categoryPerformance Management

Rethinking The Use of KPIs In The Digital Era

Most companies do not deploy Key Performance Indicators (KPIs) rigorously for review or as drivers of change. This is the overall finding from a recent survey report, Leading With Next Generation Key Performance Indicators, published by MIT Sloan Management Review. The report is biased towards Sales and Marketing functions.

Changes in the business environment such as accelerating technological innovation, intensifying competitive pressure, significant emerging risks, increasing customer expectations, and complex regulations are influencing business models and causing tremendous shifts in the strategic direction of the company.

As a result, executives are struggling to balance tactical and strategic KPIs, including operational and financial KPIs that effectively capture the moment while anticipating the future.

Part of the survey findings include:

  • KPIs are not enjoying special status as either enablers or drivers of change in many companies. Instead of providing value added insight to guide and drive performance improvements, KPIs are more about “tick-box” compliance. Either that gives you a sense of the scale of key decisions made on intuition versus data-driven or it makes you realize that despite the critical role of KPIs in enabling informed decisions, many executives are still not aware of this.
  • Lack of alignment of KPIs with strategic objectives. Only 26% of the survey respondents agreed that their functional KPIs are aligned with the organization’s stated goals and strategic priorities. Such a huge disconnect explains why many companies are struggling to execute their strategy more effectively.
  • Customer-focused KPIs are increasingly becoming more important. Many companies are taking a more customer-centric approach to spur growth. As a result, they are seeking to understand customers in more holistic ways. 63% of respondents say they are now using KPIs (such as NPS, customer segmentation, customer lifetime value, brand equity, churn) to develop a single integrated view of the customer and understand the customer’s experience at each touch point including the aggregated journey.

Based on respondents’ answers to a specific set of questions on how well a company has aligned its use of KPIs, the report authors were able to categorize the companies into three – Measurement Leaders, Measurement Capable and Measurement Challenged.

According to the study findings, six behaviors are common to Measurement Leaders:

  1. Use KPIs to lead, as well manage, the business. Companies falling into this category treat their KPIs not simply as “numbers to hit” but as tools of transformation. KPIs are used to effectively align the organization (people and processes) and also provide predictive insight that help frame strategy and lead the company into the future.
  2. Develop an integrated view of the customer: Respondents falling into this category have shifted their focus beyond traditional financial and customer satisfaction metrics to including externally focused KPIs that enable them to better segment and engage customers. Such measures complement and build upon more internally focused process KPIs. However, an integrated customer view remains an aspiration for many businesses. For example, 41% of survey respondents are still managing digital customers separately from physical customers. Companies that are making progress in this space are experimenting with automation and machine learning technologies to develop a 360-degree view of their customers.
  3. See KPIs as data sets for machine learning: Nearly 75% of executives surveyed expect that ML/AI technologies will help them achieve strategic goals. Instead of viewing KPIs just as analytic outputs for business performance review and planning, organizations can take advantage of ML which empowers software and systems to learn from data-driven experience. This creates opportunities to use KPIs (individually and collectively) and their underlying data to teach ML algorithms to improve and optimize their performance and drive marketing activities. However, care must be taken that the KPIs used as data inputs for ML actually reflect business reality, otherwise the systems will learn from wrong inputs leading to garbage in, garbage out.
  4. Drill Down into KPI Components: Drilling down to a KPIs components is critical for effective KPIs. It helps executives see the underlying data or analytic components that are aggregated into KPIs, determine why specific KPIs have over or under-achieved and prioritize critical business issues. For example, the drilling down can be done according to different customers, segments, channels or different products. Legacy organizations with legacy IT systems and legacy financial reporting processes, however, generally lack this capability
  5. Share trusted KPI data: While it is true that the whole is greater than the sum of its parts, having shared KPIs facilitates effective cross-functional collaboration because managers can see the positive or negative impact of their own KPIs on others. This cause-and-effect relationship also enables opportunistic efficiencies and outcomes. Although transparent, shareable KPIs can create new dynamics, in some cases, conflict may arise within the organization due to overstepping of boundaries in turn affecting accountability.
  6. Aim for KPI Parsimony: There is no magic number of desirable effective KPIs for an organization. However, too many KPIs easily become unwieldy, unmanageable, and create unrealistic expectations. Too few might result in the neglect of critical business issues. In today’s digital world characterized by data proliferation, it is much easier to get carried away and succumb to “KPI creep”. Measurement leaders know what to focus on – a balanced set of vital and valuable KPIs that have massive potential to make a huge difference to their businesses. Instead of wasting resources on ordinary metrics or measures that promote bad behaviours and fail to influence the strategic priorities of the business, they understand that to be effective and account for business success, KPIs must truly be “key” performance indicators.

