Posts tagged: Finance Transformation

New Report on Finance Transformation From AICPA & CIMA and KPMG

In the past years, finance has been undergoing significant changes in order to streamline its operations and free up more time to partner with the business and support key decision-making processes that drive enterprise performance.

Sadly, not all finance transformation initiatives are achieving the expected outcomes or return on investment outlined in their business cases.

A number of theories are usually cited for these failures, and they include – talent struggles, thinking transformation is a one-time project, concentrating too much on cost cutting, focusing too much on customer satisfaction, lack of strategic alignment, inability to leverage technology in the right way, and insufficient leadership sponsorship.

But how many of these causes are real? We must be careful and not run the risk of focusing more on symptoms, critical though they may be, without getting to the underlying causes of breakdowns in transformation initiatives.

Catastrophic finance transformation initiatives can be prevented, but only if we start thinking about transformation in strikingly new ways.

For starters, this means putting aside the widely-held notion that finance transformation is all about new technologies and systems improvement, and start looking closely at the real causes of failure – the people who lead and implement the change.

People play a pivotal role in the success or failure of any business or organizational transformation initiative. But in an increasingly digital world, are organizations neglecting the people perspective as they work to transform their businesses?

Finance Transformation: The Human Perspective, a new publication from AICPA & CIMA and KPMG seeks to provide an answer to this important question and has some interesting content on why it’s time for finance to invest in its people. Here are some useful excerpts with my comments:

  • Under-investment in people can spell disaster for transformation programmes and the wider organization. As much as employees are responsible for preparing themselves for a new world of learning and work in which people will interact ever more closely with machines, employers should not take the back seat and relax. In fact, finance leaders should take charge and start now to envision what the future finance function looks like, the talent and capabilities that would be required to succeed in this brave new world, and come up with a robust action plan to close any gaps, and be future-ready. Unfortunately, most employers are involved in more talk and less action about the organization’s future talent needs, and it’s time to flip the scale upside down.
  • The key to success is developing the digital, technical and people skills that will bring out the best in the technology, maximizing insight, influence and impact. Machines cannot do everything. In order to achieve improved productivity, a range of human skills in the workplace, from technological expertise to important social, out-of-the box thinking, problem solving and emotional capabilities are also required. Therefore, train your teams to think of new digital tools as team members rather than as competitive threats.
  • Finance professionals must commit to lifelong learning and upskilling, so they can keep pace in this ever-changing business ecosystem. The authors are spot-on. Placing continued trust in the skills, capabilities, habits and behaviors we developed during our professional training to cushion us from this ongoing change is ill-advisable and quickly makes us irrelevant.
  • It’s people not robots, who are the key to better insights and analysis. Simply buying new technology doesn’t help you to truly transform. Technology is an enabler of change, and can be used both for good and bad. The type and quality of data that goes through machine analysis ultimately determines the quality of insights, recommendations and impact generated. Garbage In, Garbage Out. Hence the need to train people in business, data governance and translation skills so that they can monitor and understand where and how these technologies are deployed across the organization. Also, if your team is not equipped to use the new tools to perform their jobs better, then it doesn’t matter how shiny the new tool is because an opportunity to create value is immediately lost.
  • While advances like AI promise to change the way we work, it is easy to forget that new technologies are driven by human responses to a changing environment. Although certain old roles are being eliminated and new ones created because of AI, the goal should be to augment human and technology capabilities, rather than reduce the size of your workforce. Identify and differentiate which tasks humans and machines are best suited for. For example, in the context of prediction, humans and machines both have identifiable strengths and weaknesses, and it’s important to understand the extent of these otherwise your organization’s analytics and AI investments will fail to deliver the desired outcomes.
  • The ability to learn, evolve, think differently and understand quickly is just as important for individuals as it is for business. In today’s ever-changing environment the ability to learn, unlearn and relearn is going to be a key currency for finance professionals to hold. Allowing inertia to creep in and deciding to stick with the tried and tested approaches definitely hampers innovation and change.
  • As old systems and processes are superseded by new ways of working, we must learn to leave our legacy mindsets in the past. Finance transformation is not a series of projects, it is a change in the mindset of the organization. Thriving in today’s new world of learning and work requires organizations to adapt its workforce skills and ways of working. This means embracing a growth mindset rather than a fixed mindset. That which made the company successful in the past is no longer valued in the same way today. Understand that the rules of the game are continuously changing and thus you need to be adaptive.
  • Leaders have many roles to play; introducing and communicating the need for change, acting as a change champion and enrolling employees in idea generation. Efficient and effective change management is a result of leaders taking action rather than doing more lip service. Most leaders create playbooks to guide their managerial action, and sometimes as much as the world changes they firmly hold on to those playbooks. Rather than respond to their challenges and mistakes, or earnestly learn from the problems of their competitors, they continue unhampered in their quest for certainty, stability, and conformity. As a leader today, are you relying entirely on preconceived fixed notions about your organization’s talent needs while ignoring or rejecting any contrary signs?
  • The future is unpredictable; ensuring that finance teams have the right mix of digital, technical, business and people skills to deliver insight, influence and impact will be essential if organizations are to successfully navigate the uncharted waters. Since the level of uncertainty and complexity is intensifying and the rate of change also increasing, it’s critical for organizations to ensure that their workforce are equipped with the right skills and capabilities to perform their jobs better. Employers themselves stand to reap the greatest benefits (improved productivity, increased morale, innovative ideas etc.) if they can successfully transform their workforce. On the contrary, not acting right now or delaying action shuts down opportunities to adapt and change in accordance with the new demands.

