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Delivering Reliable Insights From Data Analytics

Data and analytics are becoming increasingly integral to business decisions. Organizations across all sectors are leveraging advanced real-time predictive analytics to balance intuitive decision-making and data-driven insights to monitor brand sentiment on social media, better serve their customers, streamline operations, manage risks and ultimately drive strategic performance.

Traditional business intelligence reporting tools with static charts and graphs are being replaced by interactive data visualization tools that enable business insights to be shared in a format that is easily understood by decision makers, in turn enabling better, faster operational and strategic decision-making.

Given the constantly changing business landscape driven by increased competition, macro and geopolitical risks, intense regulatory demands, complex supply chains, advanced technological changes etc. decision makers are turning to finance teams for actionable insights to help them navigate through this volatility and uncertainty.

As business unit managers increasingly rely on finance decision support for enhanced business performance, it is imperative for CFOs and their teams to ensure the performance insights they are delivering are informed and actionable. However, a 2016 survey report by KPMG revealed that 60% of the survey participants are not very confident in their data and analytics insights.

Data Quality or Quantity?

In today’s world of exponential data growth, the ability for finance to deliver reliable and actionable insights rests not on the quantity of data collected, analyzed and interpreted, but rather on the quality of that data. The starting point for any successful data analytics initiative involves clarifying why the business needs to collect a particular type of data.

One of the challenges facing many businesses today is identifying and selecting which internal and external sources of data to focus on. As a result, these companies end up investing in data warehouses full of massive amounts of useless data. To avoid being data rich and insight poor, CFOs need to understand  the role of quality in developing and managing tools, data and analytics.

Before inputting data into any analytical model, it is important to first assess the appropriateness of your data sources. Do they provide relevant and accurate data for analysis and interpretation? Instead of relying on a single source of data for analysis, you need to have the ability to blend and analyze multiple sources of data. This will help make informed decisions and drive business performance.

Further, businesses are operating in a period of rapid market changes. Market and customer data is getting outdated quickly. As a result, being agile and having the ability to quickly respond to changing market conditions has become a critical requirement for survival. The business cannot afford to sit on raw data for longer periods. Capabilities that enable data to be accessed, stored, retrieved and analysed in a timely basis should be enhanced.

Thus, in order to provide business users with access to real-time and near-time operational and financial data, the organization should focus on reducing data latency. Reducing data latency allows finance teams to run ad-hoc reports to answer specific business questions which in turn enables decision makers to make important decisions more quickly.

In the event that finance provides business insights or recommendations based on inaccurate data, analysis and predictions, this will quickly erode, if not extinguish, business trust and shake the confidence of those decision makers who rely on these predictions to make informed decisions.

As data volumes increase and new uses emerge, the challenge will only increase. It is therefore critical for finance to put in place robust data governance structures that assess and evaluate the accuracy of data analytics inputs and outputs.

Work with business partners to set objectives up front

Churning out performance reports that do not influence decision making is a waste of time yet that is what most finance teams are spending their time doing. It is not always the case that the numbers that make sense to finance will also make sense to business partners.

The biggest problem in the majority of these cases is lack of understanding by finance of the business objectives. Instead of collaborating with the business to develop a better understanding of their operations and how performance should be measured and reported, many finance analytics teams are working in their own silos without truly linking their activities back to business outcomes.

To improve finance’s reporting outcomes, the function should take stock of the reports it produces per month, quarter or annually. Then evaluate the nature and purpose of each report produced and what key decisions it helps to drive. It is not about the quantity of reports that matters, but rather the quality of the reports.

Business partners need to be engaged at the start of the process and throughout the analytics process. They need to be involved as finance explores the data and develop insights to ensure that when the modeling is complete, the results make sense from a business perspective

By working with business partners and setting objectives up front, finance will be able to focus its efforts and resources on value-add reports that tell a better business story. Further, the function will be able to assess and monitor the effectiveness of its data models in supporting business decisions

Simplify interconnected analytics

With so many variables impacting business performance the organization cannot continue to rely on gut instinct to make better decisions. The organization has no choice but to use data to drive insights. As a result, organizations are relying on a number of interconnected analytical models to predict and visualize future performance.

