The Order
Recently, I was asked to participate in the response to a mock request for proposal for a consulting rating agency. They wanted to see what we would propose they do to solve a fictitious company’s many analytics, business intelligence and reporting problems. They listed a set of seven issues, in no particular order, that needed to be addressed.
I was asked to draft a summary of the issues, and how IBM would respond. As I analyzed the issues, I was surprised at the pattern I saw emerge. The following was my response:
As part of our proposal to assist your company, IBM has developed a series of viewpoints, insights gained through its experience and research. These viewpoints, aligned to the issues your company has identified, will serve to expedite insight derived through the project, either being validated or adjusted through the project approach as informed by the IBM Analytical Framework.
Similar to using multiple instruments to effectively monitor a complex machine, working across the range of issues is important to arriving at the desired destination. Insight gained from analysis on one issue informs direction on other issues. Our diagnostic approach provides this type of assessment. However, in the longer-term the desire to solve all issues simultaneously can lead to ignoring critical dependencies, resulting in missing significant opportunities and business benefits. Clearly understanding how each issue builds upon foundational premises leads to the highest levels of performance.
Issue: People & Organization
“The company is unsure about who should drive this strategy, what team should manage it, who should support this within the organization, what key processes must be managed, which methodologies and best practices should be used. To this end they are thinking of a competency centre.”
IBM Point of View: IBM believes, based upon the issues identified, that the evolving role of the CFO in the last ten years positions him as critical to successful resolution of these challenges. IBM’s CFO Study based on input from over 1,900 CFO’s and senior Finance leaders worldwide attest to the emerging role of the CFO and how their influence reaches throughout the organization and into the Boardroom. The results show that the role of Finance goes beyond traditional Finance and is enterprise focused.
Certainly the CFO is not alone in responsibility nor capable of single-handedly resolving all the company’s issues. The traditional finance systems were not designed for today’s information explosion, and the traditional finance work force is not trained for today’s analytical needs. However expanding upon the infrastructure and capabilities in the CFO organization will provide the shortest path to success.
Issue: Data Warehouse
“The company currently uses a mix of tools both at the HQ and in the business units. There is little standardisation of metadata and each business unit uses its own different reporting terms and definitions. The reporting is fragmented by both business unit and business function (Manufacturing, Wholesale & Retail). Furthermore, there is a range of complex and difficult to maintain data integration processes that support operational and management reporting. The group CFO and CIO desire an enterprise data warehouse and want to standardise on data integration, data quality, meta data and reporting standards across the group.”
IBM Point of View: Analytical processes begin with data. Sophisticated models based upon faulty inputs produce meaningless outputs. Consistent with the emerging role of the CFO, a trend emerging in BI is recognition of the consistent value of the finance data. The underlying premise of finance systems are data driven, (1) accepting inputs from every source system capturing financial events, (2) creating an enterprise view of those events, at least in a limited financial sense, (3) with increasing pressure to provide insight into risk, strategic revenue planning, and business model innovation/reshaping as well as their traditional areas of focus such as cost reduction and selection of key performance indicators.
However, limits in the finance system architecture historically employed dropped the full breadth of attributes of interest to others outside finance. With advances in technology, it is possible to create data warehouse environments that provide very granular levels of detail, including individual customer, material and salesperson views yet with the reliability of the finance system: consistent, controlled, reliable information meeting the highest audit standards.
Approaching the data warehouse from the potential uses of the data alone fails to identify the commonality of the underlying business events. The combinations and permutations of source system business events used for analytical and reporting purposes change rapidly. Fundamental acts of commerce – business events – change much less frequently. This fact is a much more stable organizing principle; capturing and organizing source system business events, then providing capabilities to roll-up, summarize, transform and analyze data for a myriad of purposes which change much more frequently according to business needs and capabilities.
Issue: Financial Reporting
“The financial close, consolidation and reporting processes are both time consuming and resource intensive. The organization does not have a standardised chart of accounts or standardised report packs. Each of 10 regional production sites are run as independent business units and have a regional financial controller who produces financial reports for local requirements and also submits data for group consolidation. The Group controller is responsible for the consolidated financials and reports to the CFO responsible for all financial and management reporting. Lack of responsiveness to changing business conditions, poor transparency and inability to meet future compliance demands are identified concerns.”
IBM Point of View: The world is awash in data, and more is created every day. Yet less of this newly created data is accumulated into meaningful outputs. And accumulating data is something very different than enabling an internet type search for a specific piece of data. The consolidated financial statements of the organization are, by definition, enterprise wide, although perhaps only for a handful of attributes. Yet this “supply chain” of data in summary is well respected if not adequate.
Working to expand this supply chain, in terms of (1) depth providing greater transparency to underlying business events, (2) breadth of attributes supporting a broader range of financial reporting processes, and (3) frequency to support more timely analysis, efficiently guides efforts to located trusted sources of data. This focus attacks the core issues of financial reporting in the most efficient manner.
