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.

Continuous Planning Architecture, Phase 2

Back in April, Kimberley Bermender posted on the finance systems architecture needed to support a continuous planning environment. The overall design goals included:

• Lower cost of maintenance,
• Standards-based data integration,
• Support of accurate, near real-time views into operations,
• A platform to support detecting, modeling, selecting and implementing change and then measuring results.

The main ingredients were:

• financial and operational data stores,
• an analytic (OLAP) engine – with reporting, and
• planning applications

Inherent in the architecture is the movement of data between data stores and OLAP cubes, as well as fact and metadata management. To build on that architecture, “phase 2” can include two other components that build on those design goals and get you closer to enterprise performance management nirvana.

The first is master data (or ‘reference’ data) management, and the second is a common enterprise performance management rules or calculation engine.

Master data management includes the tracking and control processes of data relationships (especially hierarchies) and instances across the enterprise. For example, product sales for a store in Ft. Collins, CO could roll-up to a ‘Central’ region one quarter, and then to the ‘West’ region the next quarter after a re-org. It’s important to keep track of which region it belonged to when doing quarter over quarter comparisons and other management reporting (not to mention statutory reconciliation and reporting). And that hierarchy could be contained in the store reporting application, the sales forecasting system, the G/L, the customer relationship management (CRM) system, and so on. Right now, those relationships are probably being manually managed and ‘lightly’ controlled. Our more complex financial systems require more automation and more rigorous control over master/reference data. And it certainly addresses at least the first 2 design considerations of Kimberley’s architecture.

For more on master data, see this DMReview landing page.

The second component is a central business rules/calculation engine. In any enterprise performance management environment, users can easily get bogged down in the definitions of data and information. For example, that Ft. Collins store could be looking at a ‘revenue’ report and not know if it’s booked revenue, commissionable revenue, recognized revenue, and so on. And even when they find out what kind of revenue it is, there can be a question of it’s accuracy: how did head office calculate it, where did they get the data from, and does it include intercompany sales or not?

Having one business rules engine lets the enterprise define ‘recognized revenue’ once, with control over the algorithms, the data refresh frequency, the data sources, and so on. Once the rules engine has certified a number, it can be used by all other enterprise performance management systems: planning can use it for prior actuals, strategic financial models can use it for long term scenarios, same store sales dashboards can use it for ranking, and so on.
The three-fold goal is to get better transparency into financial information (how did we get that number), better accountability (finance owns and certifies the number), more efficiency (define it once, don’t reinvent the wheel), and ‘believe-ability’ (start debating what to do about the results, not where the number came from).

Here’s a good article by Robert Blasum in DM Review on central rules (he also connects them to master data management)

Thanks to Kimberley and the team for letting me guest blog, please feel free to visit the Business Foundation blog over at http://businessfoundation.typepad.com/

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.

Instant Continuous Planning: Just Add Water

It's a strange feeling when personal and business lives intersect, and as I sit down to write about the value of continuous planning cycles in the business process, I am struck by recent personal experience.

It's March 25th, 10 pm, and I am sitting on the floor of my home office, a cardboard box beside me, as I stack piles of receipts, 1099s, stock sale receipts, etc in preparation for tomorrow's tax meeting with my accountant. I really don't know what to expect from this meeting – where am I in relation to the plans I set in January 2007? I could swear that I sat in the same place last year promising myself that I was going to improve this system.

And while some of you may relate to my experience (hopefully, as misery does love company), it gives me pause to think that, on a much larger scale, many of our corporate planning cycles don't fare much better. As a business director responsible for budget and planning cycles, when do you start your process? How many annual/monthly/weekly iterations do you go through? What is the effect of business change on your planning cycle? Are you feeling like there's a cardboard box beside you, yet?

With the demand for businesses to adapt quickly to changing markets in order to stay competitive and operate at maximum efficiency, we have seen significant streamlining of the planning process in recent years. In parallel, we've seen the tools and supporting infrastructure technologies become more sophisticated and robust in order to support operational and reporting needs. With pressure to move from a lagging to leading view of the business, we've evolved from annual budgets, to quarterly planning, to rolling 13 month plans and now we're recognizing the need for a continuous planning cycle that provides an accurate, real-time view of our operations.

I often hear that the concept of continuous planning in a fast-changing corporate environment is a Utopian vision rather than a realistic goal. And yet large, dynamic companies such as Symantec and Yahoo have successfully implemented continuous planning cycles into their business processes. So how do they approach this? What tools do they use? How do they measure results from their planning process?

Implementing a continuous planning cycle in your organization is not about buying a tool. It's not about agreeing to a process during a management meeting. Continuous planning requires the direction and support of the entire management team to reinvent the way the company approaches the planning process. It needs management to create a chain of accountability throughout the organization, from C-level to individual contributors; every person knows their role, their goals, the company's goals and where they stand in relation to meeting those goals. Continuous planning requires the implementation of best practices and an effective process within the organization, as well as the tools to support the process.

A successful continuous planning process requires collaboration between executive management, finance department and operational teams:
1. Define strategic goals.
2. Create plans, rolling forecasts & budgets for all levels of the
organization.
3. Roll out, analyze against execution & provide feedback loops.
4. Model & realign plans as needed.
5. Monitor & report, with audit information for regulatory & statutory
reporting requirements.

In a continuous planning cycle, steps 3 & 4 are iterative and constantly changing, driving the need for updated information to be delivered to the desktop at a near real-time rate.

To Be Continued... The Secret Sauce in the Technical Details

Insight on the Gartner BI Conference in Chicago

As a long time attendee of the various Gartner events, my favorite has always been the more intimate setting of the BI summit - typically held in Chicago. Boy, was I surprised at the 1200+ attendees of this year's conference and the expectation of bigger growth to fuel a move to Washington, DC in 2009. Last year’s event pales in comparison. BI advocates, typically a cross-over role between Finance and IT, have made a rather dramatic transition into the IT camp for this conference. Many of the sessions were educational and entry-level in scope and oriented to the first time architect and supporter of Business Intelligence environments. The event has clearly moved away from the user of past years.

Also notable was the absence of discussions on the relative cost savings in deploying a BI environment for better business planning and analysis. Other than the one rather cheeky session on how to negotiate a good deal with your BI vendor, I expected to hear more about cost cutting and using BI data to enable efficiencies and identify cost-prohibitive inefficiencies. The market picture has been doom and gloom and the "R" word blatantly used. Instead I heard a great deal about enabling integration and the expansion of analytic applications.

I think this is great news! Clearly the message was to expand the BI footprint and make use of the technology that can drive profitability, not focus on doing more with less. I had conversations with luminaries such as Howard Dresner and Ron Powell, but I also spoke with a number of vendors and implementers such as IBM GBS and Palladium, who had similar messaging of exploiting the existing technologies and refining processes to drive revenue and deliver data on a more continual basis to the employees who can make the right decisions in real-time. This to me is a message of expansion and focus, rather than retrenchment and limitations. I heard a great deal about the continual need for data, an almost real-time need to do continuous planning and report on finer levels of granular information in a more automated fashion. The message was clear. BI is tops in priority and destined to gain more mindshare of senior IT executives as the business expands and focuses their growth. To grow and expand you always need Innovators who can do more with less, but also the visionaries who can see the gold amongst the rock.