The human element of change is always the trickiest. Supply chains and marketing models can be changed, with many variables optimized for success. But humans? Well, humans tend to be the least predictable element of any corporate transformation.
Until now. The advent of advanced analytics opens a transformation door for companies that didn’t exist just five years ago. Using data from over two decades of corporate transformations globally, Accenture now has an insights-driven approach—a transformation GPS of sorts—that can predict the best change routes for individual companies based on their specific variables.
Through machine learning and prescriptive analytics, change leaders can use the insights generated in a tailored prescription for change—one with the highest probability of meeting their unique transformation needs.
The myth of low-hanging fruit
Without a deep understanding of what drives real change in their specific organization, many executives often target either the lowest performing areas or the areas easiest to fix. More often than not, when we apply analytics, those are not the drivers with the greatest overall impact on the transformation.
Using a conventional approach, transactional change drivers like communication often are heavily emphasized even though they tend to have a small impact on performance. If instead, leaders focused on even modest improvements in change drivers like emotions and team leadership, most companies could reap significantly more benefits. Trust in leadership and other emotion-related drivers influence up to 60 percent of performance improvement in large-scale transformations.
"Proceed directly to your route"
As we work with clients on large-scale transformations, we see some approaches that help smooth the ride:
Measure change as rigorously as financials. No company would forego measuring revenues, yet many forego measuring innovation and transformation, which lead to revenues. Consider Accenture research that found half (53 percent) of companies consider innovation an "ad-hoc creative process." In contrast, high performers employ innovation that is more persistent and requires the courage to change at a fundamental level.
Account for context. Situations and contexts for change are fluid. The factors to emphasize depend on where your organization is today—and they will likely change tomorrow. Data science can help change the road map as your situation and needs change.
Make invisible factors visible. Traditionally "invisible" factors like employees’ fear or frustration and team leadership’s ability to enable change hold great power because they can inhibit change. Combining the "hard" and "soft" issues contributes to the whole-brain leadership Accenture Strategy research shows is essential to success. Today, only eight percent of companies utilize whole-brain leadership.
Don’t just measure. Prioritize. Then act. No organization measures their way to success. Put simply: if your organization doesn’t have the cultural capital to change with the data, don’t squander investment in measurement. The value comes from real action.
Find the courage to ask the tough questions. With over half (57 percent) of CEOs we surveyed reporting that employees have become more powerful corporate stakeholders over the past three years, gone are the days of top-down, command and control communications. Having the courage to listen to learn, rather than to respond defensively to the insights from the data, is key to engaging employees with respect and building trust. Leaders must be willing to hear the answers to the tough questions and act appropriately.
Combining the best human intelligence of your leaders with machine intelligence, while taking into account your employees’ feelings about where you’re asking them to go, is complex. But it’s far simpler and wiser than going the historical route of change, which was sometimes an art but not at all a science. And at its worst, was akin to throwing darts at a board to see what sticks.