The secrets of measuring and managing business performance

Twenty years after the introduction of the Balanced Scorecard, performance management expert Bernard Marr explains the differences between companies that merely compile data and those that thrive from it.
The secrets of measuring and managing business performance

Never before have managers had more data to ensure that they make the right decisions. Today, companies collect data and report on business performance so that managers can better understand how well the business is doing and to help monitor the delivery of strategic priorities and goals.

There is no shortage of performance data, key performance indicators (KPIs), management dashboards and “phone directory-type” performance reports. The big question: Does all this data really lead to better decisions?

Not necessarily. Many managers are drowning in data while thirsting for insights.

I thought it would be useful to understand whether there are any factors that differentiate managers who are happy with the benefits their performance management approaches deliver from those who are unhappy.

Earlier this year the Advanced Performance Institute, in collaboration with Actuate Corp., conducted a global study of more than 3,000 companies to answer some of these questions. We took the 20th anniversary of the Balanced Scorecard, one of the world’s most popular business performance management tools, as the impetus to understand the current state of play.

What we found was that while some companies were applying business performance management approaches very effectively to gain operational insights as well as strategic foresight, a large proportion of companies were dissatisfied with their efforts to measure and manage performance.

Based on the findings, we developed a business performance management (BPM) maturity model (see Figure 1) to show how different levels of maturity correlate with increased business benefits. Approaches at the lowest levels of maturity, where companies have little data, collect and report data in an uncoordinated fashion or produce lots of dashboards with little substance, generate no or low business benefits. The companies with the highest maturity levels and the highest business benefits are those that use the data to inform operational and strategic decision-making and to make predictions for the future.

BPM Maturity Model

An analysis of the survey results shows that the largest portion of companies fall into Level 3 maturity (about 25%), followed by Level 2 (about 15%). Levels 4, 5, 6 and 7 all have about 10% to 15% of companies. Few companies (about 5%) are at Level 1.

Considering the seven levels of BPM maturity before discussing the factors commonly found in companies with higher levels of maturity should enable you to assess how advanced BPM is at your company.

Level 1: No data

The lowest level of BPM maturity is where a company has very little or no performance data available to support management decision-making. Some small- and medium-size entities in traditional industries may fall at this level because they have been in operation for many years and have never created the systems to collect and report data.

Level 2: Data and facts

At this level, companies have some facts and data, but the collection and usage of these data are ad hoc, sporadic and unco-ordinated. This situation is much more common. In a world where data are abundant, and where companies often have to collect and report data for legal or regulatory purposes, the problem is not collecting and finding the data but exploiting them.

If a company fails to put in processes to co-ordinate the collection, analysis and reporting of data, it often leads to isolated and ad-hoc insights but little true decision support. Companies falling into this maturity level often create more confusion rather than useful and structured insights because the data are not generated regularly and in a systematic manner. At this level of maturity, there is some recognition that data can be useful, but the systems are not in place to collect, analyse and report the data in a meaningful way.

Level 3: Information

This is one of the most common levels of BPM maturity. Here, organisations have more structured approaches to collecting and reporting data. The data are also more relevant and allow companies to produce regular performance reports and dashboards to support management decision-making. While this might provide some useful information, the insights and support for decision-making are still limited. These companies recognise the importance of data to support decision-making but often collect the wrong data or have data-quality issues, so the data in their performance reports and dashboards look great but fail to generate useful insights.

Level 4: Operational insights

is the first level of maturity at which companies generate real value from their data. Companies on this level use relevant performance data in a co-ordinated fashion, and this is where they are used to generate new insights that improve operational decision-making. Here, companies recognise the importance of data to support decision-making. They collect, analyse and report operational performance data such as internal efficiency or quality performance data to improve and optimise the way they operate. However, the focus is on the operational aspect of the business, which means the scope is often the business unit or an operational silo such as production, supply-chain performance, finance, marketing or HR. At this level of maturity, the data are not aggregated up into a more strategic perspective, which can create information silos and a disconnect between strategy and operations.

