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BI Briefs:
Are You Driving a Dashboard to Disaster?

online columnist Rick Sherman     Column published in DMReview.com
July 25, 2003
  By Rick Sherman

If your company is like most, it's trying to increase profits by cutting costs and growing more revenue. As an IT manager, your role in achieving this goal starts with a crystal-clear picture of your company's business activities, including goal-setting, planning, budgeting and performance monitoring. You need, in a sense, to view the enterprise with night-vision goggles to truly see into all the cracks and crevices where crucial data lurks.

You're probably thinking that you need a dashboard, right? Wrong. Well, sort of. You might need a dashboard. But it's not a silver bullet. And if you don't make it part of an overall comprehensive architecture, you're squandering your budget. Plan out your company's enterprise performance management (EPM) scheme first, then worry about whether or not you need a dashboard.

Use EPM to View Your Enterprise with Night-Vision Goggles

We'll start with a definition. Enterprise performance management describes the methods and tools used to monitor and manage enterprise performance. You may have also heard it called corporate performance management (CPM) or business performance management (BPM). Sometimes the term business analytics is used to describe EPM, but analytics can also be understood as a component of EPM. For the purposes of this article, we'll stick with EPM.

EPM helps companies gather enterprise resource planning (ERP) and enterprise application systems data, including customer relationship management (CRM), supply chain management (SCM) and financial budgeting and planning. With this data companies then calculate, monitor and react to key performance indicators.

Dashboard to Disaster

There's no shortage of vendors who say that their analytic packages provide EPM. But dig down into their marketing materials and you'll see that they're often just dressing up their usual offerings, such as dashboards, using new buzzwords. You can't put a racing saddle on a Shetland pony and expect to win the Preakness.

Many of the IT people I talk to tell me they're implementing dashboards, expecting them to expand the use of their data warehouse/data mart environments and unleash the terabytes of data that they have in been collecting over the last few years. That's my clue to ask what business initiative or pain they are targeting with these projects. I usually get a blank stare. They tell me they have all the data the business will ever need and the one key that has been lacking is the dashboard. Sounds more like a dashboard to disaster.

The IT-to-Business Chasm

Then I go talk to the business people and get a totally different viewpoint of what is going on and what their needs are. CFOs are concerned about transparency, corporate governance and Sarbanes-Oxley. They want to monitor key performance indicators that let them control costs and examine profit margins. The senior vice presidents of sales and marketing are looking to examine key performance indicators related to product performance and get details of specific issues and actions. Right now, a lot of business managers have staff calculating data on spreadsheets. Not only does this take longer, but the accuracy of the numbers comes into question. Business users want the results that only EPM can deliver. Just don't expect them to ask for it by name.

Here's the chasm: business users want EPM. IT managers think they're delivering EPM with their dashboards, but in reality they're not. It's a perfect recipe for disappointed business users and frustrated IT departments.

Four Essential Components of an EPM Architecture

Let's review what we discussed previously in BI Briefs: Mars, Venus and a Successful Business Intelligence Architecture. We have four components to a BI/DW architecture: information, data, technology and product. IT people and technical users focus on products. Business people focus on the information they need to do their jobs.

It's important to note the difference between information and data. Information is the business interpretation of the data - business rules, processes, transformations, metrics, etc. A business order is an example of data. A key performance indicator is information.

Now think about the four components of BI architecture in terms of EPM. Dashboards are just products that fit within the overall EPM architecture. EPM (or analytics) is the overall solution or architecture that the business needs. What does this architecture encompass?

Information: This is what drives the success of the EPM solution. What information do the business users need? You need to determine not just the data but what algorithms, measurements and transformations need to be applied to the data to create useful information such as key performance indicators.

Data: At first glance, it may appear that all the data the business needs is already in your data warehouse. IT folks may think that business users could find it if only they would just look in the right place. Remember, it is IT's responsibility to find the data for the business and enable its transformation into useful information. Pay close attention to the details, such as what is used in the spreadsheets that the business creates to calculate key performance indicators. There is often some other data created or guessed at to complete the calculations that the business could not find in the existing DW/BI environment.

Technology: Other than an analytics application layer, you probably already have most of the technology components you need to deploy an EPM solution. The analytics application layer is what transforms the data from your data marts into business information. This is the step that helps the business users the most, but it's also the step most often misunderstood by IT. From IT's standpoint, many transformations have already taken place using ETL tools - the data has moved from source systems to data warehouses to data marts. But all these transformations merely deal with IT systems' specific issues regarding data format and quality, and consolidation. These are all necessary steps, but the data is still not ready for the business users. The final hurdle is to transform the data into business information via analytics.

Products: Sure, you need them. But you need to understand what you need before you evaluate and buy. Look beyond the great graphical dashboard demo and the product sheet touting the ability to extract data from every source system known to mankind. Put the information and technology components under a microscope. You are buying an analytics application layer that transforms data into information. Do the key performance indicators or metrics offered meet your business needs? Does the data model provide the depth and breadth of data that the business needs?

How Do You Get Started?

Ask yourself two questions before you get started:

  1. How much customization will be necessary? Set realistic expectations with respect to the effort to implement and the business scope.
  2. Are you going to create another information silo with numbers that don't match your existing data marts and BI applications? Examine honestly if you are going for a quick-hit win at the expense of the future. But even more importantly, you will create short-term deployment issues if the numbers are different from your new EPM system and your existing data warehouse. You can and should achieve short-term success but you need to do it within a business architecture that is sustainable.

For some thoughts on organizing your approach to the EPM project read "From Peanuts to Profits - Delivering Long-Term ROI in Business Intelligence."

I'll continue to discuss EPM systems in future articles. Drop me a note if you have any specific requests or questions you'd like me to address.


For more information on related topics visit the following related portals...
Business Intelligence (BI).

Rick Sherman has over 20 years of business intelligence and data warehousing experience, having worked on more than 50 implementations as a director/practice leader at a Big Five firm and while managing his own firm. He is the founder of Athena IT Solutions, a Boston-based consulting firm that provides data warehouse and business intelligence consulting, training and vendor services. Sherman is a published author of over 50 articles, an industry speaker, a DM Review World Class Solution Awards judge, a data management expert at searchdatamanagement.com, and has been quoted in CFO and Business Week. Sherman can be found blogging on performance management, data warehouse and business intelligence topics at The Data Doghouse. You can reach him at rsherman@athena-solutions.com or (617) 835-0546.

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