Forget Spreadsheets; Business Intelligence Can Give You a Better Picture of Your Customer


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A niche pharmaceutical company located in New Jersey hadn’t thought too much about basic reports, let alone business intelligence, when its sales rocketed to $100 million after just three years in existence. At that point, finance decided to stop using Quickbooks and migrate its general ledger and invoicing to an SAP module in its parent company.

I was consulting for the company, and around the same time, its IT group found a Danish-designed system called Navision and decided to apply it to the enterprise. Of course, this was no trivial task and took the better part of two more years to implement. The trouble was, no one had time to think about back-end reports while all of this was going on.

In the meantime, hundreds of Excel spreadsheets resided on hard drives or at selected email addresses. The national sales manager had 26 separate monthly Excel outputs. Operations trumped that easily, with 80 spreadsheets showing monthly parts usage. Customer service didn’t have any reports at all, apart from hand-me-downs from other groups, while marketing claimed that none of the information being captured was even pertinent.

Even at a basic level, the company had no way of telling how much a customer was actually costing to support. Inventory costs were probably captured, but no one quite knew how to consolidate the information. Distribution costs were so cryptic that it was simply a matter of “best guessing,” based on the customer’s geographic position relative to the regional service center.

Enter Business Objects, a leading-edge business intelligence software vendor. A senior analyst with the pharmaceutical company who was investigating BI contacted Business Objects and described the problem. When upper management at the pharmaceutical company refused point-blank to spend any money on a proof of concept, the situation tweaked the interest of Matt Skilton, an inside sales manager at Business Objects. He decided to take a chance on building a proof of concept at no charge.

Five KPIs

Three months and more than 300 working hours later, Business Objects had built a POC around five key performance indicators: operational cost, inventory utilization, days of sales outstanding, expense limitation and overall corporate vitality. Using a variety of executive dashboards, alerts, drilldowns and scorecards, Skilton and his team astounded the executive team by demonstrating areas of intelligence that had never been mined before. The CFO quickly assumed the role of project sponsor and soon had her team scribbling down report requirements that no one had even thought possible a few days earlier.

Building a data warehouse that consolidated, classified and verified information from several sources was the first step in a crucial process that included the formalization of business rules and reporting needs before the business intelligence software layer could be added. Think of the BI tool as the umbrella that covers the enterprise. Depending upon the size of the various databases, the process would take several months, involve multiple resources, and cost upwards of $250,000.

However, the return on investment is undisputed. Early intervention with customers decreases days of sales outstanding, identifies competitive penetration and optimizes the supply chain reaction. Overnight adjustments mean that more customers are ordering on time, rather than on an exceptional basis. Distribution becomes more efficient and product utility is optimized. The bottom line is that a company’s initial investment is typically recouped within the first year.

Making sense of millions of bits of captured information in a SQL database was one thing, but getting the pharmaceutical firm to capture more insightful customer intelligence demanded a redesign of the front-end CRM interface. And while knowing how the customer was using the product and being able to forecast demand was beneficial, understanding key customer events and translating those events into predictive analysis was something the company could build on for real results.

Working with the heads of sales, customer service and marketing, we were able to define critical customer “moments of truth” that were either being captured in a customer service representative’s free-form notes or being filed in a sales rep’s site visit log. Defining discrete fields within the CRM interface meant that, in the case of this company, it was able to capture changes in key medical personnel, new uses of the drug, billing disputes, pricing complaints, publication of new studies and other insights. Using sales and drug usage data, the business intelligence application would then be able to directly associate a key event with trend analysis.

There are two benefits to making a connection between front-end customer transactions and back-end supply, demand and revenue information using business intelligence-based algorithms. It can help an organization anticipate customers’ needs. Rather than discovering that customer behavior and needs have changed months after the fact, the combination of trend analysis, CRM events and alerts can flag a customer before any real damage is done. Second, you can glean powerful insights from forecasting, scheduling and predictive analysis that form the basis of any BI toolset.

Seeing is believing when it comes to business intelligence. Once your executives start understanding the power of the data that you are collecting within your enterprise, it will be akin to a snowball rolling down a hill, gathering momentum and bulk as it travels.

There is no denying that it’s a lot of work to capture disparate and redundant data across enterprise systems, spreadsheets, databases and rogue applications. Data integration and warehousing are not trivial, but once you’ve tackled those tasks, that resulting single version of the truth can springboard your business into the 21st century.

Michael Cusack
Independent Consultant
Michael Cusack is an independent consultant and author of Online Customer Care€"Strategies for Call Center Excellence (ASQ Press, 1998). He was a human-computer interface designer with the AT&T Artificial Intelligence Group before joining Bell Laboratories as a consultant. His primary concern is the appropriate use of technology for customer service.


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