Michael Coveney

Michael Coveney spent 40+ years in the software analytic business with a focus on transforming the planning, budgeting, forecasting and reporting processes. He has considerable experience in the design and implementation of Business Analytic systems with major organisations throughout the world. He is a gifted conference speaker and author where his latest book ‘Budgeting, Forecasting and Planning In Uncertain Times’is published by J Wiley. His articles have also appeared on www.fpa-trends.com, that encourages innovation in FP&A departments.

Author's Articles

There are currently no published articles of this author.

Corporate Performance Management (CPM): The Need for a Framework

By Michael Coveney, Analytics Thought Leader and Author

In December 1999, Gartner introduced the concept of Corporate Performance Management (CPM), which they defined as the “... the processes, methodologies, metrics and systems used to monitor and manage an enterprise's business performance”. 

Since that time the concept has been adopted by most major software vendors, although they may refer to it using other 3 letter acronyms such as BPM, EPM and so on. 

However the market is currently confused in that many offerings, although labelled CPM solutions, are only partial solutions and do not meet the needs of CPM. CPM has also become synonymous with planning, budgeting and forecasting, which only forms part of a true CPM offering. 

To address this confusion, this document outlines a framework through which CPM can be defined and evaluated. 

Imagine that the only way you could have a car was to buy the individual components from one or more manufacturers. Suppliers would be selling the power of their engines, dashboard vendors would ‘wow’ you with their fancy dials and gauges, while those supplying the control mechanisms would impress you on the benefits of using the latest technology. As it would be up to you to put it all together, integration would be a key requirement for those with previous ‘car-building’ experience. 

Also imagine if you then had to supply your own fuel to power the vehicle, which of course would need to match the engine or at least go through various transformations to make it suitable for its intended purpose. I wonder how many cars resulting from this process would fulfil the original vision that the user imagined? 

Something similar happens in the world of decision-support software. Managers are faced with a range of tools and technologies under various vague names, such as CPM, BPM, BI, OLAP – all of which claim to be able to support organisational decision-making. But, as with the car analogy, it is up to the end-user to figure out how it all fits together. 

A Gartner survey showed that most BI applications are disconnected from the business process and the decisions they support, and that many decisions that are made have a negative or suboptimal effect on performance. In research for his book ‘Transforming Performance Measurement’, Professor Dean Spitzer found that today’s reporting and analysis systems are used to create separate, disparate silos of information that tend to focus on the performance of individual departments. Because of this, the decisions that emanate can often undermine the performance of other departments as well as undermine the achievement of overall organisational strategy. 

Many organisations are confused as to the role of the different tools available to support decision- making. This is made worse by vendors claiming to support CPM when their definition of CPM is unclear, and the ‘how’ of making their systems fulfil this task is completely absent. 
Because of this lack of clarity, a framework is necessary that will: 

  • Provide a clear holistic view of what CPM is by describing the processes involved and how they interact with each other
  • Help organisations to identify what systems they need and how to put them together to truly support CPM
  • Assist organisations when evaluating software and service provider offerings 
  • Encourage software vendors to deliver more complete solutions. This document outlines such a framework that we will call “the CPM framework”
The full text is available for registered users. Please register to view the rest of the article.
Different Planning Methods for FP&A

By Michael Coveney, Analytics Thought Leader and Author

In this article we will look at the different methods an organization can use to set direction. 

Planning Methods

Planning involves many kinds of methods that help managers make decisions. It goes without saying that any planning system must be able to handle both financial and KPI information, it must be able to model the different business structures (products, departments, customer groupings) and possess good reporting and charting capabilities. It should also be able to report data from both a financial viewpoint as well as a strategy view through dashboards and strategy maps, as well as be multi-user that allows secure access to people with different roles.

On top of this, a planning system must also possess a range of specific capabilities whose purpose is to helps an organization prepare for the ‘unexpected’. These capabilities include:

  • Driver-based Planning.
  • Initiative planning.
  • Scenario Planning.
  • Contingency Planning.

Driver-based Planning

Driver-based planning is used to predict future values based on trends and relationships between different measures such as costs, revenues and KPIs. By entering a number into certain accounts known as ‘drivers’, the model will then calculate related information.

Drivers are set by taking a target measure (e.g. revenue or some other ‘outcome’) and establishing what directly impacts its value. For those items, we then establish what impacts them – and so on. Measures at the end of the chain are known as ‘drivers’. Where possible, ‘Drivers’ need to be validated against past behaviour

For example, the drivers of Net Profit could include price per unit, unit cost, No. of visits and sales conversion rate. By entering data into these measures, the model is able to calculate Net profit.