However, given that one variable might have multiple effects, it is important for the business to understand how changes in one variable will affect all the models that use that variable, rather than just one individual model. By maintaining a meta-model, the organization would be able to visualize and control how different analytical models are linked.

It also helps ensure consistency in how data is used across different analytical models. Ultimately, decision makers will be able to prioritize projects with the greatest potential of delivering the highest value to the business.

Build a data analytics culture

Advanced data analytics is a growing field and as such competition for talent among organizations is high. Due to their traditional professional training, many accounting and finance professionals lack the necessary data and analytics skills.

More over, decision makers not knowing enough about analytics are reluctant to adopt their use. Because of cognitive bias, it is human nature to subconsciously feel that their successful decisions in the past justify a continued use of old sources of data and insight. What we tend to forget is that what got us here won’t get us there, hence the need to learn, relearn and unlearn old habits.

To move forward, the organization should focus on overcoming cognitive biases developed over the years, and closing this skills gap and develop training and development programs that can help achieve the desired outcomes. Using advanced analytics to generate trusted insights requires an understanding of the various analytics methodologies, their rigor and applicability.

It’s difficult to have people understand if they don’t have the technical capabilities. However, building a data analytics culture does not imply that the organization should focus on developing data science skills alone. You also need to develop analytics translators.

These are individuals who are able apply their domain expertise in your industry or function, using a deep understanding of the drivers, processes, and metrics of the business to better leverage the data and turn it into reliable insights and concrete measurable actions.

Building a data analytics culture that promotes making decisions based on data-driven insights is a continuous endeavour that spans the data analytics life cycle from data through to insights and ultimately to generating value. Successful use cases can be used to further drive the culture across the organization.

Finance Value Creation Goes Beyond Running the Financial Side of the Business

Advances in technology are helping the finance function reduce operational costs, streamline processes and improve productivity. Thanks to automation, tasks that used to take months to complete are being completed in weeks and those that took weeks to accomplish are getting done in days.

For instance, advanced analytics and robotic process automation are shortening the timelines finance teams require to produce a forecast, perform account reconciliations or close the books.

Technology is enabling more to be done with less and the trend is not expected to go away anytime time soon. A couple of years go the staff size of the finance function was big. CFOs were happy to have separate staff handle AP, AR, Payroll, Bank Reconciliations, Management Accounts etc.

Today the size of the finance function has shrunk significantly. Thanks to shared services centers, outsourcing and process automation. Robots have taken over rules-based, repetitive and transactional tasks that were once performed by humans.

Machine learning algorithms are already replicating highly analytical tasks, analyzing large data sets and churning out insights in real time to support decision making. Although the adoption of machine learning and/or AI tools is not yet widespread it’s only a matter of time before the technology becomes a part of our everyday life.

Implications for finance professionals

In order to stay current and move ahead finance teams need to evolve and adapt to the changing environment.

Some of the skills we have acquired in the past and relied on to get us to the next level are no longer sufficient in the current and future environment. As a result, we have to develop a continuous learning mindset. Learn new ways of doing things, unlearn the old habits and continue to relearn.

For instance, being detailed oriented alone used to be sufficient. Not anymore. Today finance professionals are expected to be commercially aware and broad in their thinking.

Decision makers are searching for collaborative business partners who have a deeper understanding of the operational and strategic challenges facing the business. Problem solvers able to enrich the business with insightful analysis and capable of recommending the right solutions. Team players who understand the markets in which the business operates, its products, competitor business and the drivers of performance as a whole.

Build a big picture perspective of the business

If finance is to be recognized as a valuable strategic business partner we need to build a big picture perspective of the business and be able to recognize the role and contribution of each function, individual, process and activity in achieving the objectives of the company. Knowing debits and credits alone will not take us far.

With the business environment constantly changing, we need to shift our focus from historical analysis to forward looking.

Many at times we spend a lot of time producing variance analysis reports that do not drive the right conclusions and actions out of the insights. For example, simply commenting sales for the month are up 5% or operational costs are down by $1MM is not insightful enough to support key decision making.

We need to understand what the numbers mean and the real drivers behind them. For example, did sales increase because of new customers, price increases, improved demand, enhanced marketing efforts, new product lines, entry into new markets, product bundling?

