Data-Driven Decisions

March 1, 2010
Creative use of data capture and statistical analysis can give your company the business intelligence it needs to make better decisions.

The new world-wide language for the 21st century is not English or Chinese, although those two languages account for 65 percent of native and second-languages among Internet users, according to Internet World Stats (www.internetworldstats.com). It's not Esperanto, the first universal language constructed in 1887 with only approximately 2 million native and second-language speakers from 115 countries. The new universal language for the 21st century is statistics. The pervasive use of statistics by education, science, business, technology and governments today ensures this. One of the many advantages to statistics and analytics is the ability to measure tangibles and intangibles and provide ways to interpret the meaning and value of data.

The Right Tools for Now

Business (data) analytics software and services employ complex algorithms and statistical methods to understand relationships found in data sets. These tools are being used by financial departments for planning, budgeting, forecasting, and trending; by marketing for data mining and predictive measures; and by purchasing and supply chain teams using all of these types of analytics and more. These programs aggregate data sometimes from additional sources, then use statistics and analytics to identify problems, solutions, recommendations and optimizations. Baseball is a great example of where statistics has always played a role, not just in calculating players' or teams' records but also in the “measuring” of a player's potential. Several team managers are well-known for using player statistics in their assessment and management to turn talent into winning teams. To answer questions about preventing player injuries, predicting ticket sales and measuring performance, baseball executives have taken steps to digitize many aspects of the games to grow their statistical data and turn it into actionable information to help the game and fan enjoyment. Many of the same approaches to using data to analyze performance can be applied by electrical distributors.

Business intelligence has been around since the 1980s, but it hasn't always been successful for several reasons. Several key components were missing: access to good quality data and low cost, faster computers, systems and technology. Businesses had data but without a corporate data governance policy, the data quality was poor and could not reliably be used. Few companies adhered to data standards or required business rules at the data gathering points. While some companies had data warehouses, few had a centralized system. Instead, companies built data warehouse silos based on departments so it was common to have customer records split between sales and accounting. Frequently, these systems couldn't “talk to each other” because they had different software vendors, data formats and business rules. With the new technology in computer systems today, more companies are consolidating data into centralized systems and taking better advantage of these data-driven capabilities to make better decisions.

Forecasting & Planning

While analysis and analytics are sometimes used interchangeably, these words have very different meanings. Analysis is review and comparison of materials or data. Analytics is the “science of analysis,” which studies the way a business arrives at decisions by using statistical and quantitative methods to identify patterns and form predictions. Other uses for business or data analytics include forecasting events, customer patterns and so forth to determine what could be different and better.

Business analytics software and services provide capabilities in several areas including business intelligence, financial performance and customer relationship management (CRM). These programs aggregate data from multiple sources, then use statistics and analytics to identify problems, solutions, recommendations and optimizations. We see use of these tools growing among electrical distributors.

Samson Electrical Supply, South Plainfield, N.J., is among the distributors that have embraced data analytics to improve efficiencies and overall profitability. Michael Cohen, vice-president, says after reviewing its operations, the company added a customized bolt-on software program for inventory management and forecasting to its ERP system. Automated monthly reports provide dynamic visibility of current inventory levels, turns and fill-rates while reducing the total inventory dollar value, with fewer supplier returns.

“Planning for the future is one of the best ways to grow the business and provide dependable services to our customers,” Cohen says. They also measure and react to several important productivity metrics to ensure quality operations and are planning routing optimization and a vehicle tracking program in the near future.

Business Analytics & Business Intelligence: The Distinction

Although there is overlap between business analytics and business intelligence, the former focuses on developing new insights about what might happen in the future, so it provides information that is predictive. It addresses questions such as, “If these sales trends continue, then how much stock will we need?” and, “What will happen next and how will it affect my business?” The key difference is the use of statistics and complex math to understand relationships and patterns in the data and quickly provide actionable data for decision-making.

Business intelligence quantifies the current status, using a consistent set of metrics to measure both current and past performance and guide business planning by queries, reporting, price cubes and pivots, slicing and dicing the data and generating data alerts. All of these functions answer questions about what happened — how many, how often, where, and what actions need to be taken based on this current data? Several of the well-known distributor ERP programs in the electrical industry include business intelligence modules with custom queries, on-line data processing (OLAP), and some include for-purchase modules with business analytics and pricing optimization.