To obtain greater value and returns from their KPIs, the report recommends companies to identify their top 3 enterprise and top 3 functional KPIs, create a process for ongoing enterprise-wide discussion of KPIs, and treat KPIs as a special class of data asset.

Additionally, I believe company leadership should also:

  • Acknowledge that effective performance measurement requires a cultural shift. The fish rots from the head. If there is no executive sponsorship, chances are high that the use of KPIs to drive growth will remain relegated to the lower rungs of the ladder.
  • Integrate performance management with risk management. The former looks at KPIs and the latter looks at Key Risk Indicators (KRIs). Business success is also a result of making informed and intelligent risk decisions
  • Start with the WHY of data collection. While it may be true to say that data and analytics are the raw ingredients of KPIs, a company’s data needs must be supported by the key performance questions raised. It is therefore imperative to ask critical questions before accessing any new data.
  • Understand that technology is just a means to an end and not the end itself. A company does not necessarily need to invest in new technology to reap returns from its KPIs. Just because “experts” are preaching the gospel of ML/AI as the solution to modern business problems, first evaluate if your business is in dire need of such technology and cannot survive without it.

FP&A Leaders are Failing to Deliver Higher Strategic Value

Last month, Prophix Software released its findings from the survey, Defining the Evolution of FP&A: Benchmarks, Challenges & Opportunities. The survey which was carried out between Q2 and Q3 of 2017 received feedback from over 300 FP&A leaders from all companies of all sizes across the globe.

The survey was conducted to establish the maturity of analytics solutions across the globe, the effectiveness and efficiency of FP&A leaders’ planning processes, how companies are leveraging technology to improve FP&A processes, and to gauge internal perceptions relative to the value of FP&A.

Although certain parts of the results are encouraging, FP&A teams significantly need to improve on their role of delivering higher strategic value to their companies.

In today’s fast moving markets, characterized by intense competitive pressures, shorter product life spans, complex business environment, increased volatility, and heightened uncertainty, it is imperative that a company’s FP&A people, processes, and systems are highly mature, effective, efficient, and leverage the necessary enabling technologies.

While going through the survey findings, a couple of statistics captured my attention.

  • 55% of the survey respondents reported being in a basic or developing state of the FP&A analytical maturity.

Comment: Essentially, more than half of the survey respondents have no formal FP&A process, no established analytical and reporting matrixes, no planning model and tools as well as BI tools. If ever they are there, these are all basic, highly manual and descriptive in nature.

This basic level of analytical maturity brings to light the fact that a culture of continuous innovation and improvement is non-existent in Finance. As the custodians of data within the organization, one would assume Finance to be at the forefront of analytical maturity, but this is not the case.

Surprisingly, 50% of respondents are mindful of technology but seldom upgrade. This statistic alone is concerning. Why are FP&A leaders reluctant to change? Are they happy with the status quo? Are they lacking the resources necessary to transform? Is it ignorance in its purest form?

Transitioning from a basic to an advanced or leading FP&A maturity level, above all, requires a cultural shift all the way from the top to the bottom of the organization. There has to be a desire to change for the better, a willingness to commit and continuous learning attitude.

