Is Innovation Magic?

There seems to be this perception that if you are introducing innovation or a new way to capture information and, as yet, no one else is doing it that way that it must be magic. Hardly. The paradigm of "thinking outside the box" is about enabling a perspective that has either been overlooked or underutilized. The simple concept of combining finance data with operational data should not be new or insightful or magical. It should be a simple everyday occurrence, but yet, it has been cited as unnatural or innovative.

In today’s economy the only way a company can guarantee success is by careful planning. If we think of the three elements driving the financial aspect of the business: the Plan, the Budget and the Forecast, only one of those has to be in constant motion to achieve success with the other two. If you are constantly planning and adjusting your plan, your budget and forecast will follow and you can take adjustments to the budget and forecast in lesser increments than the planning process. The key to enabling the continuous planning process is in having access to the financial data. That data is derived from the business and starts with a baseline plan. It needs to be continually fed with operational data to be reflective of the immediate business health. Then the Forecast will be adjusted and consequently the Budget to meet that Forecast and the iteration of the Plan.

Robert Kugel from Ventana Research sums up the path of the source of the data nicely in his blog of March 13th. CFOs Need Better Financial Information Management. I contend that it is not only the CFO who needs better Financial Data, but the Office of the CFO who must deliver the aggregated Financial data back down to the business to assist them in planning and creating profitable plans. This constant loop of data means that IT and Finance have to be in synch in the granularity of the data and the delivery of the data regardless of the tools in place. Today, it is less about the end-user technology than it is about data access and data delivery. Bad data yields bad decisions. That’s the obvious parable here.

So if we tie this back to innovation and magic, the result is that Merlin has yet to be uncovered in this economy and we suffer from a simple problem of a lack of access to the right data or information to be able to make the right decisions in real-time with the most current and scintillating data. And, more importantly, we have to bring together the education necessary to see what the data is telling us, but that is left for another blog post. Here we advocate continuous planning. The next phase is continuous data education. Can we achieve success in the future by always assessing based on the events of the past? That is where innovation may help.

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.