These models also recognise constraints such as production volume and that at certain levels cost and revenue profiles may change e.g. the impact of discounts, late delivery penalties, or that more staff will be needed which will cause a step change in values. They also recognise that there is nearly always a time-lag between the driver and the result it supports. Driver-based models are good for modelling the relationships between activities and can be used to quickly generate future outcomes, but without the time, effort and politics involved in setting these values.

However, these models only work for a certain measure such as costs/revenues that can be directly related to drivers. Other measures such as overheads will be required to get the full picture. Also, they do not take into account unpredictable external influences such as the weather and they can only model what has happened in the past, which may not be a reliable indicator of the future in a volatile market or where product life cycles are relatively short.
Initiative planning

Initiative planning recognises that it is the impact of specific actions that can help manage a change to the organic growth of an organization. Initiatives are in effect a project that details:

  •  An action to be performed
  • The department(s) involved in its delivery
  • The person responsible for overall delivery
  • The reason(s) why they are being performed and the measure of success
  • The timescale in which it is to be actioned along with defined start /end dates
  • Milestones through which the status of implementation can be monitored.
  • Resources that will be required.

Initiatives can be linked to drivers such as in the driver-planning model described above.

The difference in this planning model is that initiatives can be combined in different combinations and they can be moved back and forwards in time to see how they impact overall results. For example, if we delay initiative three by 2 months, what would be the impact on revenue and costs? Or, what if we dropped initiative two, could we bring forward initiatives four and five?

It is only by doing this kind of analysis, that the best use of resources for a given set of constraints can be determined.

Scenario Planning

Scenario planning can be used to assess different combinations of drivers and/or initiatives so that a choice can be made as to which achieves the best outcome in both the short and long-term, that is the most affordable and has the lowest risk. David Axson in his book on ‘Best Practices in Planning and Performance Management’ comments that: “Planning is not about developing a singular view of the future: one of the most valuable elements of any planning activity is the ability to factor in the impact of risk on assumptions, initiatives and targeted results. A scenario is a story that describes a possible future. It identifies significant events, the main actors, and their motivations, and it conveys how the world functions.”

Scenarios can include entering a range of driver values, trying out multiple combinations of initiatives and looking at the impact of a change to organization structures. The end result is to allow the side-by-side comparison of these scenarios, showing outcomes, any assumptions made as well as details of changes being proposed.

Contingency Planning

Contingency planning is similar to scenario planning, however, its purpose is to review the impact of a number of ‘What if?’ situations on current and forecast performance. For example, what would be the impact on profitability if raw materials were to rise by an unexpected 5%, or if the sales forecast was out by more than 10%?

Contingency models evaluate the outcome of these events and then allow managers to prepare a series of responses or initiatives that would mitigate or take advantage of such an event. Their aim is to help the organization prepare a ‘backup’ plan that can be implemented quickly.

Linking Plans to Budgets

Budgeting is concerned with resourcing a chosen scenario for a given business environment. Budgets should consist of three parts:

  • The resources required keeping the business going for the predicted business environment assuming no changes to the way the business operates. Some of this can be derived from driver-based planning models.
  • The resources required for chosen strategic initiatives to change/improve the operation of the business model. This can be set through initiative / scenario planning models.
  • Other resources not covered by the previous two parts. This will typically be manually entered or fed from supporting systems.

Together, the three parts make up the complete budget for future periods. Although most organisations conduct this process on an annual basis, there is no reason why it can’t operate on a continuous basis as advocated by the Beyond Budgeting movement.

The full text is available for registered users. Please register to view the rest of the article.
to view and submit comments
CPM Framework Overview

By Michael Coveney, Analytics Thought Leader and Author


CPM is concerned with the way in which an organisation manages its overall performance. As defined by Gartner it involves combining the methodologies used to manage strategy, the metrics that evaluate performance and the processes used to direct people within the organisation – all of which should be supported by a technology solution. 
To support organisational decision-making the framework combines the following four areas: 

  1. Content
  2. CPM Business Model
  3. Strategy
  4. Resources

1. Content 

CPM is concerned with the way in which an organisation manages its overall performance. As defined by Gartner it involves combining the methodologies used to manage strategy, the metrics that evaluate performance and the processes used to direct people within the organisation – all of which should be supported by a technology solution. 
To support organisational decision-making the framework combines the following four areas: 

Picture 1: Performance Management Framework 

  • A business model that describes how value is created by the business.
  • Strategic initiatives that are focused on improving parts of the business model.
  • Organisational resources (money, people, assets) that can be applied to enable the business model to function and that allow strategic initiatives to be implemented.

  • Management processes that direct and control planning, funding and monitoring of business operations. 
All four components are intertwined and should operate within a CPM technology solution as a continuous approach to performance management. 
Around this core system will be a range of other Business Analytic solutions, such as BI and reporting / analysis applications, that directly support specific areas within the CPM model. 
Let’s take a closer look at each of these areas. 

