- Who we are
- Media Centre
- Opportunity Now Overview
- Race for Opportunity Overview
- ON The Campaign Aims of Opportunity Now
- RfO The Campaign Aims of Race for Opportunity
- Diversity Leadership Boards
- ON Leadership Board
- RfO Leadership Board
- Membership ON & RfO
- Members
- Impact Opportunity Now
- Impact Race for Opportunity
- FAQ on BITC Diversity Campaigns
- What we do
- Take action
- Take action
- research
- The Business Case for Diversity
- ON Balancing Boards
- ON Out of Office
- ON Fit for the Future
- ON Inclusive Leadership
- ON Leadership for Change
- ON What Holds Women Back ?
- ON Women's Networks: Making Good Connections
- RfO Aspiration and Frustration
- RfO BAME Women
- RfO Race in Higher Education
- RfO Race to Progress
- RfO Race to the Top
- Diversity Integration
- Line Managers and Diversity
- Resources
- Take action
- Take action
Section head
Guidelines for using non financial performance measures
Increasing numbers of organisations use performance measures such as employee satisfaction that are not financial but which they believe can ultimately affect profitability and efficiency. However a study reported in the Harvard Business Review in 2000[1] based on field research in 60 companies reported that many fail to use these measures properly and only a few realise their benefits It concluded that most companies have made little attempt to identify areas of non financial performance that might advance their chosen strategy. Nor have they demonstrated a cause-and-effect link between improvements in those non financial areas and in cash flow, profit, or stock price. Many had adopted off the shelf measure models wholesale, with little attempt to discover which activities really add value. The study identifies that companies often make 4 basic mistakes:
Failing to link measures to strategy
Few organizations build plausible cause-and-effect relationships that may exist between the chosen drivers of strategic success and outcomes.
Not validating the links
Even those companies that create causal models rarely go on to prove that actual improvements in non financial performance measures affect future financial results
Not setting right performance targets
Target setting is inherently difficult because it always takes a while for improvements in a driver of corporate performance to produce improvements in the performance it’s meant to affect. However, if a company can reasonably estimate when the non financial performance improvements will pay off, and by how much, it can set lower interim financial goals, which can subsequently be adjusted upwards
Measure Incorrectly
At least 70% of companies in the study employed metrics that lack statistical validity and reliability. Business units within the same company often used different methodologies to measure the same thing. Most businesses had trouble developing performance measures for things like leadership or maintaining supplier relations. Many of the companies that did try to track more qualitative measures ignored them when making decisions because of a lack of trust in measures that were unproven and therefore viewed as subject to favoritism and bias.
The study outlines six steps for successful measurement.
Develop a causal model.
The first step is to develop a causal model based on the hypotheses in the strategic plan to show what areas are expected to improve as the result of commitments to particular courses of action, and then show how those improvements should affect long-term economic performance. Successful companies choose their performance measures out of the hundreds available on the basis of causal models, also called value driver maps, which lay out the plausible cause-and-effect relationships that may exist between the chosen drivers of strategic success and outcomes.
Pull together the data.
Most companies already track large numbers of non financial measures in their day-to-day operations. So to avoid going to the trouble of collecting data that already exist, companies should take careful inventory of all their databases.
Turn data into information.
There are many statistical methods for testing the causal model. Most companies have experience using correlation analyses and multiple regressions in their market research and quality improvement efforts
Continually refine the model.
Causal modeling, if used at all, is often used only once. But reassessment of results should be ongoing and regular. Beneath the proven drivers of performance lie the drivers of those drivers. Since a business can’t ever know whether it’s gone deep enough, the effort to uncover these drivers must never cease.
Base actions on findings.
Ultimately, the conclusions drawn from data analyses must be used in decision making if non financial performance measures are to improve financial results.
Assess outcomes.
The final step in the performance measurement process is determining whether the action plans and the investments that support them actually produced the desired results.
[1]“ Coming up short on non financial performance measurement” Harvard Business Review November 2003
