Should Big Data Drive Big Decisions?
This year, many companies are taking on big data – ramping up tools and technologies to find signals and insight in unstructured, often external and generally messy data. While big data may be ready for business, are business leaders ready for big data?
Big data analytics can open a window into an intricate world of customers, employees and operations that hadn’t been easily accessible before. While leaders can gain fresh insights that are immediate and real, should they use big data to drive far-reaching business decisions?
Here’s the debate:
|Big data can complicate big decisions.
Big data insights are often unfiltered and identifying the exception to the rule. It could be a mistake to dismiss the experience and time-tested resources that have served decision makers well, especially when it comes to broad strategic decisions.
|Big data can drive big decisions.
Leaders who harness big data insights can maintain the strategic direction of their businesses, while using deeper insights on customers and operations to gain a jump on their competition in tactical plans.
|Good decisions come from clean data.
Big data analysis is often based on complex algorithms that try to make sense of noisy data. The results can often be inconsistent and inconclusive. Business leaders may over-react or get distracted by weak or faint signals.
|Good decisions come from sound analysis.
Decision makers need qualified analysts to filter out the noise so they can appropriately react to patterns in the data that can provide leaders with a more holistic, multidimensional view of their customers, employees and operations.
|Big data provides little insight.
Real-time access to tweets, posts and operational data may spur kneejerk reactions to short-term problems. Instead, management should focus on improving long-term performance.
|It’s the little things that matter.
It’s the small things that are likely to engage customers and employees – or drive them away. Likewise, small tweaks in operations can result in big improvements over time.
|Business needs consistent strategies.
Leaders shouldn’t make significant strategic changes based on the shifting sands of big data analytics. Big data should be left in the hands of operational managers.
|Business needs pliable strategies.
Strategies should allow for flexibility so that the business can take advantage of potential changes in customer sentiment, operating model improvements and emerging trends.
Greg Szwartz, Director, Deloitte Consulting LLP
We’re seeing many companies adopt big data this year to get a better perspective on their customers, employees and operations with the goal of finding new insights in data from across and outside the enterprise. But accomplishing this goal will likely require leaders to adopt a new mindset and build stronger relationships with analysts who can help them interpret new signals. Decision makers who are accustomed to waiting weeks for analyzed data may find real-time data streams overwhelming. A few may face decision paralysis or, perhaps worse, send their troops off to resolve a fleeting problem.
To maintain focus, decision makers should use big data to answer specific questions. For example, one financial institution wanted to know why customers close accounts. They analyzed their databases to identify a stream of seemingly unrelated events that were likely to lead up to an account closing. As a result, they established an intervention process that’s initiated when a customer starts down this path – perhaps before the customer even thinks about closing their account.
Use big data to think small. Discover ways to tweak operations to prevent accidents. Pinpoint employees who are likely to leave. Foresee the next product a customer could need. But, use big data insight with a degree of caution. Test insights with micro-strategies targeted to address the specific situation. Based on what you learn, build on these small insights to influence – but not drive – the broad business strategy.
Big data analytics often illuminate the exceptions to the rule, testing the willpower of even highly disciplined leaders. We expect that the winners in the big data race will not compromise their strategic vision, but rather may make plentiful profits by exploiting the exceptions.
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