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Your CRM Holds a Treasure Trove of Data

By Larry Lapide

This article was originally published in the Journal of Business Forecasting, Summer 2018. It is republished here with permission from the author.

EXECUTIVE SUMMARY

In my last column, I discussed the importance of sales forecasting at industrial product companies. Since sales organizations are the most important organization in creating and shaping customer demand, I advised managers in these companies to get more involved with sales managers during the demand forecasting and planning process. I briefly mentioned that integrating information from CRM systems would provide useful insight for improving accuracy as well as sales productivity. In this column I discuss how three components of CRM systems might improve these processes for both industrial and consumer product companies.


My last Journal of Business Forecasting (JBF) column (Spring 2018) was titled “Sales Organizations Shape Industrial Product Demand”. Its premise is that, unlike consumer-product companies where forecasts made by Sales are often treated with skepticism, in industrial-product companies, forecasts developed in conjunction with Sales are critical.

In this regard, I advised that: “sales forecast models ought to incorporate the quantitative impacts to sales of various factors about sales force activities, as well as the status of the future sales pipeline of prospective customers. Generally, historical sales data (drawn from transactional order management systems) is critical in consumer products forecasting. However, in industrial-product forecasting, future customer information (drawn from Customer Relationship Management (CRM) systems, such as Salesforce.com) is critical. ” However, while not stating so in the column, I also believe that CRM systems can be extremely useful in consumer product companies as well. Thus, this column discusses the ways in which CRM systems might be used to develop more accurate demand plans and forecasts.

WHAT IS A CRM SYSTEM?

According to Wikipedia, “customer relationship management (CRM) is an approach to manage a company’s interaction with current and potential customers. It uses data analysis about customers’ history with a company to improve business relationships with customers, specifically focusing on customer retention and ultimately driving sales growth.”

Operationally, a CRM system is made up of 3 major components: 1) Salesforce Automation, 2) Marketing Automation, and 3) Service Automation, as follows (also from Wikipedia):

  • “Salesforce Automation works with all stages in the sales cycle, from initially entering contact information to converting a prospective client into an actual client. It implements sales promotion analysis, automates the tracking of a client’s account history for repeated sales or future sales and coordinates sales, marketing, call centers, and retail outlets. It prevents duplicate efforts between a salesperson and a customer and also automatically tracks all contacts and follow-ups between both parties.”
  • “Marketing Automation focuses on easing the overall marketing process to make it more effective and efficient. CRM tools with marketing automation capabilities can automate repeated tasks, for example, sending out automated marketing emails at certain times to customers, or posting marketing information on social media. The goal with Marketing Automation is to turn a sales lead into a full customer. CRM systems today also work on customer engagement through social media.”
  • “Service Automation is the part of the CRM system that focuses on direct customer service technology. Through service automation, customers are supported through multiple channels such as phone, email, knowledge bases, ticketing portals, FAQs, and more. ”

The first CRM component, Sales Automation, is what I was referring to in the last column. I discussed its use for demand forecasting and planning in industrial products companies where sales organizations are critical for the creating and shaping of product demand. All three components of a CRM system might be useful in consumer product companies as well as in industrial product companies.

CRM’S USEFULNESS BY PRODUCT MARKET

In order to understand how each of the CRM components might support forecasting and planning in various industries, we assume that companies potentially sell into four distinct product markets: 1) industrial durables, 2) industrial aftermarket & consumables, 3) consumer durables, or 4) consumer consumables.

The industrial durables markets involve selling products to companies that use them to run their businesses over periods of time. That is, until the products are replaced, decommissioned, or phased out. A CRM system’s Salesforce Automation component is a major input for forecasting and planning demand. It contains useful information about prospective sales by tracking each sales opportunity along a ‘sales cycle. ’ The cycle consists of opportunity phases starting with a prospective customer sale until it does or does not convert into an actual sale. Useful information gleaned from this system component includes the projected size of the opportunity, and its probability of converting to the next phase in the cycle. In addition, as described in my last column, it can be used to estimate sales productivity in terms of the sales rep’s ‘learning curve, ’ and thus might evolve into a decision support system for sales management.

The industrial aftermarket & consumables markets involve selling to an ‘installed-base’ of customers that are actively using industrial-durable products to run their businesses. These products, for example, might be bundled into service contracts that include remedial and preventative maintenance services on them -- such as on construction, mining, aerospace, manufacturing, and computer equipment. Aftermarket sales might also involve the selling of spare parts, product accessories, and product-related consumables (e. g., computer printer paper and ink cartridges).