Locating underlying business events source system by source system that tie in total to today’s reported financial results provides a step-wise approach to expanding data within the data warehouse while at the same time providing greater business benefits immediately in reporting.
Issue: Sales and Management Reporting
“Currently the business functions provide their own reporting and analysis using (in one case) [a common reporting package], and for other BUs home-grown solutions and Excel. This is considered inadequate, costly and has been made a key priority by the COO. The sales group want a comprehensive reporting platform to enable much greater degree of self-sufficiency whilst increasing analytical functionality.”
IBM Point of View: Historically, finance controlled a very small set of attributes – the accounting code block. Reporting on other attributes required creating separate “supply chains,” sourcing business events to reporting processes. With the expansion of computing and increasing digitization of information, the number of data “supply chains” has expanded dramatically.
The company’s work on ERP implementations over the years have likely captured many of the benefits of supply chain consolidation, concentrating resources and processes on fewer, high-value low-cost suppliers. Similar benefits will accrue to organizations that manage information as an asset, recognizing the data “supply chain” from capturing business events in source systems to aggregating and analytics in the end.
Organizing the data warehouse around business events, maintained at a granular level to retain customer, manufacturing, sales and other attributes, through a controlled and secure supply chain enables “pivoting” the financial numbers by hundreds to perhaps thousands of critical attributes. This approach enables sales and management reporting perspectives on top of the established finance data backbone, with a consistent set of tools and processes supporting an ever wider scope of reporting and analytical processes for the organization.
Issue: Budgeting, Planning and Forecasting
“For budgeting, the company relies upon on spreadsheets and manual processes. There is a disconnect between strategic plans (long-term), financial plans (fiscal) and operations (S&OP) which are run in silos. Budgets cannot easily be flexed to reflect changes in strategy and business conditions. The budget cycle is too long and there are concerns over the disconnectedness of the existing solutions as well as an inability to forecast or scenario plan for different outcomes. Furthermore, there are issues to link operational plans, between distribution and manufacturing and links between operational and financial planning. In addition they are considering some more sophisticated merchandise & store planning capabilities.”
IBM Point of View: Next attacking the budgeting, planning and forecasting process bridges the company from gaining confidence in measurement of actual, meaningful results for broader and broader sets of functions, with greater transparency and limited breakages, to beginning to harness the power of those insights to drive achievement in the organization.
Implementing the budgeting, planning and forecasting process next creates the infrastructure for measurement of fundamental measures of effectiveness, again starting with the foundational financial processes. Having first established the data and analytical infrastructure capturing granular results of operation provides two key benefits: (1) the infrastructure expedites many aspects of the summary level functions of budgeting, planning and forecasting, allowing focus on the new process aspects of these functions, and (2) creating the foundational data supply chain with granular levels and expansive attributes provides tremendous flexibility when defining which dimension of data to use in budgeting, planning, and forecasting. The first question when plans and forecast are not met is “why?” Without granular, transparent data of actual results, these questions cannot be answered.
Establishing foundational analytical processes enables the higher order functions of scorecard or dashboards, and advanced analytical processes.
Issue: Scorecard or Dashboard
“The senior management team have identified the need for a scorecard or dashboard to deliver KPIs to the BU heads and the management group. They want to focus on measures related to high level financial and non-financial performance (such as customer and quality measures) and to help align daily activities with the more long term aims of the company. Furthermore, at the functional/process level, the sales, marketing and production functions are looking for operational dashboard/KPI reporting.”
IBM Point of View: Scorecard and Dashboards provide a very effective means of establishing, publishing, monitoring and then driving change in the organization. By having established the information rich repository and foundational performance measure processes, KPI’s can be defined for a broad set of measures, both financial and non-financial, using traditional finance attribution or customer, material or sales views. Similar to expanding the foundational financial reporting environment to non-financial data, scorecard and dashboard initiatives can expand the budgeting, planning and forecasting activities to non-traditional metrics, powerfully motivating, monitoring, and measuring achievement of objectives.
Issue: Advanced Analytics
“Currently the company lacks any comprehensive capabilities for advanced analytics such as data mining, predictive and descriptive engines, traditional statistical techniques, scoring, integrated visualization and reporting for solutions such as product, supplier, customer and market analysis.”
IBM Point of View: A process of continuous innovation in reporting and analytics becomes possible, finding patterns, relationships, and insights in the business events of the organization, and using those insights to refine organizational analytical processes. This becomes possible by having established the data backbone, refined the content by use in core business processes, broadened the views it represents, and created an analytics culture which is fact-based and informed by the results of actual business events. Advanced analytics really becomes possible when the input data is accurate and accessible. The entire journey begins with capturing and keeping business events.