The authors go on to discuss the various catalysts for transformation, current digital skills gap, and barriers to skills development.

I recommend you to read the entire piece.

Innovation in the Finance Function

Compared to other organizational functions such as Sales, Marketing and Supply Chain, the Finance function is often lagging behind when it comes to embracing innovation.

In today’s era of disruption and rapid technological advancement, the only way CFOs and Finance teams can ensure sustained relevance and create value across the enterprise is through innovation and reinventing themselves regularly.

Although companies have been innovating for years, these days the word innovation has become a cliche used to describe new, shiny feature-rich products, services, markets or breakthrough ideas.

According to the late Harvard Business School Professor, Clayton Christensen:

While all those are certainly characteristics of innovations, they are less helpful when trying to understand how companies and nations can organize themselves in ways that can truly foster growth.

Innovation is a change in the process by which an organization transforms labor, capital, materials, or information into products and services of greater value.

Applied to the Finance function, innovation is the process by which CFOs transform the function’s operating model, processes, talent, culture, and systems to eliminate inefficiencies, generate better insights about the business, and improve enterprise value.

Unfortunately, this change does not come about at the mere flip of a switch. In other words, transforming Finance from the traditional scorekeeper role, into a more strategic value enabler is more than an ideas game.

It’s easy to envision the future Finance function, but ideas are only ideas unless they are communicated across the enterprise and effectively executed through a well-crafted plan of action.

Failing is just part of the journey and a step toward figuring things out

New tools, systems and operating models continue to alter the way CFOs and their teams perform their tasks. For instance, advanced data analytical tools are enabling finance teams to collect, aggregate, analyze and generate actionable business performance insights from large data sets.

The challenge: even though CFOs are acutely aware of the need to imbue their departments with digital and analytical capabilities, quite a number are too afraid of making mistakes so they are shelving investments to avoid errors.

In some cases, most of them have also started figuring out what they need to do, but because they lack clarity on how to do so, and have heard stories about failed experiences at other organization, the innovative ideas are shelved too.

A thoughtful strategy is, of course, critical to success in nearly any business endeavor, and data and analytics initiatives are no different. However, just because other companies or your company have tested the idea before and it didn’t work should not blind you to the possibilities of the future.

Failing while moving forward at the same time is better than playing it safe. Rather than embark on a sweeping digital transformation from top down, start with use case pilots that will ultimately build into a tidal wave of change.

