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This section presents a template for designing performance indica-tors. Completing this template ensures that organizations develop a sound and comprehensive understanding of each of their perform-ance indicators. This is important because it ensures that the data is consistently collected and interpreted. It eradicates the ambiguity, ambivalence, and inconsistency that we see far too often with per-formance indicators. If indicators are to become the basis for decision-making and learning, it is essential that everyone understands what these indicators mean, how reliable they are, where the data comes from, etc. The template presented here can be used to develop com-pletely new indicators or to develop a more comprehensive picture of existing performance indicators. Each aspect of the performance indi-cator design template is explained below and summarized in Figure 5.6 (see opposite).

䊏 Name – any performance indicator needs a name which should clearly explain what the indicator is about.

䊏 Strategic element being assessed – the value creation map has identified the different strategic elements (resources, core compe-tencies, and output deliverables). Which of these elements the indi-cator is helping to assess is clarified here.

䊏 Purpose – what is the main purpose of and reason for assessing performance of this element? Why is this indicator being intro-duced? Do we really need it? Is there any particular issue that is being observed and requires indicators? Is it to establish where we are at this point in time with any of our resources or competen-cies? Is it to establish a base line for our output deliverables? Is it to monitor progress and the delivery of our strategy? Or is it to test our assumptions of cause and effect relationships between specific strategic elements?

䊏 Data collection method – this describes the method by which the construct will be assessed and how the data will be collected. Here it is important to keep the purpose of the indicator in mind. Far 112 Managing performance in an enabled learning environment

too often the data collection method is an automatic response or a selection of traditional methods that might not be able to provide the necessary insights. Instead, it is important to consider the strengths, weaknesses, or appropriateness of different data collection

Name

Strategic element being assessed

Purpose

Data collection method

• Formula and/or scale

• Source of data

• Audience/access Identifies the audience, outlets, and access rights Identifies how often the indicator is reported

Identifies how the performance is presented (numerical, graphical, narrative formats) Identifies proactive notifications and workflows Identifies an expiration or revision date

Estimation of the costs incurred by introducing and maintaining this indicator

Description of the key purpose

Short description of how the data is collected

Identification of the scale used to assess performance

Identification of where the data comes from How often is the indicator measured?

Who is collecting and updating the data?

Identification of the person(s) or function(s) responsible for the measured element

Identification of targets, benchmarks, and thresholds for traffic lighting

Clear indicator name

Identification of what strategic element is being assessed (e.g. a specific resource, a core competence, one of the output deliverables)

Figure 5.6 Template for designing performance indicators

methods.³⁹ Here, the designer of an indicator should include a brief description of the data collection method, specify the source of the data, how often the data is collected, what scale will be used to measure it, and who is in charge of collecting and updating the data.

䊐 Formula and measurement scale – here the designer of the indi-cators identifies how the data will be captured. Is it possible to create a formula? Is it an aggregated indicator that is composed of other indicators? Here the designer also specifies if one of the fol-lowing scales is used: nominal (numbering of categories, e.g. foot-ball players); ordinal (determination of greater or less, e.g. street numbers); interval (determination of intervals, e.g. temperature in Fahrenheit or Celsius); and ratio (determination of equality and ratio in a continuum with a real zero, e.g. length, time, tempera-ture in Kelvin); or whether the indicator is not expressed in any numerical form.

䊐 Source of the data identifies where the data comes from. This ensures that the designer of an indicator thinks about the access to data. Is the data readily available? Is it feasible to collect the data? Will the data collection method, for example interviews with senior managers, provide honest information? Maybe differ-ent data collection methods could be combined?

䊐 Frequency of data collectionidentifies how often the data for that indicator should be collected. Some indicators are collected con-tinuously, others hourly, daily, monthly, or even annually. Here it is important to think about what frequency provides sufficient data for that indicator and how often is it feasible to measure.

Organizations might want to continuously track indicators for website usage since some of them might be readily available from the server reports. Indicators for employee satisfaction might only be feasible once or twice a year and need to be linked to the employee survey. However, some firms are experimenting with random daily satisfaction surveys to a subset of employees.

䊐 Data entry identifies the person, function, or external agency responsible for the data collection and data updates.This could be an internal person or function, or an external agency, since many organizations outsource the collection of specific indicators. This is especially common for indicators such as customer satisfaction, reputation, brand awareness, and employee satisfaction.

䊏 Ownership – identifies the person(s) or function(s) responsible for the management of the strategic element that is being assessed. This can be an individual employee or it can be a department.