Level 5: Strategic insights

This level of maturity is similar to the previous one. Here, companies clearly recognise the importance of relevant data to support decision-making and are able to gain insights from the data that allow them to make better decisions. The difference is that, here, companies collect, analyse and report strategic performance data such as high-level performance reports and board-level dashboards. This information is used to improve strategic decision-making, but companies are not linking it to operational performance management. However, the strategic insights are delivering slightly more business benefits than just operational insights, and therefore this is a higher level of maturity. The problem, however, is the same as with Level 4: Companies using performance data just to improve strategic decision-making — without linking it to operational decision-making — can easily create a disconnect between the strategic direction of the business and what operations delivers to achieve it.

Level 6: Strategic and operational knowledge

Companies that reach this level are able to use relevant performance data in a co-ordinated fashion to gain new knowledge that leads to both improved operational and strategic decision-making. Here, there is a recognition of the importance of performance data throughout the business, and it generates a high level of business benefits both operationally and strategically. Here, companies are able to create a tight link (both top-down and bottom-up) to ensure operational performance information feeds into strategic performance information and that the strategic performance insights feed into what operational performance data are used. The only difference between this maturity level and the highest one is the time focus and the level of analytics applied: Here at Level 6 most of the data are backwards-looking and reporting past performance rather than predictions of the future.

Level 7: Strategic foresight

At this level, companies use relevant performance data to make operational and strategic decisions and to develop strategic foresight and predictions for the future. But here, performance data are used not only to inform decision-making at all levels of the organisation, but also to understand what the future might hold. Predictive analytics, what-if studies and scenario-mapping are common practices among Level 7 companies. Level 7 companies know the value of data and exploit them to generate true competitive advantages and better decision-making in all areas of their business, every day. Here, evidence-based decision-making is part of the corporate DNA.

Seven success factors

The business performance management (BPM) maturity model will hopefully be useful for companies to assess their own level of BPM maturity and understand a trajectory for evolution and improvement. In addition to the levels of BPM maturity, we wanted to identify factors of success that companies with higher levels of maturity have in common. The analysis of our survey data allowed us to identify seven common success factors:

1  Buy-in and ownership

With any management initiative, if there is no ownership and buy-in, then the implementation is likely to fail or deliver very limited benefits. The same is true for BPM. The top team in a company needs to spearhead the implementation. However, what we find is that there is often buy-in at the top but little at the bottom of the organisation. This indicates that BPM is either seen as a top management initiative — often along the lines of “senior management is checking on us” or where the grass roots disagree with the measures and analysis performed.

To enable a successful BPM implementation, it is vital that companies create pervasive buy-in and communicate the need and reasons for measuring and managing performance throughout the organisation. A lack of buy-in at the grass-roots level is often the result of a lack of engagement in the design and communication of the BPM approach, as well as a lack of trust in the data quality or a lack of trust in how the data might be used. A closed-loop system, in which everyone understands the rationale of the BPM approach and has access to the data, will help to eliminate this problem.

2  Motivation for BPM

Having the right reasons to implement BPM is another key success factor. The most mature and successful implementations are those in which BPM is introduced voluntarily by the company to improve its decision-making and to generate new insights and understanding that drive performance improvements. Instead, if it is being introduced because of external needs to report (often the case in government organisations or highly regulated industries where central government or regulatory bodies force the reporting against targets), then there will be resistance. Involuntary reasons can also be internal — for example, internal quality departments or senior management teams are seen as forcing performance reporting and measurement. Here, voluntary beats involuntary all the time.

3  Integration of operational and strategic approaches

Traditionally, key performance indicators (KPIs) have been used by organisations on two levels:

  • Strategically — to monitor the execution of the strategic goals and objectives (eg, high-level KPIs based on the strategic objectives of an organisation such as financial performance or customer satisfaction); and
  • Operationally — to monitor and improve operational performance (eg, operational effectiveness metrics such as quality measures, waste levels, capacity utilisation or process optimisation metrics).

What many companies are struggling with is the alignment and integration of strategic and operational metrics. The operational measurement is too often still done without aligning it with the strategic measures. This can therefore create a disconnect between the strategic priorities and the operational priorities.

Organisations that generate higher levels of benefits are those that integrate a strategic and operational approach to BPM. This study finds that companies that use KPIs only to measure and report operational performance report low levels of benefits. Companies that have strategic KPIs but don’t align them with operational metrics also report low benefits. However, companies that integrate them and use strategic and operational KPIs and align them with strategy maps or mission and vision statements report the highest levels of satisfaction and benefits.