Create the environment

The widely held belief that leaders need to be experts and have all the solutions is incorrect. Am I therefore advocating for dumb leaders? No, great leaders understand their strengths and weaknesses.

They understand the difference between knowing and learning, and most importantly, make it a point to surround themselves with individuals and teams whose strengths complement their weaknesses.

In order to drive innovation in the Finance function, CFOs should create an environment that champions ideas, leverages strengths, organizes desired behaviours, rewards intelligent and informed risk-taking and celebrate failures.

Today, companies that are attracting and retaining the best employees are able to do so simply through empowering them to experiment with new ideas and focus more on engaging and meaningful work, in a lower stress environment, with a transparent reward system that makes sense.

Thus, it’s important as a Finance leader to get the message across to your team that failure is part of success in order to free the members from the innovation-limiting shackles of perfection.

Most successful initiatives follow the pattern that looks like this: try, fail, learn; try, fail, learn; try, succeed, repeat. You need to make this okay and let your team know that the real failure is fear of launching an idea until it is perfect.

You can’t read the label when you are sitting inside the jar

“But we have always done it this way” is one of the other obstacles to successful innovation in the Finance function. We get so used to doing our work in particular way that we become blinded to better ways of doing so.

In an era where collaboration between companies and business stakeholders is becoming a common practice, adopting both an inside-out and outside-in approach to innovation is essential.

This requires us to step back from our current standing position in order to connect the dots and gain context. We can achieve this through engaging non-finance teams across the organization, listening to their voice on the changes required and implementing the necessary changes.

Also involves forging connections for knowledge and ideation with experts around the world from outside the organization to create game-changing products and services.

Building an innovative and successful Finance function requires not only a mindset shift, but also execution and continuous iteration of ideas. Never be satisfied with the status quo, always question why you do it that way and figure out ways of how you can do your job better.

A Proactive Approach to RPA Adoption

In order to enable their team members to focus more of their time on higher value, higher satisfaction tasks demanding high levels of flexibility, creativity, critical thinking, problem-solving, leadership and emotional intelligence rather than repetitive tasks, CFOs are increasingly turning to RPA.

Short for Robotic Process Automation, RPA uses software to complete repetitive, structured, rules-based tasks to automate business processes at scale. It starts with simple, local tasks and scales up to enterprise-wide, intelligent automation, driven by machine learning and artificial intelligence.

In the finance function, RPA is being used to automate tasks that are of a repetitive nature and require tedious manual efforts.

Examples of such tasks include bank reconciliation process, sales ordering and invoicing, fixed asset management, financial and external reporting, inventory management, receivables and payables management, financial statement consolidation, tax planning and accounting, and forecasting.

Given the diverse applications of Robotics within finance, before introducing RPA into the finance function, it’s imperative for the CFO and everyone involved in the process to clearly assess and understand the benefits and risks attached.

Not every finance process is a good-fit for RPA

RPA implementation essentially depends on structured data and defined workflows. Thus, for any process to be a viable candidate for automation, the process must involve only structured, digital input and follow a rules-based processing approach.

Correctly identifying the process is therefore a critical step and holds the key to the success of any automation initiative.

However, the current plethora of new digital technologies and applications all promising to disrupt the way finance work is done is pausing a big challenge for finance leaders to separate hype from reality.

As a result, some leaders are deploying robotics into their operations simply due to a speed-to-market goal, resulting in missed benefits and unnecessary costs. When deploying RPA into finance, it’s not about following the herd or what your close competitors are doing.

Rather, you need to perform an objective analysis of your finance processes including an evaluation of which RPA tool or vendor relationship suits your unique needs. There is no one-size-fits-all solution.

Only a handful of processes can be neatly and entirely automated using an RPA tool alone. Therefore, it’s important to start your objective analysis with end to end process thinking because you will need to use multiple tools and techniques to realize the most transformative benefits.

