Why Analytics Could Save CRM

The bottom line is that today the analytics used in many small manufacturing companies starts and ends with Microsoft Excel spreadsheets. There are entire manufacturing operations run off Excel, fulfilling the roles of demand planner, manufacturing scheduling, and the continual maintenance of bills of materials, in addition to many other tasks.

Ironically in these same companies, customer contact isn’t captured and orders come in on paper, e-mails, faxes and even voice mails. While Microsoft Excel has become the manufacturing system of record for these companies and they have graphs along the walls of their factory floors showing reject rates, progress to production goals, quality levels and many other key performance indicators’ contribution to the business, there is no such visibility in marketing. In sales departments, the same thing — little if any visibility into the customer order rates, profits per product, or potential to segment out responses to customers.

There is no real automation of customer-facing processes in these smaller companies — and that’s the reason all the major ERP vendors including SAP, Oracle, Microsoft and IBM have small business initiatives.

Transitioning From Order Expeditor to Leader

I spent a part of the week with a heavy equipment manufacturer from the rustbelt, and their situation is very much like the one mentioned above. They build between 300 and 400 heavy platforms a year, many of them custom, and their factory floor runs on Microsoft Excel spreadsheets while their sales department gets leads and orders over phone, fax, snail-mail and e-mail. While the manufacturing operation has visibility into the key performance indicators (KPIs) that are essential for keeping orders moving, marketing and sales didn’t have nearly the visibility into customer orders and activity until the founder and CEO was given the job of order expeditor.

Now this didn’t happen overnight; the customers, however, found out that the delivery dates given when an order was placed were typically wrong, and that if they called or stopped by to see the founder and asked for their orders to be done faster — due to whatever reason — they could get that accomplished. Being a small company, this founder knew nearly every customer anyway. After a few months of this, production was behind over eight weeks for standard products. Costs were getting out of control and new orders weren’t coming in — in fact some new customers canceled due to lack of delivery dates being met.

Lessons Learned

Realizing that these expedites were costing much more than the incremental revenue didn’t take long. Here’s what this company did to get back on track of their quotes, orders and customer expectations:

• Instead of trying to hit an exact delivery date, they aimed for a range. At one point the company was missing 9 out of every 10 delivery dates, and losing customers in the process. Instead of trying to perfect a delivery date on quotes and orders the use of a date range helped tremendously.
• Expediting orders now have a 65-percent price premium. The founder and his management team did the financial analysis to see what expediting really cost, and decided to offer it as a service, at a substantial bump in price. At first customers balked but the company held to the policy and there is only one true expedite request per 75 orders today — in other words only about five a year.
• Customers placed orders with a rep and then called the CEO to get a better deal. Once the company started measuring order volume by channel and started looking at price concessions by customer, they realized just how many times customers would try to get a better price from another, disconnected order channel.
• High maintenance accounts were the least profitable. Those customers who wanted the most amount of support were ordering the least and often trying to use the platforms for a purpose they hadn’t been designed for. Only after analyzing customer data did this come out; the manufacturer proposed a modified platform at a higher price and the customer is evaluating it now.
• Pipeline analysis showed their best customers doing extensive quote shopping to drive down competitor’s prices. This was an interesting take-away from applying analytics to their quote-to-order close rates by customer. Their largest customers were also using them to get quotes to drive down the prices of competitors — so the manufacturer did more qualifying on each sale from that point on.
• The best leads were coming from channel partners also carrying competitive products. This was a pleasant surprise for the company; they had found that their indirect channels were the best source of new leads due to the strong Warranty Repair business this manufacturer had. Resellers looked at that side of the business as their primary revenue stream with the manufacturer. Conversely, trade shows, while important for visibility, were very costly on a per-lead basis.

Bottom line: If a small manufacturer can see so much value to their business just from a slight increase in the number of analytics used to drive customer strategies, think of what this means for the companies with armies of analysts. CRM’s redemption may be in the analytics it delivers — as this small manufacturer illustrates.