2. CPM Business Model. 

At the heart of a CPM system is an organisation model containing the relationship of activities that lead to organisational objectives. 

Although this model will differ between
industries, it will typically include how
revenue/income is generated; how
products/services are manufactured /
created and distributed to customers;
how employees are recruited, trained and assessed; and how the organisation complies with its legal responsibilities. These activities are linked to one or more organisation departments that determine those responsible for their execution. 

Some activities will have a one- to-one relationship with the organisation structure, but other activities will go across multiple departments. 

Quite often the relationships
between activities can be built as
a driver-based model where the
value of an input such as the
number of enquiries can be used
to determine the volume of sales and hence revenue via a set conversion rate. These models can be used to plan or assess the operation of the business by entering a few key values or ‘drivers’. 

Business Model Metrics 
Each activity can have different sets of measures that include: 

  • KPIs that measure success of the activity (e.g. the number of new customers acquired)
  • KPIs that reveal the state of implementation (e.g. the number of mailings made to the target customer base)
  • The resources consumed by the activity (e.g. people time, costs, assets utilised)
  • The risks involved in employing those activities

3. Strategy 

The second area – Strategy – typically has an emphasis on how the performance of the business model can be improved. It focuses on one or more organisational objectives and details specific strategic initiatives that describe how that improvement is to be actioned and who is to be responsible for their delivery. 

The terminology involved depends on the management methodology being employed (e.g. Balanced Scorecard) but most methodologies will show the relationship between the action and the objective being supported as a ‘Strategy Map’.   

Strategy Model Metrics 
The sets of measures associated with strategy includes: 

  •  A set of targets that determine the improvement to be achieved for each supported objective.( 

  • The resources that will be required to implement each associated initiative (

  • The status through which the implementation of initiatives can be monitored.( 

  • Any business assumptions that were made when agreeing on the initiatives and the value of an improvement.

4. Resources 

The third element of the framework relates to the resources (money, people, assets) that the organisation has at its disposal, with financial resources often being the focus of a budget. 

These resources should be allocated to both sustaining the business model and in ensuring that the agreed strategic initiatives are properly resourced at the right time. 

5. Management Processes 

The final area of the framework are the organisation’s management processes that direct and control the way performance is planned, resourced, implemented and monitored. 

These are typically seen and often implemented as the six distinct processes of Strategic Planning, Tactical Planning, Financial Planning, Forecasting, Management Reporting, and Risk Management. 

However, on closer examination, these processes consist of a number of interconnected activities that only together form the basis for managing performance. Consider the following schematic: 

Even within each activity, there are interconnected tasks that each department has to perform, in a specific order and at specific times. 

For example, Budgeting may start off with the setting of a high-level goal to which sales will decide on how this will be delivered throughout the year. To do this they may need to work in collaboration with marketing and production. 

Once this has been completed, other areas of the organisation can start allocating resources that fit in with the sales and marketing plan. 
There are three important things to bear in mind when designing processes: 

  • Although these are often seen as discreet processes, in reality, they are each comprised of multiple activities that have strong links with activities within other processes.
  • For effective performance management, none of these processes can be left out.
  • In today’s volatile business environment these activities need to act as a single continuous 
As a consequence, what goes on within these processes and how they are interconnected will determine whether performance actually gets managed.

6. The Role of a Technology Solution 

As with a car, these four components need to be combined and operated as a single technology solution. It needs to support decision-making through the total integration of driver based business modelling (the engine) and strategy improvement plans (visual indicators showing the intended direction) with organisational resources (the fuel), all controlled through management processes (the pedals and steering wheel).

None of these components can be run in isolation - the degree of integration will determine how ‘smooth the ride’ will be. 

Around this central CPM system will be a range of BI analytical applications that provide insight into particular aspects of each component. This insight is used to formulate plans to improve the operation of the business model. 

The role of management reporting is to bring all relevant information together in context – i.e. to link strategy with the business model and resources, in a format that’s transparent and usable to motivate the many people involved to make the best-informed decisions. Those decisions will typically lead to altering the business model; modifying or developing new strategic initiatives; and where necessary, the re- allocation of resources. All of which is performed under the control of management processes.        


7. Implementing the Framework 

Performance management is all about taking decisions on the operation of both the business model and any associated strategy improvement initiatives. What goals should be set? What things have to be done to achieve those goals? How much will it cost? How much did it cost? What will it cost in the future? Is the outcome worth it? What changes should be made? Why has a past change been agreed? And so on. 

These decisions are typically made through a series of activities based on information that is presented to a user. 