Robotics tools are non-invasive

This means organizations do not need to make existing legacy changes when implementing RPA. The technology can be installed on any desktop or computer in a non-interruptive way with minimal IT involvement or coding abilities.

Because of this faster deployment, CFOs need not make the mistake that IT involvement is not required at all. Though RPA increases efficiency, it also brings with it the concern of system hacking and data breaches.

Also, platform security vulnerabilities, privacy implications and denial of service may yield ramifications that impact the RPA integrity, reliability and downstream business processes.

That is why it’s important to involve the IT from the upfront as the team plays a critical role of ensuring strong systems are in place to raise alerts of data breaches or process errors, and proactively remedy the situations.

Similar to every other system used in the organization, software bots need to be operationally managed and technically maintained.

Risk control and governance

Automation agendas are exciting and groundbreaking, yet intelligent and informed risk decisions surrounding their implementation need to be made to proactively create value and protect the business. As robots extract, aggregate, transform and upload data, risk and control considerations should become key discussion topics.

A robust governance framework should therefore be put in place to support the robotics deployment. The framework should succinctly address areas of concern such as approval of any system changes in case of process which have been automated, scalability, data storage and regulatory compliance.

The RPA tool should be capable of generating a detailed audit trail, highlighting any change or decision taken by the bot.

Just like humans whose performance is assessed, we should also be able to monitor and confirm the accuracy of the tasks being performed by the bots, reliability of the systems and adaptability to process changes.

Robust monitoring and security governance is critical to ensure all the tools and related infrastructure developed in RPA are compliant with IT security policies, regulatory provisions and risk policies across the organization.

CFOs and other leaders thus need to be aware and ready to deal with new complexities that could arise as a result of introducing robotics in finance.

Avoid putting the technology or tool ahead of your people

Many new technology implementation initiatives fail because decision makers leave people out of the equation. People decisions are often an after thought, secondary to technology decisions.

Implementing robotics is about driving operational efficiency, productivity, quality, customer satisfaction and more. These outcomes will not be realized if the key people who are meant to drive the change are not informed from the start.

As a leader, despite not having complete details about the final benefits of the initiative, you still need to communicate across the team why the organization has decided to bring about the change, what the ultimate organizational structure will look like after the change and the change impact on the existing employees.

People drive change and not technology. Reskilling of the employees who will be interacting and interfacing with the bots is therefore necessary for the overall success of the initiative.

In order to gain maximum benefits out of the automation exercise, have a long-term view and consider its strategic relevance to the business.

Engage employees throughout the organization and focus on automating cross-functional end-to-end processes across multiple stages instead of deploying RPA in pockets.

The Accuracy in your Forecast Matters More than the Forecast Itself

One of the roles of the FP&A function is predicting future business performance and help business leaders prepare for an unplanned future through forecasting and decision support.

Although anticipating the future is challenging given today’s fast-changing environment, looking ahead is increasingly essential.

The world is far, far more complex than we think. Unknown unknowns and known unknowns have replaced the routine, the obvious, and the predicted.

Resultantly, many of the assumptions on which important future business decisions are based are easily refuted with the passage of time. For example, one of the most common outcomes of the typical business planning process is a hockey stick forecast.

These forecasts usually show significant business growth and profitability prospects. The last few years of actual results are flat, and then magically shoot up for future years just like the blade of a hockey stick.

It’s a rare experience to come across a forecast that shows a downward spiral of business performance.

Businesses leaders often present a positive outlook of enterprise performance even if the odds of achieving their bold aspirations are slim. This is emblematic of human’s limited ability to accurately predict the future.

Tunnel vision

In his book The Black Swan, Nassim Taleb demonstrates how humans suffer from the delusion of knowing. We underestimate what the future has in store.

In the same manner, we tend to develop a tunnel vision while looking into the future, making it business as usual, when in fact there is nothing usual about the future.

Instead of acknowledging our unknowledge of the future, we continue to project into the future as if we are experts at it, using tools and methods that exclude rare events or outliers.

