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You Can't Make Good Decisions With Bad Data

December 14, 2015 | By Steve Silver

  • The computing adage “garbage in, garbage out” is as applicable today as it has always been
  • Ensure that sales reps are aware of the visible and beneficial nature of the data they are asked to give
  • Sales operations must take ownership of data management by appointing a data steward

Despite the rise of big data and the ever-increasing power of analytics tools, there is an adage from the early days of computing that still applies today – “garbage in, garbage out (GIGO).”

GIGOThe truth of GIGO was reinforced recently when we were working with a client to analyze sales win/loss data. The analysis started with opportunity data captured in their sales force automation (SFA) platform. In order to close out an opportunity, the sales rep must choose a loss reason from a drop-down list with 10 possible choices. The very first choice on the list is “price.” When we ran our first analysis, we discovered that price was chosen as the reason for over 90 percent of lost deals.

This company delivers a solution that is unusual, and we know from speaking with their sales reps, marketers and customers that price is a consideration for buyers, but it is rarely the primary driver. Through further investigation, we discovered that there were two reasons for the overwhelming selection of price as the loss cause. First, the choice is top of the menu – easiest to choose and the path of least resistance for the sales rep to close out the opportunity. Second, and perhaps more important, no one – not sales leaders, not marketing and not product – was looking at the data, conducting any analysis or taking any action on it. For the sales rep, the win/loss data point quickly became just a “check the box” exercise – one more administrative activity that added no value.

What lessons can we learn from this experience?

  • Make sure any data you ask to receive from sales reps will be visibly used and that the benefits of providing the data are clear. It’s all too easy to add many different fields to an SFA platform in an attempt to meet multiple stakeholder requests. But sales operations must ruthlessly assess and challenge these requests. Who will be using the data? For what purpose? What’s the value to the sales rep? How can we make it easy for the rep to enter accurate data?
  • Sales operations must step up and claim ownership of data management by making a member of the team responsible for data control. The data steward often works with marketing operations, and is responsible for defining and enforcing data rules, assessing and reporting on data health and communicating relevant data information (e.g. new rules, changes in policy) to the sales organization.

For that client we worked with, failing to validate the quality of win/loss data could have led to incorrect conclusions about product pricing, potentially causing unnecessary price reductions and margin erosion. The lesson of GIGO is that inaccurate, even nonsensical data can produce undesired or inaccurate analysis, resulting in bad business decisions. 

We discussed GIGO - and so much more - at the SiriusDecisions 2016 Summit. Join us for four full days of data-driven best practices research, unveiling of new innovations across the b-to-b space and networking with an elite community of sales, marketing and product leaders. Learn more and register for this year's summit today.

Steve Silver

Steve Silver is a Senior Research Director of Sales Operations Strategies at SiriusDecisions. Steve brings with him more than 20 years of executive-level experience spanning sales operations, sales and product marketing. Follow Steve on Twitter @jstevensilver.

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