I have had a number of comments regarding the use of Entity Level Business Modeling. So let me try to explain why I use this method of describing the business.

This type of model is used by accounting firms to provide a means for their audit staff to understand the characteristics of a business and assess the risks associated with none performance. We often view our business from an internal perspective and do not consider how external organisations see us as a business. It is important if we need to attract investors, appease the regulatory bodies and convince internal stakeholders to describe our business in a manner that provides a risk assessment on non-performance and the steps management will take to corrective the situation.

What I will try to do is use a Telco example shown below extracted from one of the models I have created to illustrate how the Entity Level Business Model works. After this you can make your judgment as to how usefulness of this approach might be to you.

The overview diagram is a succinct way of showing a typical business model illustrating clearly the external factors that impact the internal processes. When reviewing a Business Process Management or Business Intelligence project it is advantageous for the Business Architect to have a clear understanding of the business drivers. This diagram although simplistic provides a good overview and is used to obtain an agreement with the client on their understanding of their business. This can be taken one step further to gain agreement with the customer on the Value Chain.

Once we have the overview diagram and value chain agreed we can then move to a specific level 1 process (End-to-End) and put together the information required to start building the detailed process diagrams. There is a template for doing this which I have described in a previous blog. However, what I will do now is select a level 1 process and show a generic completed template form. The process I have selected is “Customer Care and Billing”

The methodology provides a framework for setting the Process Objectives and linking the Critical Success Factors (CSFs) to both the objectives and Key Performance Indicators (KPIs). This is important as quite often I am asked how to define the operational KPIs, which hopefully now is explained.  Another important consideration is that the main functions groups within the End-to-End process are defined and linked to their Inputs, Outputs and Systems for maintaining the data along with the main transaction groupings.

The risks of non-performance are also discussed and their impact on achieving the objectives along with how management perceive their responses to mitigate the problem. The document also tries to identify the areas to be considered for performance improvement. This can be very useful information when identifying the “Quick Wins” during a Business Process Improvement project.

The information for the input to the “Entity Level Business Model” is captured during workshops with Process Owners and Stakeholders. Usually the workshops will include those process owners and stakeholders that interface to the Level 1 Process under discussion. In preparation for the workshops I consider competitive companies and how they are structured as well as their financial performance. This is useful benchmark data and helps with understanding the businesses competitive pressures. There may also be specific industry frameworks with predefined industry processes that can be considered i.e. SCOR (Supply Chan) and eTOM (specifically for Telcos).

It does seem unreasonable to go through all the effort of defining a strategy for the business and setting goals and objectives to achieve the strategy if its success cannot be measured. I have worked for many companies that set revenue and profit goals with no plan to achieve their targets. Also there is no realisation that success builds on success; by this I mean you should consider the success of the previous plan and define a way to build on that success with stretch, but achievable, growth and stability targets.

When I was working for Burroughs in the early 80’s, in Europe, we developed an Account Management training program for our Branch Managers.  It suddenly dawned on us it was easier and more cost effective to obtain new business from existing customers than to obtain new customers. To ensure this programme succeeded we developed workshops, for branch managers to help them facilitate sales team meetings, building and reviewing  account plans focused on identifying and closing business within the existing customer base. The process we went through was to capitalise on the investment in the account and marketing resources, identify realisable goals and define a roadmap to achieve the goals within an agreed timescale.  The graph of time over effort was used to highlight the impact of not setting objectives and activities to achieve Goals. It shows that if a goal is set without time bound objectives it is human nature to put things off until the last moment which often results in a huge last minute effort to achieve the goal and ultimately results in failure. This is also the same for objectives without time bound activities.  You might ask what has this to do with Business Process Management and Business Intelligence.  Well it highlights a few of points:

1.       There is more control over the outcomes of processes and strategic goals if we break them down into manageable tasks or activities.

2.       Human nature is to react to events based on a perception of urgency derived from the most visible outcomes. This can impact the overall outcome of a planned set of goals.

3.       A detailed history of the activities and objectives to achieve a goal can be stored for future analysis.

Also one of the more important lessons I learned in the early part of my career was that a lack of end-to-end process visibility could have serious implications on the performance of a business.  This lesson was learned from my involvement in the early MRP (Materials Requirement Planning) software market. Many mainframe and mini-computer software solutions were based on separate software packages developed to support a department’s business requirements i.e. financial software applications, production management, inventory management solutions, purchasing applications and sales management systems etc.  Communication between the departmental solutions was manual or batch and there was very little visibility across the organisation. One of the failings of the early Production and Inventory Control systems (MRP1) was the focus only on the material planning of the manufacturing or logistics facility with very little or no marketing or sales input. This lead to highly efficient production facilities converting raw material into finished products based on the material planners interpretation of demand. This caused a massive increase of expensive finished goods inventories with no customer orders. On the other hand there was no capacity taken into account with MRP I which meant there was often insufficient resources and capacity to meet the customer demand if the demand forecast was correct.

To remedy to this problem evolved when MRPII evolved taking into account the four key resources of a manufacturing organisation. MRPII integrated the software applications to manage these resources with resource planning and capacity management. The problem with MRPII is its very complex to implement and expensive to adapt to specific customer needs; also it is a transaction based system which has inadequate reporting for managing the business. Businesses are complex and management does not have time or the capacity to review detailed transaction reports as decisions are usually triggered by exceptions. These deficits lead to the creation of decision support systems and finally Business Intelligence. Also more sophisticated Corporate Planning; Customer and Supplier Relationship applications have evolved which are becoming integrated through web services and business process management solutions.

Sometimes it is difficult to determine the relevance of the information we collect through the many business activities along with the importance of that information to the organisation in achieving its business goals. That it is important to start by reviewing the Value Chain and the Key end-to-end processes decomposing them into operational processes and activities.

