Is Your Sales Data Causing Inaccurate Forecasting?

By Sarah Hall

By definition, forecasting is inexact. It is a data-focused assessment of possibilities; and yes, there is a lot of guesswork involved. The ideal is to minimize the guesswork through the systems and strategies you implement – as well as the accuracy of the data you use.

If your sales data is causing inaccurate forecasting, then a review of your data input methodologies, sources, and management is necessary. Accurate data is the first stage to accurate forecasting – and there are a lot of benefits to forecasts that put you a step ahead of your competition.

Forecasting in Current Business

Forecasting, across all of a business’ operational and strategic aspects, is necessary. Guy Rudolph, Vodaphone Director for Business Planning, even says that it’s “absolutely fundamental.”

In 2016, KPMG, an auditing and finance company, published a global survey with more than 540 senior executives as respondents. All respondents agree on the importance of accurate forecasting. 67.5 percent look to forecasting as a way to identify growth opportunities. 54 percent say that it guides them in the implementation of performance milestones, such as sales targets and quotas. Likewise, 46 percent see forecasting as a means to improve organizational processes.

The problem lies in the accuracy of forecasting. According to the same group, unreliable forecasting can cost. Even as little as 13 percent off mark, share prices are said to drop by 6 percent. On the flip side, respondents have seen share prices increase by up to 46 percent with forecasting that’s within a 5 percent accuracy rate.

Bad Data = Inaccurate Forecasting

The same survey says that the executives observe a lack in the quality of their sales data. A 2013 study by business services company Experian has found that 91 percent of businesses suffer from data errors. Compounded with the disuse of available external resources (only 40 percent of the KPMG respondents use reputable external resources), such as economic reports and the like, you get businesses with forecasting based on bad data.

And, however way you spin this, it is bad for business.

In fact, the same Experian study has found bad data to be responsible for an average 12 percent loss in revenue. Another study, this time by DiscoverOrg, sees a loss of about 550 salesman hours or around $32,000 due to bad data.

Loss from bad data and inaccurate forecasting is not limited to money. Time and opportunity are also wasted.

Correcting Bad Data

The cost is high when it comes to bad data. As Brian Carroll of MECLABS puts it: “Garbage data in, garbage results out. Whether you do inbound or outbound marketing, the quality of your database and lists has a huge impact on your results.”

Once you observe compromised sales data, you need to take action.

What It Means When You Suffer From Bad Data

Inaccurate forecasting is just the tip of the iceberg. Forecasting is the basis of several key aspects in business operations. With bad data prevalent, the decisions you make for your business stand on shaky ground.

Incorrect business intelligence: Bad data skews the results of Go to the full article.

Source:: Business 2 Community

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