Attending industry conferences, seminars or webinars and reading thought leadership resources as well as listening to their podcasts can help FP&A leaders keep abreast of trends and benchmark their company’s performance against peers.

  • Only 12% of the survey respondents have access to the right data, at the right time, to inform strategic decisions at their companies.

Comment: Having access to the right data, at the right time is key to informing strategic decisions and driving business performance. Unfortunately, 88% of respondents do not have this access.

This means the majority of critical decisions in companies across the globe are based on gut-feel and not evidence-based.

In today’s Big Data age, it’s startling to know that companies are not leveraging advanced analytical tools to aggregate and analyze data from disparate sources and generate key nuggets on customer experiences, competitor behaviour, trends, emerging risks and opportunities.

Moving forward, FP&A leaders need to make use of data management framework that facilitates the creation of a central data repository and ensures everyone in the company has access to relevant data whenever they need it.

This can only happen if the company makes a key decision to advance its analytical maturity model. Highly manual processes make it difficult to update FP&A models in real time, thereby inhibiting quick decision-making processes.

With the recent advancements in technology, the costs of implementing new software to enhance FP&A processes have significantly reduced. Companies should therefore not use cost as an excuse for low adoption rates.

  • Only 10% of companies reported that they find it somewhat easy to perform scenario analysis.

Comment: In today’s VUCA business environment, companies need to be proactive, develop superior forward-looking capabilities and be ready to deal with any disruptive forces threatening their survival and existence.

They need to become more flexible, adaptable and be increasingly aware of the impact on business performance of changes in the environment. This will help them take corrective actions more quickly and efficiently.

Unfortunately, 90% of the surveyed companies are finding it difficult to perform scenario analysis. As already reported, over half of them are still reliant on basic and highly manual processes which in turn makes it difficult to consider all possible scenarios in their FP&A models.

For the 10% who are finding it somewhat easy to perform scenario analysis, what are they doing right? They have managed to figure out that FP&A is a collaborative process extending beyond the walls of Finance. Also, rather than use fixed time-specific budgets, they are using driver-based rolling forecasts to see beyond 12 months.

Instead of sitting on their desks all day long, these professionals engage the wider business community, learn about the external and internal factors influencing strategy execution, how they are all interrelated and their material impact. They are then able to leverage new technologies, calculate any probabilities and update their FP&A models in real time.

Having a deeper understanding of the key drivers of business performance helps FP&A leaders define relevant scenarios that describe a range of future operating environments, and generate forecasts reflecting the changes in scenarios which in turn helps decision makers to adjust their strategic plans, targets and action plans.

  •  55% of respondents conveyed that their companies don’t think that FP&A delivers high strategic value.

Comment: FP&A professionals are a critical part of the Finance team. They help operational and strategic decision makers make informed decisions by providing them with reliable, timely and fact-based recommendations.

They bridge the gap between financial and operational plans and ensure decision makers receive the right information, at the right time. The reason why 55% of the surveyed companies are not happy with value-delivery of FP&A is because FP&A teams are spending the majority of their time on low-hanging fruits.

According to the survey findings, 51% of the time spent on FP&A is allocated to data collection or validation. Thus, instead of spending more time on generating insights and influencing business decisions, FP&A teams are busy reporting on the past and justifying reported results.

This quite understandable given the high levels of technological immaturity in many companies. By leveraging advanced analytical tools, FP&A will be able to reduce time spent on data collection, reconciliation and cleansing and free up resources that can be used to deliver higher strategic value.

Instead of generating reports and analysis that they feel are valuable, FP&A teams should regularly liaise with business teams and establish their reporting and information requirements. This will help ensure that resources and time are constantly not being wasted on non-value adding activities.

For the majority of companies that are still basic or developing their analytical maturity, I recommend that they take a candid review of their current FP&A people, processes and systems, and make an honest conclusion of whether they are happy with where they are at the present moment or need to make significant changes.