Therefore, when implementing the CPM framework three things are necessary: 

  • The structure of the business model that holds information on its performance and the impact of strategy.
  • The associated workflow through which it gets updated and monitored.
  • The data entry screens and reports are given to users that directly supports the decisions to be made 
The next sections takes each of these in turn.

The full text is available for registered users. Please register to view the rest of the article.
to view and submit comments
Data Driven Planning: The 7 Key FP&A Models

By Michael Coveney, Analytics Thought Leader and Author

In this article, I want to make the case for data driven planning to describe the 7 key FP&A models that every organisation needs to plan, resource and monitor business performance.

Seven Key FP&A Models

Key planning questions

From a planning and review perspective, there are 7 key things that management needs to know about its business processes, each of which can be assessed in a range of analytical models:

  • How efficient and effective are the organisation’s business processes? (Operational Activity Model)
  • What trends are ‘hidden’ in the detail? (Detailed History Model)
  • What long-range targets should be set given where the market is heading? (Target Setting Model)
  • Where is the organisation heading if it continues with its current business model? (Detailed Forecast Model)
  • What could be done differently to better meet long-range targets and how much would it cost? (Strategy Improvement Model)
  • What choices/risks do management face and what would be the impact on corporate goals? (Scenario / Optimization Model)
  • How much funding is required to implement the plan and where will it come from? (Cash / Funding Model)

The models that answer each of these questions have different content, structures and are used by different people at different times.  However none can be omitted or ignored, and all need to operate as a single, data-driven management system.
From a planning systems point of view, this network of models can be visualized as follows:

Schematic overview of the 7 key models required to manage performance

As can be seen, these models are fed with data from internal systems such as the general ledger, and from external sources such as market information, along with data supplied by end-users. Whether these models are separate entities will depend on the size and complexity of the organisation.  Some may be combined, while others may need additional supporting models to enable them to function effectively.  For now, we will consider them to be separate but linked models, which from a user view operate as a single system. 

1. Operational Activity Model

The Operating Activity Model (OAM) is central to organisational planning that, as the name suggests, has a departmental activity focus.  Its purpose is to monitor business processes with a range of measures that allows management to evaluate their efficiency and effectiveness.
In particular, it can be used to:

  • Compare and contrast resources, workload and outputs both now and in the past
  •  Assign budgets for ‘business as usual’, i.e. assuming that there are no strategic initiatives 

The model holds different versions of data, some of which flows from the other planning models.  These versions include:

  • Target – contains the high-level goals set during the strategic planning process
  • Budget – contains the allocation of resources for the current year/period.
  • Forecast – contains the latest ‘best estimate’ of future performance for the next couple of months
  • Actual – contains past results

The model is multi-dimensional in nature and uses ‘attributes’ that allow measures to be assigned to specific business process activities and that categorizes them as being:

  • An Objective – these define what the organisation is trying to achieve in the long-term 
  • A Business Process Goal – these measure the success of the organisation’s core business processes and support activities that directly lead to the achievement of objectives
  • An Assumption - these monitor key assumptions made about the prevailing and forecast business environment that relate to the value set for the Business Process Goals
  • A Work measure – these describe the volume (and sometimes the quality) of work performed by a particular department.   e.g. the number of mailings sent out by the marketing department as part of its lead generation process
  • An Outcome measure – this measure what an activity should directly achieve, e.g. the number of people that respond to a mailing 
  • A Resource measure – these track expenditure that flows out of the organisation.

By using these attributes, the model is able to display data by the department but in relation to activity, outcome and resources used.  Below is an example of the types of report that can be produced. 

The first report shows the corporate objectives and business process goals for a selected period.  This contains a mixture of outcome, work and resource measures for both the budget and actual performance, as well as for last year.  Icon indicators are used to display whether results are getting ‘better’ or ‘worse’ than target. 

Sample report showing Corporate Objectives and how they are supported by business process goals.

The next report shows outcome, work and resource measures for a selected department.  As with the last report, actual performance is contrasted with the budget, while the end of year forecast is compared to the annual target.  From this management can assess the relationship between workload and outcomes to judge whether the focus is on the right activities.

Sample report showing department work, outcome and resource usage

By using attributes as a filter, the above report is able to automatically display the appropriate measures as they apply to the selected department.  

These two reports just touch the surface of what can be displayed from the OAM.  Interestingly, most organisations have much of this data already, although it is typically shown in separate budgeting and scorecard/dashboard reports, without making a connection between them. When treated in this way, the data can’t be used to model organisational value and so much of its worth is lost.