Although these rare events are most of the time external to the organization, they play a significant role in influencing the operational and strategic performance of the business.

The problem with many business performance forecasts is that they tend to focus on a single point destination or outcome, including a few well-defined sources of uncertainty ( known knowns) at the expense of others that do not easily come to mind.

The goal is not to predict or forecast all improbable events but rather to have an open mind and acknowledge that the likelihood of your actual future being different to your predicted future is considerably high.

Think of new products that failed to hit the mark with customers, projects that experienced cost overruns or took longer to complete, companies that failed to survive their forecast horizon etc.

The list of forecast horror stories is endless. I am sure in 2003 the thought of Lehman Brothers going under five years later was a laughable idea and outside the company’s projections.

Mitigating the tunnel vision

When it comes to forecasting, most of us adopt the inside view to assess the future performance of the business or any other project.

In other words, we tend to plan and forecast based on the information in front of us, neglecting some sources of uncertainty outside the plan itself. Daniel Kahneman, the well-respected psychologist has termed this WYSIATI – What You See Is All There Is.

As a result, we produce plans and forecasts that are unrealistically close to best-case scenarios. However, there are many ways for any plan to fail, and although most of them are too improbable to be anticipated, the likelihood that something will go wrong is high.

The cure for tunnel vision is taking an outside view of that which is being forecasted. Optimism bias often gets into the way of accurate forecasting leading to some of the horror stories mentioned above.

Thus, to avoid falling victim to optimism bias it’s important that you go through all the statistics of projects or initiatives similar to that being forecasted. This will help you identify an appropriate reference class and use the statistics to generate a baseline prediction which acts as an anchor for further adjustments.

Measure your forecasting error

Even though the world is complex and constantly changing, many planners are still adopting a simple view of the world as evidenced by their click and drag forecasts projecting into the long term future. Simply extrapolating projections from one year into the next is a mistake.

The accuracy of forecasts is more important than the forecast themselves. Do you attach possible error rates to your forecasts and measure the actual error rate after the forecasted horizon has passed? As the projected period lengthens, the larger the cumulative forecasting errors.

Despite evidence of enormous forecasting errors in the past, there is an ingrained tendency in us to ignore failure statistics and believe we are suddenly better at predicting the future compared to our uncomprehending predecessors.

Should we therefore discard predicting the future altogether? No, we first need to acknowledge that what we think we know about the future is not all there is. Our comprehension of the future is limited. From there on we can plan while bearing in mind such limitations.

In other words, we should stop overestimating our known knowledge about the future. We may be good at predicting the ordinary, but not the irregular, and this is where we ultimately fail.

Challenge of Finance Best Practices and What CFOs Should Do About It

The modern CFO is touted as the right hand man of the CEO, providing strategic and operational decision support. No longer is the CFO only responsible for preparing and interpreting financial statements based on historical accounting data, but also for taking a holistic view of business performance and helping the organization move forward.

Thanks to new technologies and improved business operating models, CFOs across industries have been able to transform finance into a value creation function. Further, finance leaders are overwhelmed with finance best practices advice from professional services firms, research analysts and consultants.

Finance leaders are advised to standardize ERP systems, adopt financial planning and analysis technologies and ditch spreadsheets, streamline budgeting processes and implement driver-based rolling forecasts, automate and accelerate financial close and reporting etc.

The list is endless, but does a complete reliance on best practices advice improve finance’s performance and value creation?

Best practices and benchmarks are meant to help business leaders assess the progress of their companies against “leading performers” as opposed to being aspirational ideals to be attained.

The challenge with viewing best practices as standards of excellence is that, their attainment might mistakenly be interpreted by business leaders that no further effort, experimentation or thought is required.

By their nature and application, best practices are transitory. Given today’s business world which is constantly changing – practices, processes, systems and operating models that have enabled us to drive business performance are no guarantee of future success.

CFOs therefore have to realign their functions if they are to keep pace with the demands of an increasingly dynamic marketplace. Always keep in mind that best practices are only beneficial as long as the circumstances in which they are established remain stable.