Adopting a standard Framework such as SCOR (Supply Chain Council Operations Reference) highlights the typical process decomposition. The SCOR model although focused on Supply Chain can be and is being adapted to other industries and is similar to the APQC Process Classification Framework(PCF) discussed in a previous Blog. SCOR has three defined process Levels with the 4^th level defining unique company practices to maintain a competitive advantage, which is out of scope in terms of the defined reference model. Within the SCOR framework process metrics and best practices are recommended along the ability to fine tune the process elements to a company’s specific needs.

When I was lecturing at SIMM (Singapore Institute of Materials Management) I was asked to develop and deliver a course on Supply Chain Intelligence to students studying a Logistics Degree. The objective of the course was to illustrate the value of using business metrics to monitor the achievements of an organisation through the use of Business Intelligent tools.

This proved to be quite a challenge as many students were not familiar with key management ratios. Also they had no previous work experience and could not conceive of the value of business performance measures to an organisation. Whilst researching course material to explain the value of Business Intelligence, I came across an excellent document called “The Business Performance Handbook” produced by the Performance-Based Management Special Interest Group (PBM SIG) a U.S. Department of Energy (DOE) organisation.

In the document they define a performance-based management programme as a systematic approach to performance improvement through an ongoing process of establishing strategic performance objectives; measuring performance; collecting, analyzing, reviewing, and reporting performance data; and using that data to drive performance improvement.

This fit well with my understanding of Performance Management and seemed to provide a good framework for the lecture:

·         Step 1: Define organizational mission and strategic performance objectives.

·         Step 2: Establish an integrated performance measurement system.

·         Step 3: Establish accountability for performance.

·         Step 4: Establish a process/system for collecting performance data.

·         Step 5: Establish a process/system for analyzing, reviewing, and reporting performance data.

·         Step 6: Establish a process/system for using performance information to drive improvement.

One of the more interesting points, raised in Step 3, was the importance of accountability to the success of performance management. This also reinforced my belief that key Performance Indicators should be derived through a decomposition of processes and their key ratios. Through the decomposition KPI’s can then be assigned to individuals who are then accountable for ensure operation performance is met. Also by decomposing the KPIs we can analyse the impact of non-performance, and improvements made through tactical adjustment to the plan.

Using a conceptual framework stimulates thought about what should be measured. Frameworks are useful to organise ideas, identify common vocabulary, and ensure sufficient coverage of the performance measurement system. Some frameworks fit particular organisations better than others.  But rather than take a considerable time, and investment, to decide, which is the best approach I would suggest it really does not matter as any framework will help get an organisation started. Later when updating performance measures, it is useful to review other frameworks to identify new ideas and approaches that might improve your system. There are several Frameworks available and below are some of the better known ones:

The Balanced Scorecard - In 1992, Robert Kaplan and David Norton introduced the Balanced Scorecard concept as a way of motivating and measuring an organisation’s performance.

SCOR Scorecard - Has over 200 key performance metrics to monitor overall supply chain performance (level 1 metrics), as well as, many focused metrics to help a specific process to improve level 2 and 3 metrics.  This metrics are used to build performance trends for areas under improvement, or to compare against industry best practice performance.

The ”Critical Few” Performance Measures - Having too many measures—therefore generating  a large amount of routine data—could distract senior management’s focus from those measures that are the most critical to organisational success.

Performance Dashboards - A performance dashboard is an executive information system that captures financial and non-financial measures as indicators of successful strategy deployment.

The Malcolm Baldrige National Quality Award Criteria - In 1988, the Malcolm Baldrige National Quality Award (MBNQA) was instituted to promote total quality management (TQM).

Six Sigma and its derivatives - is a disciplined, data-driven approach and methodology for eliminating defects (driving towards six standard deviations between the mean and the nearest specification limit) in any process -- from manufacturing to transactional and from product to service.

Back to the lecture: Using a Business Intelligence tool with a predefined demonstration made it easier for me to help the students understand the value of Performance Management and how it fit in to the rest of their course work. As they were Logistics students I used SCOR.

This led me to believe that before embarking on a Performance Management Project it would be useful to demonstrate the power of BI to management and the stakeholders. Also to stress that acceptance of accountability is, key to the future success of the project.

Many of the Business Intelligent projects I have worked on have been exceedingly challenging. The challenge is not the technology; it is often determining what should be measured that proves to be the problem.  Many managers do not seem to have a clue, when it comes to determining the key metrics that can be used to establish the performance of their organisations operational units. There is also the other side of the coin, where management focuses at a too detailed a level, and cannot link operation performance back to the higher key performance indicators of the business.

There is no need to re-invent the “wheel”. Several frameworks are available that can be used to accelerate a Business Intelligence project. I have used a Balanced Scorecard approach and the Supply Chain Councils SCOR framework on some of the projects I have worked on. These can be used at a more detailed level in conjunction with Six Sigma and Lean principles. Most frameworks are similar in their approach and rely on the decomposition of organisational goals and objectives into more detailed activities and tasks. This approach provides a framework for assigning responsibility and ownership of the performance metrics. As an example of process decomposition we consider the cash-to –cash cycle time which is made up of three other key processes:

1.       Days Payable Outstanding (Accounts Payable)

2.       Inventory Days of Supply (Inventory Management)

3.       Days Sales  Outstanding (Accounts Receivable)

The three sub-processes can be further decomposed to involve other parts of the organisation i.e. Planning, Procurement, Manufacturing, logistics and Sales etc. Which when applied tightly integrates the organisation breaking down barriers of communication.

Using pre-defined performance frameworks accelerate the successful implementation of Performance Management Projects. They also provide a means of benchmarking an organisations performance against others in similar industries.