2. Cash / Funding Model (CFM)

Closely linked to the OAM is the cash/funding model (CFM) that is used to assess the organisation’s need for financial resources. Some of those resources will be used to support operating expenses, and others will be required for capital investment or strategic initiatives. This model is linked to the operational activity model (OAM) that contains budgets and forecasts in order to predict future cash flows.  It then goes on to help management assess the best source for any cash shortfalls.

Although it is true that most internal financial systems hold data relating to the flow of cash, what they do not allow is for management to model the data from a planning point of view.  For example:

  • to see a revised cash flow based on new supplier credit terms or a change to customer payment profiles; 
  • to consider the cost of funding an increase in production capacity to meet the projected demand for new products; or 
  • to assess the impact on resources by outsourcing a particular function.

Similarly, financial systems do not hold the key assumptions that affect cash flow. For instance, inflation has a major impact on cash resources, yet the underlying data supporting any inflation assumptions is not contained within those systems.

Modelling cash flows and balances require different sets of information, as shown below:

                               Cash / Funding model content

The dotted line indicates information stored within the CFM, while the bold lines indicate the data flows from other models in the planning framework. Data held can be summarised as follows:

  • Customer and supplier payment terms. The CFM contains details about each major supplier and customer where the cash flow effect is to be calculated. Depending on how payment terms are defined (for example, in weeks or months), the time intervals in this model may be at a shorter increment than that of the OAM.
  • Cash supply. Cash is modelled for budgets and forecasts. The supply side of cash is taken from the OAM where the level of detail allows individual supplier or customer movements to be identified so they can match up with the appropriate customer details.
  • Cash demand. Similarly, the demand side for cash is also taken from the OAM and takes into account all operational expenses, which for a manufacturer would include the supply of raw materials and manufacturing costs. It also includes any cash flows that arise in relation to capital expenditure. As with supply, these outflows are at a level where they can be linked to the payment profiles held within the CFM. 
  • Net funding requirements. Rules within the CFM are used to ‘time-shift’ the imported cash supply and demand data into the time periods in which cash will flow in and out of the organisation’s treasury bank account(s).  To this, other cash consumers and income streams not covered are added. This may include items such as interest payments and dividend accruals. These details are entered directly into the CFM. By subtracting the demand for cash from the supply, management can review the financial resources required.

To address any cash shortfall, or to reduce the amount of borrowings, budget and forecast data within the OAM can be reassessed to see which activities could be changed. The model also allows management to gauge the impact of changing customer and supplier payment terms. Assuming this has been done, the model can now be used to assess how any cash shortfall should be financed with the two obvious financing sources being debt and equity.

When reporting actual results, much of the data within the cash flow model will be loaded directly from the underlying transaction systems, so there is little need for modelling other than to produce a comparison between budget and forecast versions.

3.  Detailed History Model (DHM)

The role of the Detailed History Model (DHM) is to back up the Operational Activity Model (OAM) described in the last blog, when comparing actual results with budget.  The DHM has a much lower level of detail than the OAM and supports investigations into past performance. This will almost certainly include income and resources, as these will be made up of transactions held within the general ledger. Some of the workload and outcome measures may also have further details, which can be used to analyse business process activity.

There is likely to be more than one DHM, with each focusing on a specific area of performance such as revenue or production costs.  However, it is not desirable to create DHMs for every measure, as this could distract management from what is important. Instead, DHMs should be created for those measures whose values play a significant part in either directly resourcing or monitoring a business process.

When defining a DHM, the question should be asked, ‘What information do I need in order to understand the actual results being presented in the OAM?’  The answer determines the level of detail, the analyses that are required, and the type of history model that will meet those needs.

DHM’s can be of different model types that include: 

Transaction data set. These are tables of data that can be queried and summarised. An example of this type could contain the general ledger transactions behind each account code. These would be loaded from the General Ledger (GL)  on a regular basis and could consist of date, department, account code, supplier, and amount. Capabilities within the DHM would summarise this data by department, month, and account codes that are then fed into the appropriate place within the OAM.

The DHM could then be to support expense queries. For example, from a variance in the travel budget, a user would be able to drill down into the supporting DHM to see the transactions that made up the actual result. They could then issue another query that extracts transactions for a prior month to see if any expenses had been held over and hence had caused this month’s variance.
As with the other types of DHM, the ease of use and capabilities provided to an end user will depend on the technology solution being used. As a minimum, this type of DHM should support the following examples:

  • Filters.  E.g. list all transactions making up a particular account code.
  • Summaries. E.g. total all transactions for a particular account code and over a selected period.
  • Sorting and ranking. E.g. show the top 10 departments as ranked by travel expenditure.

