Expert Opinion

This Management Brief presents an outline of Corporate Performance Management (CPM) systems and provides an overview of the various components and benefits associated with CPM.

The key benefits of CPM systems are greater speed, improved accuracy and simplified auditing processes. CPM systems have the capacity to eliminate accidental or “other” errors from distorting an organisation’s record systems. Michael Burns [1], president of 180 Systems, Canada, writes that CPM systems enable compliance with the stringent demands contained in new legislation through the provision of powerful consolidation processes, financial reporting and work flow management, and that this leads to better control/approval procedures and, importantly, eliminates the need for cumbersome spreadsheet-driven processes.

Automated CPM environments are made up of various application modules, see figure 1 above, adapted from Viaene and Williams [2] of the Vlerick Leuven Gent Management School, in Belgium:

The three steps shown—Monitor, Analyse and Report—represent a natural sequence of information management that is used by many organisations. This is followed by more complex, multidimensional analysis in the search for causal relationships.

Viaene and Willems cite Gartner’s definition of CPM, stating that it is “an umbrella term that describes the methodologies, metrics, processes and systems used to monitor and manage the business performance of an enterprise.” Greater transparency is now demanded in the way that organisations are managed, and CPM is an enabler that promises to meet these expectations. For example:

• The organisation’s objectives would be translated into critical success factors and well-chosen key performance indicators (KPI).
• A balanced set of performance metrics—or Balanced Scorecard—would be used to link with the organisation’s strategy.
• “Near real-time” pertinent management information would be effectively filtered and made available to the managers of the organisation.
• Value-adding components would be streamlined throughout all parts of the enterprise and have an ultimate focus on customers.

Important components of CPM systems are:

1. A Data Warehouse, which is the centrepiece of all CPM implementations. The data warehouse contains enterprise-wide, consolidated and standardised data, which has been grounded upon agreed definitions and business rules.
2. Scorecards and Performance Dashboards, which capture critical performance information in one location and in formats that can be easily assimilated. Dashboards tend to be used for monitoring operational performance, while scorecards monitor the status and evolution of tactical and strategic objectives.

CPM and Continuous Improvement

According to Bruce Silver [3], an independent industry analyst, the ultimate goal of CPM is “the optimisation of business performance through continuous improvement with key performance indicators being aggregated and displayed in real time using performance management dashboards and reports”. CPM software suites support high-level strategic metrics, “drill-down” analytics and the ability to create alerts where results deviate from defined performance targets. CPM implementations have enabled new management philosophies to be created, calling for organisations to document, analyse and measure activities in terms of their end-to-end processes. These processes often cross functional boundaries, and diverge from the traditional discrete functions of marketing, sales and customer service.

Max Kay [4], founder of KCI Computing, states that the need for the integration of business performance tools has brought about a “harmonic convergence” that has not been seen previously in the CPM industry. Historically, the focus of management tools has been upon the development of financial management tools relating to budgeting, financial consolidation, modelling, reporting, and online analytical processing. However, users now need to juggle multiple products, databases and interfaces; for this reason, consistency and integration have become important, central issues.

As the quality of CPM tools increases, users are demanding the removal of the traditional barriers that have separated financial planning/analysis from operational planning/analysis. Techniques that were once the exclusive domain of finance and accounting experts now pervade many organisations that are seeking to become more productive and competitive. Key performance indicators and balanced scorecards generally include both financial and non-financial information. They have become common management tools that form the foundations of performance assessment.

CPM products are now expected to have the following attributes:

1. Integration: Using common data and metadata along with user-friendly interfaces.
2. Flexibility: Using a variety of data sources and views to meet the dynamic needs of the organisation.
3. Quality and Accessibility: Using accurately presented information with access to different CPM components, such as planning, budgeting, and reporting tools that are hosted on the same platform.
4. Navigability: Navigability of information from both inside and outside the Business Performance Management application.
5. Timeliness and Consistency: Timeliness and consistency of information.
6. Communication: Communication of targets and the strategic/tactical goals that are associated with these
7. Wide Usability: Enabling strategy, analysis and performance measurement to pervade organisations, and to influence the actions of management and staff at all levels.

