Let’s talk about CRM Systems

This is an excerpt of the original article. It was written for the September-October 2018 edition of Supply Chain Management Review. The full article is available to current subscribers.

September-October 2018

If it’s September, it must be time for Gartner’sTop 25 supply chains, the lead article in this issue of Supply Chain Management Review. As I was reading this year’s contribution from Gartner, I was struck by the number of the Top 25 that have launched NextGen Supply Chain initiatives, using Big Data, artificial intelligence (AI), robotic process automation (RPA), machine learning and the like to digitize their supply chains. It made me wonder: Is the rest of the pack falling behind or are they ready to follow the leaders?

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My May/June 2018 Insights column was titled “Sales organizations shape industrial product demand.” It pointed out that at consumer-product companies, forecasts and plans made by sales organizations are often treated with skepticism. At industrial-product companies, in contrast, understanding sales activities is critical to developing them.

My advice was that sales forecasting models ought to incorporate the quantitative impacts to sales of various factors about sales force activities, as well as the status of future sales opportunities (i.e., the sales pipeline) of prospective
customers. I noted that in general, historical sales data drawn from transactional order management systems is critical in consumer products demand forecasting.

Meanwhile, when it comes to forecasting industrial products, future prospective customer information drawn from customer relationship management (CRM) systems (such as Salesforce.com) is most critical. While I didn’t assert this in the column, I also believe that CRM systems can be extremely useful in consumer-product companies as well.

This column discusses the ways in which a CRM system might be used to develop more accurate plans and forecasts.

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