䊏 Targets and performance thresholds – identify the desired level of performance in a specified timeframe (e.g. 5% increase of market 114 Managing performance in an enabled learning environment

share by the end of March next year) as well as the performance direction. Performance directions indicate at a glance whether it is better to exceed the planned target, hit the target value exactly, or whether it is better to stay beneath the planned value. Financial results or employee satisfaction are usually indicators where the

‘bigger is better’ performance direction applies (the bigger the number of performance achieved in this area the better). On the other hand customer complaints or harmful emissions are indi-cators where ‘smaller is better’ (the fewer customer complaints a company receives or the less a company pollutes the environment the better).

An example for ‘balance’ or ‘target is best’ would be quality indicators with SPC (Statistical Process Control) charts where there are upper as well as lower limits that should not be exceeded and it is best to hit the targeted tolerance range. Many firms use ‘traffic lighting’ to illus-trate the levels of performance. Here, the designer of an indicator would therefore specify the thresholds for red/underperformance, amber/medium performance, green/good performance, and sometimes blue/over performance. Here, it is also worth thinking about internal or external benchmarks; these can be derived from past performance, from other similar organizations or departments, or from forecasts.

䊏 Reporting – Here, the designer of an indicator identifies the way the performance indicator is reported. It identifies the audience, access restrictions, the reporting frequency, reporting formats and possible notifications and workflows.

䊐 Audience and access identifies who will receive the reports on this performance indicator, possible outlets or reports, as well as possible access restrictions. Indicators can have different audi-ences. It might therefore be a good idea to identify primary, sec-ondary, and tertiary audiences. The primary audience will be the people directly involved in the management and decision-making related to the strategic element that is being assessed.

The secondary audience could be other parts of the organiza-tion which would benefit from seeing the data. A possible ter-tiary audience could be external stakeholders.

This part of the design process would also look at possible reports (existing or new) in which this indicator would be included. The designer of an indicator should also consider access restrictions to this indicator. There might be reasons why the access to certain indicators is restricted to individuals, groups of people, departments, or outsiders.

䊐 Reporting frequency identifies how often this indicator is reported. If the indicator is to serve a decision-making purpose within the organization, then the indicator needs to provide timely information. The reporting frequency can be different from the measurement frequency. An indicator might be col-lected hourly, but then reported as part of a quarterly perform-ance meeting.

䊐 Reporting formats identify how the data is best presented. They should clarify whether the indicator is reported as, for example, a number, a narrative, a table, a graph or a chart.The best results are usually achieved if performance is reported in a mix of numerical, graphical and narrative formats (see also section on Reporting Performance Indicators). Considerations here also include the presentation of a data series and past performance. A graph con-taining past performance might be very useful in order to analyse trends over time and this could also include targets and bench-marks. Increasingly too, organizations use traffic lights or speed-ometer dials to present performance data.

䊐 Notifications/workflows identify proactive notifications and possible workflows. Workflows are predefined and automated business processes in which documents, information or tasks are passed from one person or group of persons to others.

Notifications are predefined and automated messages and involve the proactive push of performance data, messages or alarm notifications to predefined individuals or groups. For example, e-mail notifications or workflows could be automatically trig-gered if an indicator is updated or moves over a predefined threshold.

䊏 Expiry/revision date – indicators are sometimes introduced for a specific period of time only (e.g. for the duration of major projects or to keep on eye on restructuring efforts). The common practice is that a significant number of indicators are introduced once and collected for ever because no one ever goes back and identifies the indicators that are not needed any more. Other obviously tempor-ary indicators are introduced without giving them an expiration date; however, for those indicators a revision date should be set that allows the designers to review the template and check whether it is still valid.

䊏 Estimated costs – another aspect that should be considered is the costs of introducing and maintaining a performance indicator.

There is often an implicit assumption by many managers and meas-urement experts that creating and maintaining measmeas-urement sys-tems does not incur significant costs.⁴⁰ However, on the contrary, 116 Managing performance in an enabled learning environment

measurement is expensive, especially if the indicators are supposed to be relevant and meaningful to aid decision-making and learn-ing.⁴¹ Costs can include the administrative and/or outsourcing costs of collecting the data, as well as the efforts needed to analyse and report on the performance.

䊏 Confidence level – once the above aspects of an indicator have been addressed, it is time to think about the validity of the indica-tors. To what extent do the indicators enable us to assess the given strategic element? For financial performance, the confidence level would normally be high, since established tools are available to measure it. However, when we try to measure our intangibles, such as organizational culture, the confidence level would necessarily go down a peg or two. The assessment of the confidence level is sub-jective but forces anyone who designs an indicator to think about how well an indicator is actually ‘measuring’ what it was that it set out to ‘measure’. Organizations have different preferences of how to express confidence levels; some use percentages (0–100%), others use grades (1–5; or low, medium, high), colour codes (e.g.

red, amber, green), or symbols (such as smiley faces). In addition, it is suggested that a brief written comment is included to clarify the level of confidence.