Data Warehousing

Healthcare organisations are a good example of the increasing requirement for organisations to be able to manage large amounts of complex data. While advanced electronic health record systems have been implemented with fast response times for individual patient records, they do not easily support cross-patient analysis and reporting. Randy Thomas [5], an associate partner of IBM’s Healthlink division, states that there is a growing need for clinical, financial, and administrative analytics/reporting spanning a broad spectrum of business requirements. The problem of leveraging vast stores of clinical and other data cannot be solved by simply dumping it all into a giant data warehouse, as this unfortunately tends to create a data “landfill”.

Bringing together disparate data from multiple sources requires an underlying plan, one that is driven by the knowledge of how the data is intended to be used (i.e. the organisation needs to define a knowledge management process). The development of such a plan will typically take organisations three to four months to complete. A decision framework should then be designed, and this should comprise a set of “principles” that describe the needs and aspirations of the organisation in association with analytics. A road map would then be developed to guide the design, build, and execute process, which may run over several years, but will result in the construction of an orderly data warehouse appropriate to the goals of the organisation.

Data Warehouses Using Advanced Business Logic Improve Medical Claims

A large amount of complex paper work is associated with medical claims submitted by providers to health insurers and, according to Frank Marshall, Chief Operating Officer of MedSynergies in the United States [6], an average medical group will have more than 30 per cent of its claims denied on first pass, and approximately half of these claims will never be collected. The creation of a data warehouse with an automated workflow environment can radically improve this situation. Data warehouse technology has the capability to “thin slice” massive amounts of claims information into actionable reports, and to route these reports to specific decision makers while suggesting various appropriate actions. Using an advanced business logic engine, the data warehouse gets “smarter” with each additional claim filed, and can spot billing issues as they occur. Recent advances in analytical software have made it possible to amalgamate claims information into a centralised claims data warehouse. For example, a data warehouse has been implemented which managed claims information from approximately 1,000 healthcare providers across 23 states and contained some 7.3 million individual billing items. The business logic engine of a data warehouse enables rules to be applied throughout the process to maximise claims processed and minimise errors. Customised reports can also be used to determine if fee schedules are correctly aligned for optimal reimbursements. This can lead to significant amounts of money being saved on an ongoing basis.

Data Warehouse Trends

The growth of data warehouses is increasing exponentially, along with conflicting demands for the support of more users, increased query and data complexity, and more “right-time” information. This has brought many organisations to a crossroads. Richard Winter, president of WinterCorp in the United States, asserts [5] that these organisations are looking for answers to the following questions:

• Is their current architecture suitable for ongoing growth?
• Can they scale up economically within reasonable financial limits?
• Do they have access to personnel that are able to manage the complexity of a data warehouse?

The organisations fear that without suitable answers to these questions, they will be left behind by their competitors. Vendors also face challenging requirements, including how to:

• Increase the capability of ICT platforms to handle growing scale and complexity.
• Simplify operation, management and use.
• Incrementally adjust software pricing downward.
• Pass on hardware savings.

Balanced Scorecards

The classical Kaplan and Norton balanced scorecard has four dimensions:

1. Customer
2. Internal business processes
3. Innovation and learning
4. Financial perspectives.

These are often modified to suit the needs of the organisation involved. According to Deryl Northcott and Necia France, of the Auckland University of Technology in New Zealand [8], the following dimensions and associated measures were implemented by New Zealand hospitals (see figure 2, below):

The simplicity, balance, as well as the cause-and-effect relationships, have made this an attractive strategic management tool for New Zealand hospital administrators. The key performance indicators used for measurement purposes are of prime importance in connection with the effectiveness of the tool.

