Corporate performance management (CPM) is the latest rage within the data warehousing/business intelligence (DW/BI) industry. But where does one begin to gain a handle on what CPM is, where it overlaps with the rest of DW/BI and, most importantly, how to attack a CPM implementation? I will address these questions beginning here and continuing over my next few columns, specifically examining how the value-driven data warehousing (VDDW) modeling and integration framework (described in the June 2007 issue of DM Review and DM Direct1and detailed on the Foulkrod Enterprises Web site) constitutes a superior content foundation for CPM.
CPM Defined
Let's start with the most basic question first. What is CPM, anyway? Is it really something new? Is it anything at all? These are questions that bear addressing, for our industry suffers the reputation, not entirely undeserved, of being long on message and short on results. When we speak of "CPM," are we merely assigning new names to existing tools and approaches in an attempt to generate hype or are we talking about something truly new, or at least, a new and better approach to an old problem? Further, is CPM mature and robust, or is it still a swirling ball of vapor that has yet to completely coalesce?
To assist us in answering these questions, let's first draw an important distinction: CPM the discipline versus CPM the toolset.
As a discipline, CPM can be defined as the practice of forecasting performance, planning and budgeting accordingly, setting benchmarks for the various segments of the business, tracking actual performance against those goals and taking appropriate remedial or opportunistic action. As a discipline, this certainly isn't anything new - it could simply be called "business planning, monitoring and management," which is something as old as business itself. What is new is the efficiency with which the associated information management tasks - typically involving much tedious spreadsheet jockeying - can be executed with the assistance of various tools that are coming of age.
The CPM toolset, then, consists of the technologies that promise to re-engineer the discipline of corporate performance management. Again, there is a mixture of both old and new that needs to be addressed. Much of the underlying functionality required to support CPM is nothing new or unique, consisting of conventional components already subsumed under the BI umbrella: reporting and visualization tools, collaborative workflow, unstructured/external data integration, predictive analytics, etc. Perhaps this is a cause for some of the wrangling over how to classify CPM, i.e., whether it falls under BI or its own category, because much of the functionality it requires is generally understood to be part of the BI stack. That being said, CPM goes beyond conventional BI in that it introduces productivity tools that automate best practices for planning and budgeting. In this sense, corporate performance management represents a repurposing or retargeting of conventional BI, with some added application functionality, toward a specific objective, namely, the comprehensive planning, monitoring and management of the firm's financial performance. 数据挖掘实验室
CPM - A Bottom-Up View
While much of the market emphasis around CPM centers on the aforementioned aspects - the supporting productivity and process enablement tools - the methods for generating and integrating the data content required so as to support comprehensive performance analysis do not enjoy significant market attention. That's not surprising. Modeling and integration don't tend to generate a lot of hype. Nevertheless, they are key determinants of success or failure for most DW/BI initiatives and, when done well, can greatly simplify the system landscape and even reduce the investment required in additional tools.
This is where the VDDW framework comes in to play. While CPM productivity tools are rapidly evolving and maturing, the VDDW approach addresses the big missing piece - content - and specifically, how to model and integrate operational, business process and financial data so that the various tools in the CPM productivity suite have a healthy and enriched supply of it. 数据挖掘实验室
CPM requires insight into net operating profit across the various slices of the business, a process-centered view of the drivers of that performance, and the capacity constraints and leverage achieved on the various resources the business employs to execute those processes. This is precisely what the VDDW framework provides; and further, it does so while adhering to important data warehousing best practices. 数据挖掘研究院
The first and foremost of those best practices - a cardinal rule of data warehousing - is that you deal with data at its naturally occurring grain, generally the level of the individual business transaction. Solely from the perspective of conventional DW/BI, this rule is important for it simplifies system integration but, more importantly, ensures accuracy and maximum reporting flexibility. From the perspective of CPM and activity-based costing, this rule is equally important, for the individual transaction represents the culmination of an iteration of business activities, and activities are the constituents of processes, and processes consume resources, and resources cost money. There is then a natural schematic intersection of business process and financial expense at the level of the individual operational transaction, and the VDDW framework formalizes this relationship in such a way as to allow maximum, ad hoc flexibility in analyzing both the consumption and contribution of corporate overhead. 数据挖掘研究院
The VDDW framework therefore provides a serviceable content foundation for CPM. In my next few articles I will further explore what CPM entails and how it fits together with the VDDW, by decomposing CPM into its constituent components, and exploring the dependencies between those components, with the aim of teasing out some principles for how to execute a CPM implementation. 数据挖掘研究院
References:
1. The Data Warehouse Content Gap, Part 1. DM Review June 2007.
The Data Warehouse Content Gap, Part 2: What is ABC and How Does it Function? DM Direct June 2007. 数据挖掘研究院
The Data Warehouse Content Gap, Part 3: How ABC Benefits the Business. DM Direct June 2007.
The Data Warehouse Content Gap, Part 4: The ABC / EDW Hybrid. DM Direct June 2007.
