Data-driven transformation—embedding data in operations throughout a company—is
becoming a question of life-or-death in most industries. Data-driven companies reduce waste and drive performance improvements far beyond historical levels, and companies that use fresh, granular data in sales, marketing, supply chain, manufacturing, and R&D can improve EBITDA by 20% to 30% over their peers. In fact, six of the ten most valued companies today are built on data—Apple, Alphabet, Microsoft, Amazon, Facebook and Alibaba—compared with only one in 2006.
But new initiatives toward data-driven transformation often fail, because companies try to achieve the transformation in giant leaps instead of small steps. For example, companies often start by trying to reinvent their core IT systems—a multiyear effort that can cost hundreds of millions of dollars. But data-driven transformation initiatives can succeed only if they are cost-effective, incremental and sustainable.
When the rules of business are being rewritten on a quarterly basis, companies need an approach to transformation that is agile, manageable and focused on results. As such, in our experience, successful data-driven transformation initiatives start with small-scale, rapid
digitization efforts that lay the foundation for broader transformation, and that generates returns to help fund later phases of the process. Companies can then draw on knowledge gained from early wins to create a roadmap for companywide transformation, industrial data/analytics, and build new capabilities to execute new data-driven strategies and processes.
For example, a large industrial company considered a massive digital transformation of its core infrastructure, but it did not want to tie up capital in a massive change program. Instead, it opted for a few quick-win initiatives in inventory management and capacity optimization, which have generated $20 million in value in nine months. Applying the lessons from its early wins, the firm then created a roadmap for 10 major data-transformation initiatives, from demand-forecasting to managing the outbound sales force. The overall goal of these efforts is to unleash $200 million in value over three to five years and help the company raise its EBITDA margin by 2-4%.
We’ve found this step-by-step approach faster, less expensive, and more likely to succeed than starting with a system-wide overhaul. In our experience, by using existing data systematically and combining it with external data, companies can generate results fast, with some achieving 20% of the potential of a full data-driven transformation within as few as six months.
The promise of data-driven transformation has captured the imagination of leaders throughout the business world, who are inspired by the idea of using data to make better decisions and implementing digitizing processes to improve performance. Beware that these forces can also encourage companies to try to achieve sweeping, companywide change to go digital, which can lead to counterproductive overreaching.
This contest will not be won by making huge bets. The winners will be agile, pragmatic and disciplined.