Unfortunately, volatility and uncertainty are the norm today.

As a finance leader, you should be weary of copying best practices from other businesses with little adaptation otherwise you risk stagnating creativity and commoditizing innovation across the organization.

Rather than continue to depend on the widely accepted best practices, CFOs need to adopt a new mindset, break old habits and promote a continuous improvement culture.

Many at items promising ideas never experience the light of the day because the culture management has created rewards success and punishes failure. Leave some slack for experimentation and encourge constructive failure.

Simply following a complete set of rules or principles will not, on its own, drive finance function effectiveness. Before jumping at the so called best practices, at least ask yourselves:

  • How are we doing what we are doing now?
  • Why are we doing what we are doing this way?
  • What would it look like if we didn’t do things this way?
  • Who expressed this is the best practice?
  • Why is it considered best practice?
  • Does the best practice work for our business?
  • Is the best practice still valid or outdated?
  • Under what circumstances was the best practice established?

Answering the above questions will help you validate the best practice and its potential to boost organizational performance.

Adopt ideas, processes, technologies, and skills that drive change and create value. There is no hard-and-fast playbook. In a culture of innovation, new ideas spring forth from all directions, especially from the unexpected sources.

Just because the organization’s existing structures, systems, skills and processes are driving performance today does not mean they will continue to do so in the future. The past is prologue but not necessarily precedent.

Finance leaders who continue to find comfort in implementing widely accepted best practices to secure competitive advantage or embrace “this is how we have always done it” approach in today’s increasingly uncertain world are not only squandering resources but also destroying value.

Human or Machine Intelligence? Augmentation Key to Better Forecasting

Forecasting is an invaluable process for any business. A forecast can play a significant role in driving company success or failure. For example, high forecast accuracy helps a business anticipate changes in the market, identify growth opportunities, reduce risks, analyze  root causes of performance and proactively respond.

On the other hand, forecasts that are poorly designed, based on weak assumptions often result in unintended consequences.

Preparing highly accurate and reliable forecasts to support decision making is one of the major challenges faced by performance management teams across sectors and industries.

Traditionally, business performance forecasters have relied on past performance to predict future performance. In a perfect, static world the formula works well. However, as we all know the world is not static. The only thing that is constant is change.

Volatility, uncertainty, complexity and ambiguity are at an increasingly alarming level. Further, new technologies are transforming how we do our work now and in the future.

A number of manual processes have successfully been automated. Where businesses have previously relied on financial data alone to make strategic decisions, the dawn of the digital age has brought new meaning to non-financial data.

The new world of algorithm-powered machines

The traditional approach of forecasting is highly manual and time-consuming. People spend a significant amount of time gathering, compiling and manipulating data in spreadsheets.

Most of the time, the data used to predict the future and create forecasts is historical financial data residing in the company’s ERP systems.

Unfortunately, in today’s rapidly changing world the future doesn’t sufficiently resemble the past.

As the new digital era continue to unfold, more and more data (financial, operational and external) will increasingly become available to support business forecasting.

Given that the traditional approach of forecasting leverages data in structured format to prepare forecasts, with more and more unstructured data available, CFOs and their teams have to rethink the old school forecasting process.

In order to increase the agility of the business to proactively respond to competitor activities, customer, market and industry changes that threaten the achievement of set objectives, or trends that present specific opportunities, the organization should consider all types of data at its disposal and discern what is important and what is not for business performance forecasting purposes.

Artificial Intelligence, machine learning, deep learning and natural language processing are disrupting traditional business operating models and companies are increasingly tapping into these new technologies to drive forecasting processes. These highly powered machines use statistical algorithms and modern computing capabilities to collect, store, and analyze large quantities of data and predict what is likely to happen in the future.

The algorithms are fed with warehouses of historical company and market data and taught to mimic human intelligence. Overtime, through learning, forecasting accuracy is improved.

