In today’s fast-moving marketplaces, the gap between creating a strategy and executing it is getting shorter by the day. No longer can a business in any sector afford to spend six to nine months researching, developing and fine-tuning its strategy before starting to execute it. If it does, then the market will have moved on so far that the strategy will already be obsolete before it’s off the drawing-board.
Instead, what’s needed is an approach based on harnessing the wealth of data that’s now available to all businesses, using it develop a “minimum viable strategy” (MVS), and then kicking on with executing this strategy at pace. It’ll be apparent very quickly whether it’s working and what tweaks are needed. And once in execution mode, the strategy journey can evolve and flex with the market as conditions change.
All of this may sound straightforward enough. But all too often, I find that management teams push back against creating a data-driven strategy with the MVS approach on the basis that their internal data isn’t yet good enough. “We need to clean it up first,” and create a “data lake” they say. “Then we can analyse it to work out what our strategy should be.”
At first sight, you might think this is a sensible way to become a data driven business. But you’d be wrong. To illustrate how the MVS concept can work, I’d like to share a story about soggy fries as an example, as told by various Twitter executives. Stay with me on this – I promise it’ll be worth it.
It goes like this. A company selling deep fat fryers to restaurants across the US wanted to know where to target its customer service and support teams to greatest effect – driving efficiencies and higher revenues through cross and upsales. It knew its fryers weren’t being used in the optimal way by its customers in some regions of the country, but it didn’t know where these areas were. And its internal data gave it no clues.
So the company decided to tackle the problem from the other end – with the question it was trying to answer. It went onto Twitter and ran a geographical analysis of people mentioning “soggy fries”. The regional distribution of poor dining experiences showed where its customers needed more help using its fryers: precisely the insight it needed to allocate its teams to the right areas.
To my mind, this shows two things. First, don’t just rely on the data within your business – there’s loads of potentially valuable information out there already, much of it available for free. And second, the first step towards the right strategy is pinpointing the question you want to answer. That then leads you to the data which can help to develop your strategy, and allow the business to run effectively while giving investment capacity to fund other innovative and strategic moves.
Of course, when it comes to the critical enablers for an agile strategy, a readiness on the part of management to fully embrace the power of data is just one. Our research on traits of truly agile businesses explores several best practices that leading companies adopt to drive business agility and while insights obtained through effective use of both internal and external data sources are only one factor, they can influence decisions at every stage of the strategy journey.