In my column, “Installed-Based Forecasting” (JBF Spring 2012), I discussed a “Pot-of-Water” forecasting model for projecting an installed base of customers actively operating industrial products. My illustrative example was taken from the computer service contract model we used in the field service division of a computer manufacturer at which I worked. The forecasting modeling approach starts with a current installed base, and then over a future forecast horizon adds and/or subtracts forecasts of: new contracts and installations, upgrades and add-ons, replacements and renewals, and decommissions and cancellations. The forecasts are used to project various aftermarket goods and services that might be demanded by customers over the horizon.

A CRM system’s Service Automation component is the major input that might be used when forecasting and planning demand for these products. The system would contain transactional and planning information regarding installed base customers. From it, forecasters and planners can then estimate future service interactions with these customers, as well as the purchases of aftermarket & consumable products.

Regarding the latter products, in my JBF column, “Lifecycle Forecasting” (Spring 2018), I discussed an approach to forecasting part sales in terms of the lifecycle of a durable product manufactured with component parts. Basically, there are four phases of the lifecycle of a durable product starting from its initial sales and installations to its end-of-life. These lifecycle phases are: 1) Introduction and Active Selling, 2) Leftover Selling, 3) Post-Sales Support, and 4) End-of Life Support. I discussed the various time-series and cause-effect forecasting approaches that might be used to forecast part sales during each phase. The Salesforce and Service Automation components of CRM can provide useful information for forecasting these sales.

The consumer-durables markets involve selling durable products to end-consumers for use in their home such as white goods (e. g. washers, dryers, and refrigerators) and electrical products (e. g. home computers, phones, and vacuum cleaners). The CRM system’s Marketing Automation component is often a major input that might be used when forecasting and planning demand for these products. The system would contain useful information about all the promotional activities (e. g. trade programs, new product launches and pricing actions) done by the marketing organization to create and shape demand. Information about prior promotions and their sales performance, as well as plans for future activities, would most likely be found in this component. Demand forecasters and planners could use this information to do post-mortems on promotions, as well as estimate promotional impacts on future customer demand.

The consumer-consumables markets involve selling consumable products to end-consumers for consumption in their homes such as health and beauty aids, groceries, paper towels, and baby diapers. Both a CRM system’s Marketing and Service Automation components might be useful when forecasting and planning demand for these types of products. The Marketing Automation component would contain useful information about all the promotional activities of the marketing organization. Similar to the consumer-durables markets, demand forecasters and planners might use this information to gauge prior promotional effectiveness, as well as estimate the impact on future customer demand.

Meanwhile, a CRM system’s Service Automation component would also be useful to forecasting and planning. It would contain information on customer service calls from customers consuming existing and new products. Information about product satisfaction (e. g. about product use and product quality issues), and sales channel effectiveness for products can support product innovations, as well as generally support product forecasting and planning processes.

LOOK INTO YOUR CRM SYSTEMS FOR VALUABLE INSIGHT

As discussed above, all three components of a CRM system might provide information for improving the accuracy of forecasts and plans for both consumer and industrial product companies. According to Gartner, CRM became the largest software market in 2017 (at $39.5 billion) and is expected to be the fastest growing one in 2018. CRM as a business function has (obviously) been around throughout the history of business, and some CRM software applications existed prior to the newer cloud-based ones. However, in 1999, Salesforce.com pioneered CRM software in the cloud, and turbocharged the growth and pervasiveness that we now see in the use of CRM software systems.

Despite this phenomenal growth period in CRM-related information and data, I suspect most forecasting and planning managers have spent much of the past two decades investigating Big-Data’s downstream demand signals (e. g. from social media). But has this taken away too much of their time that could have been better spent investigating the information available in the CRM systems, in their companies? If they have not done so yet, they should check them out. They may find a treasure trove of useful demand signals in their own backyard! Using these might add significant accuracy to plans and forecasts, as well as potentially lead to the development of decision support systems for their marketing, sales, and customer service management organizations. These systems might lead to productivity improvements for them, as well.


ABOUT LARRY LAPIDE | Dr. Lapide is a lecturer at the University of Massachusetts, Boston, and an MIT Research Affiliate. He has extensive experience in industry, consulting, business research, and academia as well as a broad range of forecasting, planning, and supply chain experiences. He was an industry forecaster for many years, led supply chain consulting projects for clients across a variety of industries, and has researched supply chain and forecasting software as an analyst. He is the recipient of IBF’s inaugural Lifetime Achievement in Business Forecasting and Planning Award. He also serves on the IBF Board of Advisor. Dr. Lapide welcomes comments on his columns at llapide@mit.edu. (This ongoing column in the Journal is intended to give a brief view on a topic of potential interest to practitioners of business forecasting and planning. Suggestions on topics that you would like to see covered should be sent via email to llapide@mit.edu)


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