Everything might look good today, but always remember that Good is the Enemy of Great!

Intelligent Automation: The Next Frontier in Finance Transformation

Advancements in technologies and the exponential growth of data are presenting massive opportunities for the finance function to embrace intelligent automation, aggregate and analyze data from disparate sources and ease reporting and analysis.

Today, we are witnessing technology evolve at different rates, providing a spectrum of capabilities ranging from simple, rules-based and deterministic process automation to smart machines that can learn and adapt. Thus, the potential to deploy automation in the finance function is significant.

Intelligent Automation as the Way Forward

To meet today’s finance challenges, finance chiefs have to embrace digital transformation, harness new technologies to supplement or automate the tasks undertaken by knowledge workers, drive better process effectiveness and cost efficiencies in ways not previously possible.

Process automation is not a new thing. Automation has for a very long time proven itself as an operational efficiency driver and quite a number of organizations have successfully automated their Order-to-Cash, Procure-to-Pay, Record-to-Report and Cash Management processes and reaped the intended benefits. However, in today’s tech-driven environment, businesses have to think beyond basic automation and embark on intelligent automation – to include higher-value performance management processes.

Successful digital transformation comes not from implementing new technologies alone but from transforming the organization to take advantage of the new possibilities that technologies provide.

The key to successful digital transformation is developing a deeper understanding of the “why” and “what” of automation. With intelligent automation, repetitive and rules-based tasks are automated and made smarter, workflows are streamlined resulting in improved decision making, humans are freed up to take on more strategic roles and machines augment human skills and capabilities to deliver new business solutions that would not otherwise be possible. Intelligent automation thrives when it’s augmented with people to drive better outcomes as humans have to educate machines the reasoning steps necessary for transforming raw data into valuable and actionable insights.

Adopting Intelligent Automation

Intelligent automation is fundamentally transforming traditional ways of operating, for businesses and individuals. Prior embarking on this journey, it is critical to have a thorough understanding of the intelligent automation technology landscape.

At the lower end of intelligent automation spectrum is Robotics Process Automation (RPA) which many finance executives are familiar and comfortable with. These systems act as a virtual agent to execute tasks and imitate the same manual path through an application would take using a combination of user interface interaction or descriptor technologies. They are good solutions for aggregating data, performing basic analysis and then visualizing the data.

The substantial benefits of an efficient RPA process makes the technology very attractive to finance teams. Its best applications are generally highly manual, transactional and rules-based processes that have a low exception rate and are subject to high operational risk, for example, accounts payables/receivables, claims processing, invoice processing, regulatory reporting, journal processing, periodic accounting books closure, contract/SLA compliance and account reconciliations.

RPA technology allows accounting and finance teams to configure computer software to reason, collect and extract knowledge, recognize patterns, learn and adapt to new situations or environments. Think of this as your everyday excel macros but at a more advanced level. Another added advantage of RPA is that it helps finance functions achieve cost efficiencies by lowering the Full Time Equivalent (FTE) costs. Successfully implemented, a robot or computer software program reduces the number of full time personnel required to run the finance function. Also, the system can be configured to perform tasks during hours of the day humans are not available.

More sophisticated than RPA systems are Machine Learning and Natural Language Processing systems. The former involves computers improving their performance as a result of being exposed to large datasets and developing learning capabilities by themselves without the need to follow explicitly programmed instructions. The smart machine automatically discovers patterns in data and uses these patterns to make predictions. The more transaction data a machine learning system processes, the better its predictions are expected to become, to the point where it can predict situations just before they actually happen. Machine learning capabilities can be used to enhance sales forecasting and fraudulent transaction detection.

Natural Language Processing (NLP) is technology based on the understanding and interpretation of human language by a computer, and is usually associated with the analysis of large pools of information, such as legal documentation. NLP technology has the capacity to organize and structure data in real-time on a large scale from a multiple sources and can facilitate an employee’s work by carrying out demanding tasks such as going through client information to single out discrepancies or summarizing lengthy financial regulation documents.