CFOs and their teams need to be doing more than running the financial side of the business – recording revenues and costs. Instead, they should help the business adapt and make insight-driven strategic turns without throwing off alignment between broad strategy and day-to-day execution.

Part of building a bigger picture perspective of the business requires a finance function that is more flexible and collaborative than in the past and knows how to manage its internal working relationships. A finance function that is capable of partnering with operations instead of always pointing out what operations is always doing wrong.

Spending the majority of our time behind our desks preparing financial statements and regulatory compliance reports will not help us become more strategic and commercially aware. We need to get interested in the affairs of the business. Avail ourselves for projects that take us out of our comfort zones. Regularly interact with colleagues outside finance to get a deeper understanding of the drivers of the business, what projects the teams are working on, how they align with the broader strategy, the risks and challenges they are facing and recommend solutions.

If you are used to sitting behind a computer all day, leaving your desk to engage with the business is initially unnerving but the more you do it the more confidence you gather. Evolving priorities require a finance professional with a well-honed ability to communicate, build trust and maintain collaborative relationships with the rest of the business.

Driving business growth versus cost cutting

Too often finance teams are focused on cost cutting activities in order to improve the bottom line instead of identifying alternative ways of driving up top line growth. Today’s global companies are operating in a world of complex supply chains, intense competition, shifting customer expectations, increased regulatory demands, emerging operating models and exposure to significant business risk. Cost reduction alone will not help the business sustain its competitive relevance in this world.

The problem with many cost optimization programmes is that they fail to deliver the expected outcomes. It is not about how much you cut the costs, rather where you channel resources to differentiate, stimulate growth and achieve strategic objectives. Finance needs to look beyond narrowly defined functional or organizational structures when identifying candidates for cost cutting and take a holistic, end-to-end view of costs across the whole organization. This will help separate the strategically-aligned good costs from the non-essential bad costs.

With the adoption of big data and analytical tools becoming mainstream, it’s not too late for finance to play catch up. Transitioning to data analytics starts with putting in place a well-structured data and information management foundation and then combining technology with the right analytics and expertise.

Only then can finance transform data into true, actionable business intelligence (on products, customers, markets, process efficiencies, supply chain, competition and business risk) that drives better informed decision making and business growth.

Traditional financial reporting does not provide the actionable information the business needs to make more informed strategic decisions. Today, the business needs to leverage both structured data (which resides in enterprise databases) and unstructured data (email, social media, internet) including analytics to generate insightful analysis that can help drive operational and strategic performance.

For example, finance should be able to collaborate with the marketing function, analyze and interpret customer data to understand customer journeys, and help the function design and implement better customer/brand strategies and responses.

Finance cannot expect to drive business growth by continuously doing the same things. It’s not about this is how we have always done things here. Ask yourselves: what is the right way of doing things in today’s disruptive world and what are the expectations of the business?

Risk-Based Decision Making

Risk is an inherent element of the business. Given that every business activity or decision has a risk consequence, a business should not expect to operate and progress by making risk an afterthought.

Technological advances, evolving customer expectations, volatile markets, global political instabilities, shifting demographics and natural disasters are impacting business models and forcing organizations in every sector to rethink the way they operate.

Left unaddressed, these forces of change have a huge potential of derailing the strategic plan of the business and accelerate the organization towards failure. In order to survive in this VUCA world, the business should make a paradigm shift from reactive to proactive mode. This helps prepare and plan for the future rather than respond to it  after it has arrived.

The challenge today in many companies is that risk-based decision making is an afterthought. Only after going through a turmoil do people start asking where is risk management and why did the risk experts fail to anticipate the events in advance. In financial services companies where there are dedicated risk management teams, it is easier to point the finger of blame.

However, not all companies have a dedicated risk management function.

Risk is everyone’s responsibility

What exactly is the meaning of this statement?

Is making risk everyone’s responsibility part and parcel of risk culture?

What is the best approach of making everyone embrace risk-based decision making?

If some employees within the organization have never received training or guidance towards risk decision making, are they still held responsible?

By making risk everyone’s responsibility are we increasing confusion and blurring the lines between accountability and responsibility?

In the event that a business fails as a result of activities or decisions that could have been avoided, who is held accountable and responsible?