Balanced scorecards are perhaps the most widely used measurement framework found in business today. Unfortunately there are many examples of failed balanced scorecard systems. Sir Andrew Likierman [9], professor of management practice at the London Business School, emphasises that it is essential to measure the success of adopting a scorecard in order to (a) be able to determine if its impact can be improved, (b) ensure that problems are remedied, and (c) create an environment of credibility for further organisational initiatives. Likierman suggests the following important stages for constructing and managing organisational balanced scorecards:

1. Identify Measurement Problems:

• Clarify objectives – without a clear idea of what the scorecard is intended to achieve, it is impossible to define—let alone measure—any benefits
• Measure costs (including opportunity costs) and cost benefits.
• Identify a basis for comparison of the current situation versus conditions after the implementation of the balanced scorecard
• Account for the unexpected effects of implementation, which may arise due to (a) overconfidence when introducing the new technique or (b) to flawed design and implementation (unfortunately, a frequent occurrence with scorecards)
• Discover links between the measurement tool and performance – or see if benchmarks are able to be found

2. Take Action Before Starting the Implementation to:

• Identify all “monitorable” costs and benefits (i.e. not just numerical ones)
• Identify risks affecting costs and benefits, and make provision to manage them
• Where possible run a pilot implementation.
• Adjust expectations about what can realistically be achieved. If possible, do this on the basis of the organisation’s past experience relating to the introduction of new techniques.

3. Improve the Measures:

• Move from using input to outcome measures(as with outcome measures, it is possible to focus on true improvements)
• Learn from the experience of others (e.g. from literature, conferences, case studies or shared experiences)
• Establish milestones for anticipated costs, benefits and timing
• Recognise the limitations of quantitative measures – a number of measures will need tobe based on judgements
• Allow for flexibility, because unexpected events will arise that were not part of the original plan.

4. Mitigate Any Remaining Problems.

• Analyse the evidence and beware of spurious numbers (NB – certain measurement problems may not be able to be resolvable).
• Provide a good written commentary as part of the monitoring of all initiatives. The commentary should be realistic about the limitations of the measurements used, and take into account the length of time since the implementation began. The commentary should include a conclusion that outlines both quantifiable and unquantifiable elements.

Performance Dashboards

Performance dashboards are extremely useful for working with vast amounts of rapidly changing data that are received on a daily basis. Karen Schwartz [10], a specialist technology and business writer, points out that capturing this data is merely the first step towards understanding it, and that performance dashboards, or digital dashboards, can assist organisations to recognise, analyse and rectify issues quickly. Digital dashboards are automated panels that display up-to-date data, together with performance measures, using dials and gauges that indicate the status of the various measures. Usually managers can “drill down” from the displayed measures and locate detailed information. This can help them to make decisions and determine the root causes of problems. In support of this, Schwartz cites David Vandagriff, vice-president of business development at Corda Technologies Inc. Vandagriff states that “managers have told us over and over again that they are getting inundated with spreadsheets and database reports. The dashboard pulls the information out at a high level and lets a manager understand at a glance whether things are going well and where there are problems”.

Key Performance Indicators (KPI)

Effective metrics should be [11]:

1. Aligned with corporate strategies and objectives.
2. Owned by an individual or group, accountable for its outcome.
3. Predictive by measuring the drivers of business value.
4. Actionable by incorporating timely, actionable data to enable early intervention to improve performance.
5. Few in number by focusing upon a few high-value tasks.
6. Easy to understand i.e. straightforward and not based on complex indexes that users are unable to influence directly.
7. Balanced and linked by reinforcing each other, not competing or confusing.
8. Transformative through triggering a chain reaction of positive changes throughout the organisation.
9. Standardised by being based on standard definitions, rules and calculations, which enable them to be integrated into dashboards throughout the organisation.
10. Context-driven by putting performance in context through applying targets and thresholds that users can check for progress over time.
11. Reinforced by attaching compensation/incentives.
12. Relevant through being reviewed/refreshed periodically.

Kate Vitasek, managing partner of Supply Chain Visions in the USA, insists that metrics should be aligned to strategy, and the following table adapted from 5 Ways to Tie Your Benchmarks Into Corporate Strategy [12], compares various metrics in this regard (see Figure 3, below):

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