In 1995, if you were to print out all of the data captured by customer-relationship management systems, you could fill file cabinets covering one square block on the island of Manhattan. Repeat the exercise today, and the file cabinets would cover the entire island. The amount of customer data we have access to has increased by 110,000 percent over the past two decades. But over the same period, forecast accuracy has actually dropped from 84 to 76 percent, according to academic researchers. And last year alone, U.S. publicly-traded companies mis-forecasted over $2 trillion in revenue. The key takeaway is that data alone won’t move the needle when it comes to improved performance. Instead, putting data to work is what really counts.
This week at Dreamforce, Salesforce.com took its own swing at harnessing the power of data with the debut of Wave, its long-anticipated Analytics Cloud service. While there are still many open questions about the new offering, it’s clear that Wave moves beyond many of the incumbent visualization and discovery tools with its gamified user interface (Salesforce’s term) and mobile-friendly architecture. While Wave will most certainly add a new arrow to the quiver of front-line business users, it falls short of the more radical transformation that will allow companies to move from data-driven discovery to data-driven execution. The good news is that such a transformation is already underway. Here are a few of the insights I’ve gleaned from customers and partners that are breaking new ground in their efforts to connect data with action.
Use your data to break the rules
LinkedIn has leveraged the massive trove of social data it has collected to totally change the way territories are defined and managed by reps. Conventional wisdom dictates that territories be defined geographically and that reps be assigned based on physical proximity to any given patch. Companies take this approach because they assume that reps have a stronger local network. But in an increasingly transient society, that’s no longer the case. So LinkedIn takes a different approach. It generates a “social proximity index” score for reps by assessing their relationships and then builds territory assignments around those relationships. A rep may be calling on an account on the other side of the country, but a close relationship usually proves to be much stronger than a geographic divide.
Humanize the data
Members of the IBM Watson team call out another key factor in putting data to work -- humanizing it. Historically, programmatic computing has forced people to adapt to the machine and to speak the way it does (insert your favorite programming language here) and ask questions based on rigid protocols (any SQL programmers in the house?). But the premise behind IBM’s cognitive-computing initiative is that machines should conform to the world of humans.
Case in point -- a new joint venture between C9 and IBM Watson called Sales Advisor. This solution allows sales reps to ask questions using the vernacular of, well, a sales rep. When, for example, a rep types, “I need some pointers on how to bridge with the CTO,” IBM Watson uses natural-language processing to understand the intent behind the question. It then scans a massive corpus of unstructured sales data aggregated by C9 and returns a set of responses that describe how to run a productive meeting with a chief technology officer. To serve up that kind of interactive experience, you need a true application, not just a set of visualization tools.
An insight in hand is worth two on the PC
Marketo’s data strategy centers around keeping a rapidly expanding, global sales organization on the same page when it comes to sales execution. To do so, they’re looking to harness technologies that expose reps to critical insights in the “moment of decision” via mobile devices. Rather than put the burden on the rep to search for relevant information, Marketo is starting to tap into solutions that are context-aware and capable of serving up appropriate information. For example, reps can pull up C9’s Mobile OppScore from their phones to get predictive data on whether or not a deal will close and recommendations on the immediate actions that will move deals forward.
A new view on data
Over the past two decades, companies set their sights on learning everything they could about customers and prospects. While new solutions like Wave allow us to discover interesting new facets of the data we’ve collected, the most exciting innovations are focused on delivering more actionable insights in the moments when they will count the most.
Michael Howard is chief executive of C9.