through those three mechanisms.
“85% of new products fail, and the reasons they fail are unexpectedly simple,” he says. “First, they fail because we assume there is a customer for the solution, but, when we launch the product, we realize those customers don’t exist. Second, the customers exist but they have a different problem to what we expected. Third, the customers and problems exist, but our solution doesn’t actually solve their problem. And fourth, the customers exist with the expected problem, and the solution delights, but we can’t figure out a way to make money at scale.”