Rich Data, Poor Results: Four Reasons Big Data is Failing Your Sales Department
I have no data to back this up, but it seems that the jargon cycle is accelerating. Today’s technology buzzwords have shorter half-lives than their predecessors, for reasons I’m not entirely sure of. It took about a decade for people to start calling “color TVs” what they were – TVs. It took perhaps five years for “social CRM” to go back to just being called “CRM.” And it’s amazing how quickly the term “big data” has faded from frequent use. Data is just data – its relevance depends on much more than its bigness. The buzzword “big data” did serve a purpose: it alerted businesses to the information resources locked within their digital systems, a resource that was sitting idly awaiting the time when businesses could tap into it. But that realization has only made this data more tantalizing, yet frustrating, for businesses who don’t realize how to tap into it. Many await a pre-built report or an alert that will by itself find a crucial bit of insight that will transform their businesses. That passive approach is doomed to failure. To make data work for you – especially sales data – you have to be active, engaged, and unafraid of making the occasional mistake. Being active in a smart way means realizing a few important points about data: Data sets are only valuable in relation to other data A single set of data is nice; it can be measured chronologically (another set of data) or examined cumulatively. But that’s where the insight ends. What makes data powerful is the correlation of one data set against another. For instance, if you wanted to understand whether time on the job led salespeople to be better at margin protection, or if it drove them toward discounts, you might compare average margin percentage per deal vs. tenure of sales staff. Those are two distinctly different sets of data. Another example: if you wanted to illustrate the value of acting quickly on leads, you might compare deal size vs. the time between a lead being passed to sales and sales acting on it. These correlations are what identify the behaviors you should encourage and which ones should be shelved. Even if, as a manager, you have a “feel” for what works and what doesn’t, this kind of analysis allows you to put real numbers behind your assumptions – and gives you greater credibility in coaching your sales teams. It also allows you to prioritize the behaviors you want to influence. However, many sales managers don’t have the luxury of comparing data sets. That is because… The more disconnected systems you have, the less effective your analysis will be If plugging data into an analytics tool is a drag-and-drop or point-and-click task, you’re likely to do more digging into the data to test ideas and uncover insight. If doing that analysis means manually pulling data from various systems and re-inputting it, that analysis is not going to get done. The return on that analysis may still be greater than the cost, but realistically speaking, people simply won’t want to do it. The explosion of analytics and reporting tools has led to products that are actually enjoyable to use, if and when the data is in a usable condition. They invite analysis and comparison, and allow the exploration of several ideas in a shorty period of time to reveal insights. When analysis is drudge work, that exploration of the data is curtailed, and it’s less likely that insights will be revealed. Having a set of customer-facing software solutions that work together short-circuits the data problem and allows analysis by more people, leading to more insight. But it’s not all about the software – it’s also about the imaginations of the people doing the analysis. That’s why… Sales managers need to learn to think like SABERmetricians To those unfamiliar with the term, “SABERmetricis” was the study of baseball statistics pioneered by Bill James and the members of the Society for American Baseball Research. Baseball had its standard set of statistics, but they often failed to paint a complete picture of the effectiveness of individual players. By looking at easily-obtained data differently, James and company reinvented how baseball talent was evaluated (as dramatized in the movie “Moneyball”). The data was the same, and even the means of analysis was the same. The big difference was that the analysts looked at the data in new ways. Sales managers need to employ similar thinking to extract valuable insight from data. The standard metrics still apply, but mixing and matching data sets and correlating behaviors to results can provide more focused insights, often ones that are surprising. Doing this effectively confers a competitive advantage – if you’re really thinking about getting a leg up on competitors, you don’t want to examine data the same way they do, but instead examine it in a way that’s uniquely effective for your organization. All the analysis in the word won’t guarantee results, though. Context is key, and that’s why… Human input is the secret ingredient in turning information into insight Just as sales force automation software didn’t replace salespeople, insightful research will never replace sales managers’ judgement. A failure to understand context can cause important insights to be ignored, or to give inordinate importance to insights that aren’t really that vital. The sales manager must assume the role of the final arbiter of the importance and applicability of insights drawn from data; he or she should explain why a nugget of insight is important. On occasion, because of statistical anomalies or a badly-applied use of analytics, the data may give a false impression of what’s going on. It’s up to an experience human to spot those outliers, track down their sources and ensure that data doesn’t steer the sales team wrong. Want to learn more about the best ways to turn data into sales results? Attend “How Your Rich Data is Leaving You Poor,” a session at Dreamforce 2016 hosted by CallidusCloud and featuring several business leaders who have successfully harnessed data to improve sales performance. The session is October 6 at 1 p.m. at the Marriott Marquis Hotel, Yerba Buena Salon 4-6. Register for the session here!
Chris Bucholtz | September 20th, 2016