Wednesday, April 30, 2008

Instant Continuous Planning: Just Add Water (Part 2)

In the previous Continuous Planning post, we discussed the evolution of management processes from a lagging to leading view of the business and examined the business processes needed to support the continuous planning cycle.

Defining and evolving management processes requires the confluence of data across and between all stakeholders within the business environment, including customers, supply chain, and organizational groups such as Finance. For the Finance department, this means providing the means for continuous planning and the ability to consolidate these digested results with the organization's other data. To support this, there are a number of technologies that must be in place within the organization:
  • Planning application
  • Analytic application (OLAP database)
  • Financial & operational data stores
  • While not necessary, performance management tools such as scorecards and dashboards provide a feedback loop
Best practices dictate that the following technical and process requirements support the continuous planning cycle:
  • 100% uptime of the planning application. This is particularly important for global enterprises where teams in various geographies are accessing data; no group can be shut down.
  • Near real-time reporting. Incremental data updates and calculations provide near real-time reporting against plan data.
  • Integration with operational and business data. Access to operational data provides necessary planning context; as well as instant feedback and adjustments to the plan. Availability of other data such as supporting detail or plan assumptions is integral within the reporting environment.
  • Consistent performance. Ensuring fast and consistent performance is crucial during the planning cycle.

Architecture to Support Continuous Planning Cycle

The architectural framework required to support a continuous planning cycle includes:
  • Change Data Capture. The planning application collects data and performs value-adding multidimensional calculations upon the data, but does not aggregate it. Through an intelligent backup process, only changed data is backed up and extracted from the application.
  • Financial Data Store. At an established rate (every 2 minutes, for example), changed data is extracted from the planning application and is automatically loaded, with associated metadata and security, into the central repository. The shared data enables the ability to quickly digest and present data to the analytic applications.
  • Load into the Analytic Reporting Application. From the financial data store, the financial assets are loaded into the reporting analytic application, where consolidations can be completed on-the-fly.
  • Reporting from Analytic Applications. The reporting application should be easily accessible from a wide range of tools – including performance dashboards, scorecards, report writers, spreadsheets, and any other common reporting tools used within the organization.
  • Alternative Architectural Options. Flexible reporting strategies can be a valuable extension of this architecture. For example, a planning cube can contain few dimensions and limited granularity. The reporting cube can have additional dimensions and a deeper level of detail to support robust reporting needs.
Previously, the support of this architecture required a patchwork of data movement tools and custom scripts that did not allow for the integration of data from the proprietary source systems into a larger financial data warehouse. This did not enable the sharing of data within the greater organization and generally required a costly combination of tools and consulting that needed ongoing maintenance and support.

But companies are now accomplishing this efficiently and cost-effectively, with a significantly lower cost of maintenance. With the availability of comprehensive, standards-based data integration solutions and management teams establishing best practices around their planning cycles, the transition from a lagging to a leading planning process, with accurate, near real-time views into operations, is a realistic goal for any organization. The return on this investment is the creation of an innovative, flexible, and dynamic planning cycle that allows your company to quickly recognize changes in the competitive landscape, the ability to model changes quickly, determine the best alternatives, implement, and measure results.


Ron Dimon said...

Hi Kimberley,
Thanks for presenting continuous planning very clearly. I think once an organization has "operationalized" the architecture you describe (let's call it phase 1), they may be ready for an advanced (phase 2) architecture. I think 2 key components of phase 2 are master data management (aka reference data management) - where an organization can centralize it's data relationships including hierarchies - and a common rules/calculation engine. This really begins to bridge the gap between actuals and plan (including budget, forecast, scenarios, etc.) reporting & analysis.

Kimberley Bermender said...

Ron, This makes an excellent suggestion for an upcoming post. Thanks for your comment.