Accounting and finance teams can leverage NLP to explore unstructured data to gather market intelligence, comply with regulations or provide procurement surveillance. For example, NLP queries can identify possible incremental sales/purchase orders and flag out any potential red zones.

In addition to the above, when combined with other digital technologies such as RPA and machine learning, NLP can help finance organizations make accurate customer and pricing decisions. For instance, RPA can help aggregate all the required customer information from multiple systems and build customer profiles based on a scoring model. NLP technology analyzes and interprets the structured data, prepares the reports in an easily readable format, then communicates relevant customer pricing insights in a narrative form.

Establish a Small Business Use Case

As much as understanding the intelligent automation technology landscape is critical, this alone is not enough. You also need to build a coherent business case for adopting intelligent automation. One of the hurdles faced by finance executives when trying to implement new technologies is lack of buy-in and support from other senior executives. So often these initiatives are greeted with less enthusiasm and labelled costly and time-consuming investments.

Instead of initially embarking on wide-scale deployments, finance chiefs are advised to first start with the discovery mode. This involves selecting an individual process or processes for automation and use these as a yardstick for success. The rationale behind starting small is that you want establish quick wins and business use case, tell a compelling story, then build on that success. There are certain factors that need to be considered when identifying the process candidates for automation and these include – the amount of time spent on each activity, the number of steps or people involved as well as what systems already exist to perform some of these tasks.

If an activity or process requires more time to complete, is labour intensive and has many steps to follow, then automation might be worth the investment. Regarding systems already in place to perform some of these tasks, it is important to consider if there are any other alternatives for achieving process efficiency that the organization is bypassing and that could yield better outcomes.

If the results of the pilot program are evident enough and convincing in terms of the amount of time savings, the level of operational costs reduction, how intelligent automation is leading to better outcomes and what the business is able to achieve that wasn’t possible before intelligent automation, then it becomes less of a daunting task to secure buy-in and support from the project sponsors.

Organizational Culture and Communication are Key Ingredients 

The tendency for employees to resist change can derail a move towards wide-scale deployment of intelligent automation. This is often the case if employees have concrete belief that their jobs are being taken over by machines leaving them redundant.

With intelligent automation, smart employees are freed-up from monotonous, non-value-adding work, and empowered to focus more on higher value work and tasks that require creativity, critical thinking and judgment to achieve increased individual productivity and greater employee satisfaction.

Thus, in order to secure employee buy-in business leaders must be proactive in commencing this process. They must engage employees and communicate the change and benefits of new technologies, offer to retrain or redeploy those affected and provide a clear path towards new roles as well as prepare employees to work alongside automated processes.

To be successful, change strategies should be established and reinforce the connection between intelligent automation and ongoing employee development, and the ability of new technology to augment existing roles, while also giving rise to new and engaging ones.

Reinforce Collaboration Between Business Teams and IT Specialists

A significant number of new technology failures are attributed to the lack of collaboration between business and IT teams. Many business leaders are often under the incorrect assumption that adoption of intelligent automation systems does not require extensive IT support. As a result, they tend to ignore the input of these specialists leading to immense project failures. The opposite also holds true. In the case of IT-extensive projects, IT leaders often undermine the contribution of business teams and fail to take process nuances into consideration.

To be successful and yield better outcomes, intelligent automation should be a combined effort between business subject matter specialists and technologists with an operating model that defines the roles and responsibilities of each player.

Business subject matter experts play the critical role of defining operational requirements, leading process design initiatives and monitoring performance, while technologists focus on ensuring effective data security and governance, systems integration as well as monitoring identity and access and control.

Intelligent automation should be tackled as part of a bigger digital transformation initiative contrary to being delivered in isolation. Senior executives, leadership teams and employees must all share an integrated automation vision, commit to its success, and develop measurable goals across the organization against which performance can be assessed.

