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CPM and MDM: The Missing Link
Two of the most popular buzzwords in business intelligence are Corporate Performance Management (CPM) and Master Data Management (MDM). Almost every vendor and consultant in the traditional business intelligence space has attached themselves to one or both of these terms. Few, if any, have figured out how to exploit the natural synergy between these two seemingly different disciplines. When used together the result is a one-two knockout punch.Corporate Performance Management
Although the industry has not settled on the one sentence description for CPM, it is generally accepted that CPM is a discipline combining traditional data warehousing, business intelligence, budgeting/planning/forecasting, and dashboards/scorecards/analytics. At the core of CPM is the notion of interrelated metrics providing insight and actionable items to the business for monitoring and action.
Leading and lagging indicators which provide early warning and post action metrics can be expressed in various forms ranging from executive dashboards to balanced scorecards to strategy maps and their many variations.
One of the more approachable methods for mapping cause and effect is the analysis chain where metrics are mapped together in a cause and effect chain. At one end are highly visible financial metrics such as net income or EBIT. At the other end of the analysis chain are the root cause metrics that can be traced as a dominant metric to impact the financial metric.
A simple example of an analysis chain:
[# of Customer Attitude] impacts [Customer Retention Rate] impacts [Net Income]
In analysis chaining each metric is also mapped against two dimensions: Availability (High vs. Low) and Understanding (Universal vs. Specialized). The analysis chain then takes a form of a two by two matrix:
In this case the Net Income is both universally understood and highly available; the Customer Retention Rate requires specialized knowledge to understand but it is still highly available; Customer Attitude requires both specialized knowledge to understand and is not easily available.
In practice an analysis chain can be much more complex. Historically an organization can have hundreds of analysis chains, but there are usually less than 15 critical analysis chains that strategically impact the organization.
Master Data Management
MDM can take many forms such as Customer Data Integration (CDI) or Product/ Employee/Vendor Master. Similar to CPM, the industry has not solidified on the one sentence definition of MDM, but generally there are two considerations common to MDM.
1. Master data is shared information critical to providing a unified view of the subject (Customer, Vendor, etc.) enabling high confidence enterprise-wide analysis and reporting.
2. Implementation of a party-based model allowing the master subject to be modeled illustrating the various relationships in which it participates.
MDM has sometimes been referred to as "conformed dimensions on steroids".
Critical to MDM is the concept of defining core and extended sets of master data. Core data is the root of common data that any application accessing the master data will need. The core at a minimum exists with a set of fields which when concatenated provide uniqueness to the customer record. Although this may seem simple, such as using social security number, many times this is the biggest stumbling block to get MDM analysis off the ground. Legacy systems, syndicated data, or resulting data from mergers can all cause the uniqueness to be much more than the simple SS#. The core will also have common data that will be used by all or nearly all applications. Beyond the core there exist additional data elements. The data is often grouped into non-core segments that have some kind of business or technical affinity.
CPM & MDM - Complementing Disciplines
As defined above, CPM through the analysis chain is most concerned with high impact metrics. The belief in universal definitions (MDM) is implicit in the slicing and dicing of these metrics, which occurs when the organization is trying to determine the cause of a variance in performance metrics.
MDM though is concerned with the common dimensions and providing a single version of the master subject (Customer, Vendor, etc.). In choosing to implement MDM, the natural implication is the management of CPM metrics.
Without MDM an organization is at risk that its CPM analysis of its metrics may be disjointed and uneven. Even if an organization has defined its 15 strategic analysis chains, measuring the data points within the chains using inconsistent master data makes the metrics suspect at best.
Using the Net Income/Customer Retention/Customer Attitude from above, it becomes apparent how the metrics can be dangerously misleading without the master view.
In this example the organization is selling computer chips business to business, but the definition of a customer is different for the various metrics.
- The Net Income is sourced from the general ledger (G/L) where the customer is at a corporate level such as IBM.
- The Customer Retention Rate is derived from the sales force automation (SFA) system where the customer is defined at a site level such as IBM Boca Raton vs. IBM Armonk.
- The Customer Satisfaction metric is not captured in a system, but is a subjective opinion of each buyer at IBM by the appropriate sales representative.
Adding to the complexity is that the G/L and SFA have incongruent rollups of the customers due to reorganization of the customers file in SFA on a regular basis. Thus an IBM site in the G/L customer file may rollup to a different hierarchy in the SFA. If the analysis chain was implemented with support of MDM, the metrics would use the same definition of the customer and provide a level playing field for measurement.
MDM as the Foundation for CPM
While each organization understands that there is a cause and effect relationship between metrics (as represented in the analysis chain), the metrics themselves may be useless and misleading without MDM.
Whether using analysis chains, balanced scorecards, strategy maps or some other CPM method for metrics, an added analysis of relation of the metric to master data is the best way to ensure that the same yardstick is being used to measure the metrics. Thus, early on in the business analysis of the metrics an organization needs to initiate a concurrent effort to assess the master data implications with the metrics.
This will ensure that the one-two punch of CPM & MDM will have real business impact and not merely falter at the gate as another set of IT initiatives.
Anthony Politano has more than 20 years of experience in IT and is the author of Chief Performance Officer. Read his blog at www.tonyfromjersey.com.
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