The CFO as the champion of risk-based decision making

In companies lacking a dedicated risk management function with a CRO at the helm, overseeing of risk management is normally under the purview of the CFO. The CFO is better positioned to champion meaningful risk conversations across the organization and drive better decision making processes.

Many people connect risk management with the negatives, hence the desire to avoid risk at all costs. Risk-based decision making is not about managing or avoiding risk. Effective risk management involves looking at the upside of risk and making informed risk decisions that help the organization achieve its stated objectives.

Driving a risk-based decision making culture therefore goes beyond lip service. It is not about merely saying everyone is responsible for risk. It is about raising risk management awareness and developing risk competencies across all staff levels through training, discussion and sharing of risk information.

Risk doesn’t start to happen once the strategy has been set. With the world always changing, risk is a constant present both before and after strategy setting. That is why it is important to understand the risks of your strategy including risks to the execution of the strategy.

Once every employee has a better understanding of risk, how it applies to their individual area of responsibility and align with the overall strategy of the business, risk-based decision making ultimately becomes part of the culture.

Given that finance has a unique end-to-end view of an organization the CFO plays a critical role in helping business partners understand the strategic plan of the business, identify, quantify, and mitigate any risk that affects or is inherent in the company’s business strategy, strategic objectives, and strategy execution.

The CFO is capable of leading the risk conversation and ensuring that the focus is more on taking advantage of opportunities and achieving strategic objectives and less on the downside, in turn ensuring that more value is created than is preserved.

Although the CFO has the bird’s eye view of the organization and an understanding of where the risks are coming from including the mitigation strategies, s/he cannot do it alone. Risk management requires an holistic approach across the company, and different risks are the problem of the function that they most impact.

It is therefore imperative that the CFO co-ordinates efforts and works alongside other C-suite executives to identify and assess emerging risks and best understand how to mitigate them.

Having the ability to partner with the business and speak their language is key to leading and engaging C-suite executives in meaningful risk conversations that help mitigate risks to the execution of the strategy.

Relationship between risk and performance

Risk conversations have to keep pace with the complexity of the business. Elevate the conversation to include a discussion around sources of potential disruption, their impact on the day-to-day execution of your strategy and the creation of value, and what your organization should do to increase the possibility of success.

Risk and performance are two sides of the same coin. A business cannot manage risk in isolation of performance. At the same time, the business cannot manage performance without consideration of risk. It is therefore imperative to integrate risk into your strategy and performance management decision making processes.

One way of embedding risk in the strategic planning process involves connecting your risk reporting and your strategy execution. Unfortunately, companies spend a significant amount of time compiling risk registers that do not inform strategic decision making. I have come across risk registers that list hundreds of risk events with very few of the events connected to the achievement of strategic objectives.

Risk assessment exercises should not be performed in isolation to strategic decision making. It is therefore important for the team responsible for performing risk assessments and compiling risk reports to understand what the strategy of the organization is, including what the strategy colleagues are doing on a day-to-day basis.

Not only will this help understand the business environment but also key assumptions. Instead of churning out the same report with the same list of risks on a monthly or quarterly basis, your report should be a reflection of key risk management changes overtime and help influence business decisions.

Conclusion

Risk-based decision making should be integrated into the overall management system of the organization. Given the constantly changing business environment, the business should always be ready for the unthinkable.

Business leaders should therefore focus on continuously improving the organization’s risk management framework and employee risk competencies to ensure both are capable of withstanding the test of times.

CFOs Beware: Don’t Get Caught Up In the Hype of New Technologies

In one of my articles, Finance Transformation: From Efficiency to Effectiveness, I recommended CFOs to first identify a business problem before investing in a new shiny piece of technology.  Today, there is so much talk about digital transformation and the immense potential of new technologies to drive business performance.

With a plethora of tools available on the market and all promising to deliver better results, one of the biggest challenges faced by many CFOs and finance executives  is identifying, evaluating and selecting the right tool for the business.

Compounding the problem are a myriad of  articles and blogs on finance digitization portraying messages such as,  “If you are not yet invested in digital, you have already missed the train or if  you are not using the cloud, be aware that everyone else is moving forward and moving faster than you are.”

For fear of missing out, some finance executives are leading their organizations on digital transformation initiatives without a clearly defined and articulated plan.