As technology evolves at an accelerated pace, finance leaders have no choice but to concede that automation in all its forms is already playing a role in their organization’s future. Aligning technology investments to customers’ needs and business outcomes is now a critical endeavor than before.

Why KPIs Alone Do Not Drive Results

No matter how small or big a company is, all companies aspire to achieve superior business performance that beats the odds. Meeting after meeting, they map out a road map for achieving this success. KPIs are brainstormed and a select critical few to focus on defined for monitoring.

Designed to track performance against targets and drive results, KPIs help managers and executives establish whether performance is improving, deteriorating or remaining stagnant. This then allows them to take corrective action where necessary.

The problem we see in many companies today is lack of KPIs ownership and accountability. Yes, they are tracking the right metrics but the process ends there. There is no individual who is responsible for the performance of that metric.

KPIs Need People Ownership and Accountability

KPIs alone do not drive results, they need people ownership and accountability. Ownership is key to ensuring successful adoption of performance management across the organization. Lack of buy-in and engagement makes it difficult for employees to manage their performance.

On the other hand, accountability ensures that individuals, teams and management are held responsible for their performance against specific initiatives. Having said this, you need to empower your employees to drive performance and not micromanage them.

If employees are not given autonomy to manage their performance, in the event of faltering results, they will most often enter into a fight-or-flight mode which by default is counterproductive.

When it is clear who owns the results, management can make follow-ups with responsible individuals or teams, provide visibility of how they are performing and how their performance is impacting the top-level business metrics. This helps create awareness of any performance problems that need addressing at the earliest convenience.

One of the reasons why companies are facing KPIs ownership problems is because of a lack of shared understanding of the meaning of performance measurement. So often, performance measurement is associated with punishment and rewards. Hit the targets and you get rewarded. Miss the targets and you get punished.

This shouldn’t be the case. Rather, performance measurement should act as an improvement tool that propels the organization forward.

A Culture Focused on Performance is Needed

In order to drive company-wide adoption and buy-in, organizations must develop a culture of performance. What do I mean by this? All employees must go through training on “what is performance management?” and how to do it.

This is key to ensuring that everyone speaks the same language concerning KPIs and performance improvement. It is imperative that employees have a shared understanding of how performance is managed and communicated, both at individual and team level, and how this influences overall objectives.

In addition to training opportunities, organizations should also provide tools that enable employees to embrace this culture. The environment should be supportive of this cultural shift, otherwise all efforts will end up being fruitless.

Improving corporate performance starts with individuals and entails a cultural and mental shift. Thus, employees should be able to see the cause-and-effect relationship between their actions, business performance and rewards. One way of creating this awareness involves identifying performance champions within the organization and granting them the responsibility and resources required for transforming the culture.

For example, performance champions play a critical role of continuously reinforcing the right habits in one another so that performance improvement is on their minds all the time. They also help explain the significance and value of using KPIs or metrics of success in their everyday work.

Once individuals and teams have a clearer understanding of the “why” part of KPIs, it completely changes the way they view performance management and also the importance they grant to the process.

Execution is Key to Business Performance Improvement

Although KPIs provide focus and act as a road map for strategic success, we should not ignore the important role people play in this entire process. There is a huge difference between tracking performance and tacking action. Performance management goes beyond monitoring of key metrics.

To be effective and enable better decision making, KPIs need to be evaluated against a target. This helps establish whether the outcome is acceptable or not, at the same time allowing corrective action to be taken.

If there is no pre-defined target to measure actual results against, how can we expect decision makers to take immediate remedial actions? Positive actions and results are a product of consistent, relevant and reliable information being shared across the organization.

Despite more and more data being tracked, reported and communicated in today’s analytics world, many decision makers are still lacking the necessary business insights to improve performance. They are repeatedly receiving insignificant information, which unfortunately, they are unable to act upon to drive business performance.

Once information is consistent, relevant, reliable and communicated throughout the organization, it can be acted upon. It is therefore important to make sure that the information that is being communicated and presented is in a format that is quickly and easily understandable and consumable.