Multi-dimensional model. This type of DHM allows users to produce cross-tabular analyses. Data is stored and referred to by its business dimensions. Users then have free access to the way in which data is presented, which can incorporate charts, additional calculations, and colour-coded exceptions. Examples of this type of model include sales analyses that could include types of customers, products sold, discounts provided, returns, and shipping costs.
Unlike the transaction data set, a multi-dimensional model is able to provide the following:

  • Multiple views of the data. E.g. show sales revenue by product and customer, customer profitability, returns by product and location.
  • Trends. E.g. calculate a rolling 12-month average and show this by month for the current year versus last year.
  • Exceptions. E.g. show all customers whose year-on-year growth has been negative.

Unstructured data model. This final type of model provides support for non-numeric data, such as notes, news reports, social media discussions, and competitor product videos. By linking these into the OAM, qualitative information can be provided that can make a substantial difference in the way results are perceived.
For all the DHM types shown above, a security system is required that will automatically filter out data that the user is not allowed to see.

4. Detailed Forecast Model (DFM)

Detailed Forecast Models (DFM), like the DHM, are typically used in conjunction with the OAM to collect forecasts that operational managers believe they will achieve in the short term. This can include a range of measures including workload, outcomes, and resources.

Although the OAM can collect forecasts at a summary level, there are measures that benefit from having this at a more detailed level. For example, revenue for a manufacturer can come from a range of customers and products, each of which has their individual profitability profile. As a result, the product mix can have huge implications on total revenue and costs. Therefore, to predict profitability with any degree of accuracy requires detailed knowledge of what is being sold, its volume, and to whom.

Similarly, sales of high value items or those that relate to a project are often dependent on timing. In these cases the sales process may be long and when the business is won, the resultant impact on costs and revenues in a particular time period can be significant. Without knowledge of the detail, it is easy to jump to the conclusion that an over or underperformance is exceptional rather than expected.  For this reason, collecting information concerning the sales order pipeline and using this to populate the sales forecast not only improves accuracy but also provides insight should any variances occur.

As with DHMs, different measures can have a wide range of supporting detail and so there are likely to be multiple forecast models where each has a focus on a particular measure.  Again, not every measure warrants its own forecast model. Ideally, they are only created for measures where the underlying mix of detailed transactions can have a large impact on results when compared to plan.

Providing detail behind a forecast so that informed assessments on accuracy can be made 

DFMs will typically hold just a forecast version of data, as actual results will be held in the detailed history model. (Remember, we are using the word model in a logical sense; the actual implementation may combine these into one physical model.)  For some measures, data may exist in another system (for example, many companies use SalesForce.com to collect sales information). If this is so, then the DFM may simply be a place where the latest data is stored that is then cleared out and repopulated each period. Alternatively, the DFM may be a system in its own right that is used to hold and track forecasts.

DFM’s can hold a range of data, not all of which is numeric.  For example sales forecasts may include the following fields:

  • Date that the sales forecast was entered
  • Region responsible for the sale and where any revenue will be credited
  • Sales executive involved
  • Company being sold to
  • Sales type (for example, whether the sale is to an existing customer or a new prospect)
  • Product(s) being sold
  • Value of the order
  • Date contract is due to be signed and revenues recognised in the P&L summary
  • Percent chance of the deal going ahead
  •  Any notes to describe the current situation

As with DHM’s, data within a DFM can sorted, summarised and reported. For example, show all sales due in the next three months ranked by the percentage chance of them being signed. This enables management to look in detail at a forecast so they can form their own opinion as to what could happen and to take remedial action should they fall short of what is expected.

As an option, a sales DFM could apply the per cent chance measure to the value of each sales situation to produce a modified forecast value within the OAM, or the OAM could contain two measures—one holding a value that assumes all sales opportunities will materialise as held, and the other using the per cent chance. This provides a range of values that could be used to assess future performance.

It is also worth storing prior forecast versions so that over time, a picture can be built up on the reliability of forecasts. For example, which sales people are able to forecast with an accuracy of 5 per cent three months in advance? Which measures produce the most variability when viewed six months in advance? 

Knowing how trustworthy a forecast is can help determine which measures need regular inspection and the level of caution required when making decisions based on them.  Also, if managers are aware that forecasts are being monitored closely, then they are more likely to pay attention to the values they submit, which in turn are more likely to be trusted.

5. Target Setting Model (TSM)

The Target Setting Model (TSM) is a mathematical model that allows management to simulate different business environments as well as the way in which it conducts its business processes.  Its purpose is to generate target values that will challenge the organisation as to what its performance could be in the future.

The TSM typically relates the outcomes of organisational business processes (for example, products made, new customers acquired, and customers supported) to long-term objectives and resources. In many ways, it is similar to the Operational Activity Model (OAM) described in blog 3, except its rules are used to generate targets from a range of base data. This is also known as driver-based modelling. In effect, there are a few independent variables, such as forecasted unit sales volume, which are driven by dependent variables (e.g. price, material unit cost), which are based on assumptions about the business environment (e.g. market size and growth).