Too Many Unconnected Systems

Due to the lack of having a clearly mapped business strategy to address digitization, some finance executives are getting caught up in the hype that inevitably comes with every new piece of technology or software on the market. Instead of investing in technology or software that serves the business, they are investing in new tools that the consultants or software sellers recommend irrespective of whether the decision is rational or not. So often the end product is a disintegrated technological infrastructure.

New technology, combined with streamlined processes and talented people is supposed to transform finance from an inefficient function into an effective team player in the business. Unfortunately, this is not always the case. Technology is acting as a hindrance. Businesses are superimposing automation on broken or marginally improved processes in turn expecting magical results. In other instances, finance teams are spending a significant amount of time reconciling and aggregating data from different systems.

Today there is an increasing call on finance to play the role of a strategic advisor to business teams yet when it comes to answering basic performance questions, most finance teams are hard pressed to do so.  One of the reasons being that the information required to answer such important questions is housed in different systems all over the organization.

Further, the individuals responsible for partnering with the business to support decision making lack access to some of the systems. They have to rely on information on spreadsheets or reports produced by those with access and most of the time this information is not readily available.

Imagine the frustration of having to wait on someone for days or weeks to send you information and when the information finally arrives you realize that it is not what you expected. For example, the report is not for the business unit you are reviewing or the period selected for the report is incorrect. Because you don’t have access to the system you have to go back to the report compiler and explain again your information requirements.

This back and forth process slows down decision making at a time when accuracy, speed and agility are increasingly important.

Looking at the same information

One of the keys to have meaningful performance conversations is have everyone look at the same information. For example, if the business wants to review the level and nature of capital investments for a given period it is imperative to ensure that the source of this information is common across the organization.

I have come across situations whereby more than one system is used to record capital expenditures often with major record differences between the systems in use. Time and resources are then redirected to focus on reconciling and resolving the reporting differences. It is therefore imperative for CFOs and finance executives to understand that technology alone will not drive transformation.

The data you input into a system will determine the output of that system. That’s why it is important to make sure that everyone is working from a central data repository. Having multiple copies of solutions is inefficient and counterproductive.

As an organization, you do not need too many systems to look at the same information. Thus, before acquiring that new piece of technology always ask yourself, “What is the problem that this new technology will resolve and also how will the investment enhance or strengthen your existing technological capabilities?” Many at times, we are quick to point out the limitations of the current system and use that as the reason for investing in an alternative solution.

Instead of taking a holistic view of the technological needs of the business, we take a piecemeal approach. For example, if AP is not happy with the current system we invest in another AP-focused system. If another team identifies system deficiencies, we look around on the market for a specific tool that addresses that function. This cycle continues over a period of time and ultimately the organization is left with a handful of siloed pieces of systems not completely integrated into the overall technological infrastructure of the business.

As the business and its information needs evolve, sometimes a reconfiguration of the current system(s) as compared to implementing a new one is what is needed. That is why it is important, from the onset, to evaluate the suitability of each piece of technology against the various growth phases of the business. Ask the software seller, “If our business continues to grow, will your product still be able to support our business needs and help us deliver our unique value proposition?”

Considering all the plausible scenarios and options available will help you determine if the technology will serve you for the short or long-term future.

Fear of missing out

Studies have revealed that as individuals we are prone to mimicking people’s actions and their product choices instead of applying our own independent assessment and best judgement. This not only happens at a personal level but also at a professional level.

For example, imagine as a CFO you recently attended an industry conference and the majority of finance executives you met spoke about investing in AI capabilities. Some have already implemented pilot projects and others are at an advanced planning stage. Since your organization hasn’t made plans yet, you make a hasty decision to invest in AI to avoid missing out and keep pace with what others are doing.

The problem with this simple approach is that rather than initially evaluate AI investment from an internal point of view and your business’s strategy perspective, you are now investing in AI from an external point of view based on what other businesses are doing.

I am not saying it is wrong to collaborate and get ideas from industry peers. In fact, this is one of the key reasons for attending conferences. To get informed about emerging trends and disruptive technologies and prepare for an uncertain future.

What is important is that you don’t allow competitor behaviours to drive technology investments in your business. Rather, clarify your business questions first, fix any broken processes before looking into technology and assess how the investment aligns with your overall business strategy.

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.

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