You can have well-defined KPIs but what matters most are not the indicators or how many you have, but what your employees and teams do with these indicators.

KPIs Should Actually Reflect Business Reality

KPIs are an important tool to help us explain progress towards our stated goals and strategic priorities. Despite their usefulness in helping us understand where we are coming from and where we are going, KPIs are not well understood in many business settings. The key part is the one that is a significant problem. One of the first challenges faced by management and executives is determining what makes a performance indicator key.

Not every performance indicator is key. For a measure to be considered key, it must focus on what really matters to the decision makers, prompt action when things have gone wrong, alert when performance is fading, and motivate when everything is going well. The fact that you have a list of measures that you are tracking on periodic basis does not necessarily mean all of them matter. For me, KPIs are those critical few measures that drive the achievement of strategic objectives.

In other words, KPIs represent the measures that an organization relies on to monitor and drive business performance. Since these key metrics are relevant to a particular company, management should not feel compelled to create KPIs with the sole intention of replicating those reported by their peers. Although there are standard measures for each industry or sector, not all companies have the same strategy, objectives, initiatives, priorities, capabilities, data sources etc.

As a result of these differences, companies prioritize metrics differently and assign different weights to their objectives. Thus, the key to unlocking performance measurement potential is linking the process to your organization’s strategy and objectives. Considering the fact that your value proposition and business drivers are unique to you, your KPIs should also be unique to your organization.

Linking KPIs to strategy enables you to assess whether the strategies adopted by the company have the potential to succeed or not and this allows you to proactively take corrective action where and when necessary.

In current times of increasing economic uncertainty, digital disruption, changing business models, constantly shifting customer habits, rising regulatory pressures and increased competition and complexity; new strategies and objectives emerge questioning the relevance of KPIs used to monitor performance in previous periods.

The KPIs chosen to track performance and provide decision support must continue to be relevant over time and help executives develop a deeper understanding of the business. Thanks to developments in new technologies, organizations now have access to new and more critical information which in turn is facilitating reporting of new KPIs that accurately represent the organization’s strategy, the performance against which determines success.

Since KPIs helps us identify, explain and resolve critical performance issues that are instrumental for the overall success of the business, functional managers should regularly question the significance of the current set of KPIs and determine if they are actually supporting executives in making effective strategic decisions. Performance indicators that are useful cover all business areas and activities, and empower decision makers to conduct an impartial review of the business.

They also allow collaboration between functional teams and support synergies by underlying the impact of decisions taken by others on the overall performance of the company.

It is no secret that today we are living and working in an information age where information overload has become the norm. There is so much information out there to the extent that decision makers are also experiencing this information overload and don’t know what to do. In some organizations, functional teams are obsessed with measurement and have now forgotten the true meaning and objectives of metrics. The temptation to measure everything that can be measured is significantly high.

We cannot measure everything just for the sake of measuring. We need to measure only that which is critical and are able to actually do something about it. Managers or those individuals tasked with creating and monitoring performance metrics should regularly ask themselves one of these two questions – (1) Are our KPIs presented in isolation from the organization’s strategy or objectives? (2) Are our KPIs adapted to their target audience?

You don’t want to waste ample time and resources measuring those metrics that lack any insights for strategic decision making. In most cases, when KPIs are developed in isolation that is when companies end up watching a long list of measures. What you need instead is to focus on only a few metrics that are actionable, bearing in mind that the number of KPIs to measure depends on your target audience.

Executive and operational scorecards normally have a different number of KPIs to focus on. However, understanding how executive metrics and operational metrics align and support each other is crucial. This helps address the problems arising from redundant or contradictory metrics.

Defining the right KPIs and linking them across all levels of the organization to drive consistent execution is key to achieving breakthrough performance.

Remember, not everything that is measured is managed.

 

 

 

 

© 2019 ERPM Insights

Theme by Anders NorénUp ↑