Measures for these models can be selected by taking long-range targets and determining what drives their value.  The answers to these are then subject to the same question and so on until a base ‘driver’ is encountered, i.e. a measure whose value determines the targets it supports.

More sophisticated models recognise constraints, such as production volumes, the impact of discounts, late delivery penalties, or that more staff will be needed at certain levels of sales. They also recognise that there is nearly always a time lag between the driver and the result it creates. 

It should also be noted that these models only work for those measures that can be directly related to drivers, such as costs and revenues. Other data, such as overheads, will still need to be included to produce a full P&L summary.

Sample relationship map on what drives sales growth.  Measures on the right-hand side are drivers.

Because of their simplistic nature, driver-based models are not able to take into account unpredictable external influences, such as the unexpected market growth or changes in government legislation that impact taxes. This is where versions come into play. To see the impact of uncontrollable influences, the TSM is set up to hold a variety of scenarios where management can re-run the calculations with different driver values that simulate changing assumptions. For example, the model can be run with different sales conversion rates or unit costs, each of which will generate a new version of the P&L summary. These can then be displayed side-by-side so management can see the impact of each change. 

The aim in doing this is to allow a range of options to be evaluated concerning the future. These options will revolve around business drivers, which, if based on business process outcomes, will cause management to rethink how these are conducted and what could be improved. The end result of the TSM is a scenario that management believes will give them the best outcomes for the available resources. These values are then used to set top-down targets within the OAM that can be referenced by individual departments during the budget process.

6. Strategy Improvement Model (SIM)

The Strategy  Improvement Model (SIM) is used to evaluate how the current performance of an organisation as forecast in the OAM (‘business as usual’) can be transformed into one that supports the targets set by the TSM. The model allows managers to propose initiatives that can then be assessed, approved or rejected for implementation. Initiatives could involve improvements to current operations, such as replacing old machinery, or something entirely new, such as developing a new range of services or entering new geographic markets. In both cases, initiatives typically represent a set of activities that are not part of current business processes. 

From a logical point of view, the SIM consists of two sets of data linked to the OAM where ‘business as usual’ is kept.
Relationship between initiatives and ‘business as usual’

The first part of the model is where managers propose initiatives that are linked to business process goals, departmental structures, and resource. Here initiatives can be reviewed, assessed, and gain approval.
When an approved initiative becomes ‘live’, its set of activities and associated data are transferred into the OAM, where it is kept separate from existing operational data. However, the OAM allows the accumulation of resources and other measures to give a total ‘business as usual’ plus ‘strategic initiatives’ position.

This is achieved by defining a new dimension in the OAM for strategy, which is made up of the following members:

Total strategy. This is a consolidation member that accumulates ‘business as usual’ data with ‘total initiatives’ data.

    - Business as usual. This member contains all of the data for current business processes, but without applying any strategic initiatives.
    - Total initiatives. This is a consolidation member that contains the accumulation of data from its members; that is, the individual initiatives.

  • Initiative 1. This contains the data for a selected initiative as transferred from the SIM.
  • Initiative 2. This contains the data for a second selected initiative, and so on.

Keeping initiatives separate allows them to be monitored individually so management can keep a watchful eye on their implementation and resource usage versus expected benefits. Too often, initiatives are assumed to be responsible for an improvement in performance when no attempt has ever been made to actually measure whether this was true or whether the costs involved were worthwhile.
Linking the SIM to the OAM helps organisations to:

  • Accurately define ‘business as usual’ (or baseline) performance of the current organisational business processes.
  • Capture plan versus actual cost of strategy implementation and the benefits being realised.
  • Provide a transparent way of assessing priorities in the areas where performance improvement is most needed.
  • Avoid vague claims or estimates for initiatives, as the SIM requires clarity.

As time passes, it should be possible to re-plan, suspend, delete, or select new initiatives as required. Should an initiative be suspended, it can be moved back to the SIM until required at a later date.

7. Scenario / Optimization Model (SOM)

The last model in the planning framework is associated with Risk Management and enables managers to assess the impact of unexpected change and how it impacts corporate goals.  In the book ‘Best Practices in Planning and Performance Management’, author David Axson comments that  “Planning is not about developing a singular view of the future:  one of the most valuable elements of any planning activity is the ability to factor in the impact of risk on assumptions, initiatives and targeted results.”  He went on to say  “A scenario is a story that describes a possible future.  It identifies significant events, the main actors and their motivations, and it conveys how the world functions.”