4  Integration of performance measurement and analytics

Another factor that is becoming a differentiator is the level of integration between traditional KPI measurement and analytics. While KPI measurement is more static with a focus on high-level indicators to monitor performance against high-level goals (the how well are we doing against our plan question), analytics are more dynamic, using wider and larger data sets to challenge the business (the what, why and how questions). Those companies that report that they combine approaches such as KPIs and Balanced Scorecard approaches with business intelligence and analytics generate more benefits in the form of richer and more comprehensive business insights.

5  Time-focus of BPM

Traditionally, performance data were used to report historic information (eg, financial performance of the last quarter, success of the last marketing campaign or results from a staff survey). More sophisticated approaches and the use of information technology allow companies to track performance much more in real time. Especially with the emergence of sophisticated predictive analytics tools, companies can now look into the future. Predictive analytics take past and present data and apply statistical models to them to predict future trends, behaviours, sales, etc. Examples include:

  • A telecom company uses past patterns as well as social media analytics to predict which customers are most likely to churn or be loyal.
  • Facebook analyses our posts, our “likes” and our updates to predict what products or services we might want to buy.
  • The police can look at past and current crime data together with demographic and economic data and predict how many crimes of various types will be committed in the next year in specific neighbourhoods.

To be truly effective, any performance measurement and management activity should be concerned with the next quarter and the things it needs to do to improve performance.

6  Data quality

Another critical success factor for more mature and more successful BPM implementation is ensuring data quality. The famous saying “garbage in, garbage out” sums up the problem. If we want good insights that lead to improved decisions that drive future performance, we need data we can trust. It is no good putting in place sophisticated performance reporting and shiny dashboard solutions if the underlying data are not reliable. 
7  BPM technology

Technology to support BPM activities has evolved tremendously over the past few years. Initially, the focus was on storing and reporting performance information using databases and dashboard solutions. More sophisticated approaches then allowed companies to create closed-loop systems that help to integrate operational and strategic performance data and align traditional performance measurement with analytics. This allows companies to analyse the data and integrate performance reporting with, for example, financial management tools or other tools such as risk management or project management.

Today’s sophisticated IT solutions provide integrated BPM platforms with the ability to perform predictive and Big Data analytics and enable companies to visualise performance in interactive graphs and reports delivered to mobile devices over the internet. Many previous studies have shown that using an integrated performance management and analytics suite generates the most benefits, while most companies still use tools such as spreadsheets, Word documents and PowerPoint presentations as their main IT tools to collect, store, analyse and report performance information. Office tools have many limitations when it comes to interactivity, data presentation, data storage, data security and quality control.

About the survey
Measuring and Managing Performance – A Global Study had responses from more than 3,000 companies across all continents. The majority of participants were based in North America (32%) and Europe (41%), followed by Asia (8%), Australia (7%), Africa (6%), the Middle East (3%) and South America (3%). The companies represented varied from large multinationals to small- and medium-size enterprises. Large companies of 5,000 or more employees made up the largest individual group. All major industry sectors were represented. Almost one-quarter of the responses came from the services sector, followed by government, retail and wholesale, manufacturing, and energy and utilities – all with about 10% each.

Bernard Marr ( is an author and authority on organisational performance and business success. He is founder and CEO of the Advanced Performance Institute, a research, consulting and training organisation in business performance.


Google is an example of a company that would fall into the highest level of maturity. Board members have identified their strategic priorities and a set of about 35 questions they require answers to. Each question is tightly linked to the company strategy and spells out the company’s information needs. Board members ensure all data that are reported to them provide answers to the key questions, which provide a powerful filter for performance reporting and data.

Google then uses a combination of traditional key performance indicators as well as more innovative analytics such as text analysis. For example, the company’s traditional HR performance data, such as 360-degree feedback scores, staff engagement or productivity, are now supplemented with interview data and text analytics of “best manager” type awards. This combination of structured and unstructured data has allowed Google to narrow the factors that make a good manager at Google and the factors that managers who struggle have in common.

Google has used the insights to inform changes in its recruiting process, induction program and leadership training as well as its performance management process.