Measuring the Unknowns

When carefully applied, statistics and analytics can give you ways to measure or estimate the value of intangibles and unknowns.

“It's always been a challenge to find ways to measure sales force productivity outside of sales objectives,” says Steve Barker, vice-president of Mid-Coast Electric Supply Inc., Victoria, Texas. “Sales figures are not enough because it's an indirect method to measure productivity. For instance, in a recessionary economy like the current status, it would be inaccurate to attribute reduced sales to inactivity. So how do you know when someone needs assistance or more training to improve their numbers or should just be making more calls per day? It doesn't work to clock the time to travel to and from and time on site for the customer's visit and average those because there are too many variance factors (changes in route due to traffic, waiting for start of customer meeting, more time on site to help with new problems).”

Mid-Coast discovered another problem when they talked to their customers about value and satisfaction. Several customers did not recall even recent visits or the services performed. The company needed a time-sensitive way to capture the essential details about the purpose of the visit, people involved, dates and times, warranties serviced and other information about service provided during the visit.

Mid-Coast used business intelligence tools provided in their SX Enterprise system, plus purchased data management utilities, to capture data from different sources to solve both problems and open up possibilities for other applications. They had event-driven data and measures such as sales per customer. To this they added global positioning system (GPS) data to measure location and session time, and they now require sales reps to file a log report for each customer visit describing who they saw or tried to see on that visit and what services were provided. The reps use their smart phones or wireless notebooks to complete the log reports from their cars immediately after the customer visit. GPS data available through local telecommunication providers support these reports. “It's a very fluid solution providing great opportunities to measure other areas for effective use of resources and productivity,” says Barker.

Using Data to Improve Service & Profitability

United Electric Supply, Inc., New Castle, Del., takes full advantage of its Eclipse ERP system's reporting and business intelligence functions with a new project in which they collect data on the profitability of each activity involved in taking and shipping a customer order. According to Rich Chadwick, director of training, they are reviewing the cost to serve per customer, per delivery, plus many other factors. During this project, they will be checking with the department teams for their input on labor and cost saving measures, Chadwick says.

Since this is a holistic view, information will be collected and analyzed from all areas of the company including warehouse and finance. Once all of this information is consolidated, it will be converted into corporate performance objectives. It's possible that some customers will be below average. If this occurs, steps will be taken to assist the customer in utilizing mutual efficiencies and growing their value. All these activities are possible using the business intelligence and analytic tools in their ERP system.

Identifying Solutions

Creating data decision-based tools for enterprise systems, business intelligence and analysis requires a rich source of data. For some companies this may mean finding external data sources. Using new data sources to supplement ERP transactions or catalog data and then using business analytic tools and statistics to analyze the combined data can reap benefits in measuring customer or employee interests, performance, behavior and usage because the business must react fast to problems to stay competitive.

Jim Hoffman, vice-president at Schaedler Yesco Distribution Inc., Harrisburg, Pa., suggests there are few limits to the data that can provide insights. “We currently use 65 key operation measures from our Eclipse ERP system to measure our business and employees, monitor operations and provide feedback to our management team,” he says. “Our delivery drivers help in the collection of data by using ‘electronic manifest devices’ to record the times and their stops. Then at the delivery point, the drivers add the mileage. This information helps us measure our true costs for fuel, vehicles, maintenance and labor, in addition to having a detailed historical record about the customers' receipt of purchased materials.”

Creative analytical thinking helped Schaedler Yesco add new, readily available sources of data. Says Joyce Hess, corporate branch manager, “We've recently added inbound and outbound telephone records, which we've integrated with some of our ERP reports to provide the missing time elements for event performance measurements.”

Now is the best and right time for electrical distributors to be using technology's greatest gifts — business intelligence, analytics and statistics — to collect, aggregate, analyze, measure, compare data and provide predictions, decisions, and actions to grow your business.

Beth Badrakhan is a data consultant with 35 years of experience in the electrical industry. She has worked with U.S. and Canadian manufacturers, distributors and contractors on data content, quality, life-cycle, integration and standards. She was formerly employed by IDEA as IDW Data Manager for nine years. She also has worked for two electrical distributors and the service provider Trade Service Corp. for seventeen years in data operations and administration. She can be reached at [email protected].