Whiteboard Video: A Tale of Two Manufacturers

Meet Bob and Kevin. They’re both high-level managers responsible for pricing at industrial manufacturing companies. Both of their businesses were growing and becoming increasingly complex with thousands of products, thousands of customers and large sales teams.

They were tasked with managing prices and hitting profit goals, only Bob and Kevin took very different approaches to setting the right price. Kevin took a manual, hindsight analytics approach. Bob took another route, price optimization.

So, who came out on top? Watch this short three-minute whiteboard video to find out:

A Tale of Two Manufacturers

A Tale of Two Manufacturers

If Sales Data Doesn’t Help Decisions…Don’t Do It

vladoHarvard Business Review recently published a great article on the one factor that matters in whether or not a sales data solution will be successful. In his words:

“It’s not the data and technology that matter. What really matters is how technology, data and analytics can help salespeople, sales managers and leaders improve fundamental sales force decisions and processes.”

This article is spot on. There is huge potential when companies can combine experience, data and technology to fundamentally improve the way they make decisions. Over the next several years, the sales profession will be transformed more than any other role in B2B companies with the emergence of so much new information and technology. Companies who have the ability to harness these data and technology advances coupled with the mobilizers to drive cultural change will reap big benefits.

It’s great to see the “big data” conversation turn from theoretical to concrete. A few years ago, the focus was on the many possibilities of data. Now, the chatter has pivoted to which solutions work — and which don’t. In this piece, author Andris A. Zoltners goes on to list specific examples of how data technologies help salespeople, sales managers and sales leaders.

In practice, I’ve found that a sales data solution works best when executive strategy is tied to the daily decisions of sales teams. Executives typically set strategies around revenue, organic growth and customer retention to secure the top line. Sales teams are then tasked with ensuring that everything they do is aligned to those strategies.

However, it’s never that simple. Most sales reps, particularly in B2B, are responsible for hundreds of accounts and thousands of products. For sales reps to know each and every opportunity for cross-sell, upsell, retention and wallet-share across those customers and products is quite frankly impossible. Each misstep in decision making results in lost revenue for the company.

What we’ve observed is that a sales data solution works best when it’s informed by executive strategy, and then translates that strategic guidance into specific, actionable opportunities for sales reps. In short, it should provide sales reps with answers to the three most critical sales questions: What customers should I call on? What products should I sell? And, what price should I charge? Companies who execute well on that formula are seeing 20-30 percent increases in revenue that they were unable to find with their current approaches.

To Zoltner’s point: Sales data only matters if it helps you take action.

Read More: Does Your Mobile Sales App Drive Effectiveness, Or Just Efficiency?

Image courtesy of freedigital.net/vlado.

What is the Biggest Misconception About Big Data?

Data Informed recently asked Pete Eppele, and a handful of other data experts, one simple question: What is the biggest misconception about big data? Pete’s response:

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“From my perspective, the biggest misconception is that there’s more benefit and better ROI available from simple analytics on big data than from more sophisticated, predictive analytics on little(r) data. Managers often think that the next wave of benefit from data-driven decision making comes from amassing and analyzing a huge volume of data from a variety of different internal and external sources. They then start down the path of applying simple analytics to the data set to see what sales or marketing insights they can glean. Simple analytics, particularly when they are backward looking in nature and don’t have the ability to separate true signal from noise, can be confusing and, worse yet, misleading.

Regardless of how large and diverse a data set used in the analysis, simple analytics fail to provide a clear path forward for how to make better decisions in the future. A better approach is to start with the business problem in mind, seek out only the data you need to address it and apply sophisticated predictive and prescriptive analytics to the data. For example, a company’s transaction data that is collected in the course of doing business holds a wealth of signals that can inform everything from inventory decisions to pricing decisions to sales decisions when sophisticated analytics are applied to the data set. The output of those sophisticated analytics is not charts and reports that require interpretation. Rather, the output is forward-looking guidance to make a specific type of decision. This approach offers significantly more benefit at a much lower cost.”

Read the four additional answers in the full article.

Speak Your Mind: What is the Biggest Misconception About Big Data?