Having helped over a dozen highly successful companies with their enterprise business intelligence (BI) and analytics strategies, I can attest that many companies still approach performance management in old-fashioned, manually intensive ways. They spend too much time figuring out what happened and not nearly enough time determining courses of action that have high chances of success.

The companies I've worked with are prominent in various industries—manufacturing, distribution, financial servies, transportation and logistics, retail, and energy. Regardless of industry, business performance management (BPM) is mainly about understanding the dynamics around customers, products and/or services, channels, and the business units responsible for achieving financial and operational results. In addition, performance is generally measured in comparison with prior-period results (directional trend) and against budgets and various operating plans or targets. Given this common framework, there are many key recurring performance management questions:

• How are we doing compared to prior periods (e.g., year, month, week, day of week) and budgets (e.g., annual budget, quarterly updated budget, get-well plan)?

• How well are we executing our operatonal plans and meeting targets (e.g., market share growth, channel penetration targets, planned product promotion, service cross-selling and upselling targets, and many others)?

• For which customers, products and/or services, and channels are revenues more than last year and for which are they less?

• For which customers, products and/or services, and channels are revenues ahead of target and for which are they behind?

• How are business units performing compared to last year and compared to plans?

Overcoming Analytical Complexity

Managers need timely and accurate answers to these key questions in order to manage performance efficiently and effectively. That said, all but the simplest companies have many customers and products and/or services, many operate in more than one channel and/or geographic area, and all manage performance via some combination of business units operating according to some sort of business plan. This creates analytical complexity when it comes to getting answers to our basic performance managements questions—and it's really multidimensional analysis you require. Here are a few examples of analytical complexity in different industries:

• Financial services companies often have millions of customers, hundreds of locations, dozens of services with various options, and three or more channels.

• Consumer packaged goods manufacturers often have hundreds or thousands of products sold to many different types of customers at thousands of locations, via hundreds of retailers (customers) in various channels.

• Grocery chains operate dozens to thousands of locations that stock upward of 40,000 items sold to many different types of consumers in a wide variety of combinations, with widely varying margins.

To substantially increase management and business analyst productivity and effectiveness around performance, BI in the form of dashboards, scorecards, and multidimensional slice-and-dice analyses is the perfect tool for the job. Yet, for some reason, companies spend lots of time and money each month on business analysts (or equivalent titles) who wrangle a combination of static reports, custom data sets, and data from spreadsheets, emails, and other sources, and then amalgamate all that into a static presentation deck and send it up the chain for review.

Summary: Fully Leveraged BI

In contrast, a well-designed custom performance management system leveraging BI can put executives, managers, and analysts in a position where just a few clicks of the mouse can tell them which combinations of customer and product or service and channel and business unit are having the most favorable and unfavorable impacts on business performance. Imagine being able to know this in minutes instead of days so that BI can be further leveraged to look ahead, model scenarios and economic impacts, evaluate options, leverage decision-support techniques, and decide on courses of action in days instead of weeks or months.

In this day and age, a BI-enabled performance management system should be the norm, not the exception. For more on this topic, please see chapter 6 in my recently published book, Business Intelligence Strategy and Big Data Analytics (2016, Morgan Kaufmann).

Steve Williams is president of DecisionPath Consulting. He has developed enterprise business intelligence and analytics strategies, business cases, and road maps for companies with annual revenues ranging from $500 million to $20 billion. Steve has also been a judge for TDWI Best Practices in Business Intelligence and Data Warehousing competition, and he has written articles for Strategic Finance magazine and the Business Intelligence Journal, among others.

TDWI Onsite Education: Let TDWI Onsite Education partner with you on your analytics journey. TDWI Onsite helps you develop the skills to build the right foundation with the essentials that are fundamental to BI success. We bring the training directly to you—our instructors travel to your location and train your team. Explore the listing of TDWI Onsite courses and start building your foundation today.