As with DHM and DFMs, there may be more than one SOM.  For example, when balancing manufacturing costs with sales forecasts, some organisation’s employ sophisticated production models that determine which machines should produce which products and as a result what materials need to be ordered.

Similarly, when looking at the impact of a rise in commodity prices, it would be beneficial to assess a range of price values and to then compare the cost outcomes that these would generate.  From this management can then decide on how they would respond. For example, they may want to evaluate changing the current business structure or implement a new initiative.

The aim of the SOM is to allow management to ‘play’ around with different scenarios, each of which is documented as to the assumptions made about the future business environment and the change that could be made in response.  These are the presented back as a ‘side-by-side’ comparison from which decisions on the value set by the TSM can be evaluated, or what adjustments may be required to the current budget in order to keep the original plan on track.

The full text is available for registered users. Please register to view the rest of the article.
to view and submit comments
Four Steps Towards Analytic Maturity

By Michael Coveney, Analytics Thought Leader and Author

The volume of data available today is staggering. It is estimated that every 60 seconds around 1,820 Terabytes of data will have been created, 700,000 Google searches performed along with 98,000+ tweets and 11 million instant messages. Of course, not all will be relevant to your organisation, but if data represents the ever changing requirement of our customers, shouldn’t we be interested? Business Analytics provides the only way to quickly and effectively sift through an ever-increasing mountain of data to highlight hidden trends and nuggets of information that could be vital to survival and growth.

There is no point on aimlessly analysing data in the hope that something will jump out at you.  It won’t and all that you will do is waste vast quantities of time and effort.  Like any search, there must be an objective and a plan to reach that objective.  This is where a mature approach to analytics comes in.

Stage 1: Review existing BI/analytic needs

The first step is to look at your current use to see if they cover the key questions in the business:

  • What actually happened?
  • How efficient and effective are our business processes?
  • What is likely to happen if we carry on as we are?
  • Where should we be aiming given where the market is heading?
  • What could we do differently and how much would it cost?

This set of questions will almost certainly require different models (see my blog on 7 Key Analytic models).  Check what you have and note which areas are weak of non-existent.  For each weak area, ask yourself what would be the value to the organisation if you knew the answer.  You may want to ask colleagues/senior management the same question, which could be defined in terms of the threats and opportunities of ‘not knowing’.

Stage 2: Focus on the area with the most impact

From the above, take one area that has the biggest potential on improving performance (or mitigating disaster) and determine what data would be needed to provide the answer.  Remember it’s not about what data you have but what you need.  
Once you’ve done this then go and see what data exists, making a note of where it is, the cost of acquiring it and, if not available, how to get a reliable estimate.  Knowing the status/cost of crucial data is a key element in creating a strategic approach to business analytics.  Just because you have data doesn’t mean it is useful – it could just be a distraction from what you really need to know.

Stage 3: Gain experience in using a modern BI/Analytics system

Business analytic systems have changed tremendously over the years.  Today, most systems can analyse huge amounts of disparate data, quickly and with little knowledge of IT systems.  When evaluating a potential system keep in mind the types of analyses that you’ll need to answer the key business questions.  Then try out the products capabilities that support those analyses on a sample set of your data.  Check it for usability, it’s collaboration potential with other users, and how it links into planning.  The cost of acquiring, developing and supporting an analytic system should be placed in context of the benefits that will be obtained.

Stage 4:  Create a Business Analytics strategic plan for the organisation.

Armed with the above information, you should be able to create a plan that outlines the development plan for business analytics throughout the organisation.  Analytic models are never static and will always require tweaking or re-development.  That’s because the data being analysed will generate new data requirements and analyses that will be needed to move forwards. 

A good way forward is to establish a group of people to monitor the impact and potential of business analytics.  People that understand how the organisation functions, its strategic goals and have up to date knowledge of the latest development in analytic systems. An ideal place for this group is within the FP&A department

The article was originally published on the  prevero Blog

The full text is available for registered users. Please register to view the rest of the article.
to view and submit comments


Author's Articles

July 31, 2019

In December 1999, Gartner introduced the concept of Corporate Performance Management (CPM), which they defined as the “... the processes, methodologies, metrics and systems used to monitor and manage an enterprise's business performance”. 

June 18, 2019

These notes were made during the 9th meeting of the FP&A Circle in London. The notes are a mixture of comments and thoughts made by those who presented the case studies.

May 16, 2019

These notes were made during the meeting of the FP&A Board on 16th May 2019 in London.  They are a mixture of comments made by attendees and thoughts of those who presented case studies.

March 15, 2019
FP&A Tags:

These notes were made during the 22nd meeting of the FP&A Board on 7th March 2019 in London.  They are a mixture of comments made by attendees and thoughts of those who presented case studies.