In addition, NLP algorithms are able to go through a myriad of documents including articles, social posts and other correspondences written in plain text and extract insights that can be injected into the forecasting model.

Humans and machines augment each other

It is no secret that machines have a superior advantage over humans when it comes to collecting, storing and analyzing large data sets in real-time. But does this imply that decision makers should rely exclusively on machine intelligence to drive business decision making? The simple answer is no.

When it comes to applying critical thinking and judgement, human beings are much better than machines. Humans are able to evaluate and translate the machine’s conclusions into decisions and actions. Take for instance the forecasting models that are used to predict the future, the best source of information for these models are the domain experts for whom the models are designed.

The domain experts have a better understanding of the models, what assumptions to base the models on including the ability to uncover flaws that others may miss. Software developers, data scientists, AI experts and automation engineers, among others rely on expert judgement of domain experts to hard-code data features in databases that are used to train predictive algorithms.

In one of my articles, Applying Design Thinking to Finance, I highlighted how companies are heavily dependent on analytical thinking in order to drive business performance.

The solution is not to embrace the randomness of intuitive thinking and avoid analytical thinking completely. The solution lies in the organization embracing both approaches, turn away from the false certainty of the past, and instead peer into a mystery to ask what could be

The fact that the past is not a reliable predictor of the future does not necessarily mean that it is not important. History has been known to provide major lessons to us. In the same manner, human judgement can be used to determine which historical data is suitably representative of the future to be included in forecasting decisions.

When data is abundant and the relevant aspects of the business world aren’t fast-changing, it’s appropriate to lean on statistical methods to prepare forecasts. However, even after the forecasting model has been designed and adopted, human judgement is still required to evaluate the suitability of the model’s prediction under different scenarios.

Important to note is that predictive models do no more than combine the pieces of information fed to them. These machines are good at identifying trends and imitating human reasoning. If bad or erroneous data, or good but biased data is presented to the algorithms, issues can arise.

Setting aside human biases

People make decisions based on logic, emotion and instincts. One of the challenges of preparing forecasts in a complex and constantly changing world is setting aside human biases.

Subconsciously, human beings have a tendency to base judgement and forecasts on systematically biased mental heuristics rather than vigilant assessment of facts. System 1 Thinking.

According to Daniel Kahneman in his book Thinking Fast and Slow:

  • System 1 is an automatic, fast and often unconscious way of thinking. It is autonomous and efficient, requiring little energy or attention, but is prone to biases and systematic errors.
  • System 2 is an effortful, slow and controlled way of thinking. It requires energy and can’t work without attention but, once engaged, it has the ability to filter the instincts of System 1.

Personal experiences built overtime make us overgeneralize facts and jump to conclusions. Instead of focusing on both existing and absent evidence, we act as if the evidence before us is the only information relevant to the decision at hand.

As a result, the risks of options to which we are emotionally inclined are downplayed, and our abilities and the accuracy of our judgement are also overestimated.

Further, a focus on the limited available evidence causes us to create coherent stories about business performance including causal relationships that are non-existent. We are quick to ignore or fail to seek evidence that runs contrary to the coherent story we have already created in our mind.

Such actions do not result only in overconfident judgement but also cause us to be overly optimistic and create plans and forecasts that are unrealistically close to best-case scenarios.

By addressing own cognitive biases and enabling collaboration between humans and machines, business forecasters will be empowered to create forecasts that enable faster and more confident decision making.

Machines can only assist and not displace the typically human ability to make critical judgement under uncertainty.

Applying Design Thinking to Finance

I recently finished reading The Design of Business: Why Design Thinking is the Next Competitive Advantage by Roger L. Martin. It’s well worth reading. Even though the book was published almost a decade ago, the ideas and principles espoused by the author are still relevant and applicable in today’s business environment.

Design thinking is a customer centric process used by designers for creative problem solving. The process utilizes elements from the designer’s toolkit like empathy, intuition, systemic reasoning and experimentation to arrive at innovative solutions that benefit the end user or the customer.

Finance is increasingly being called upon to provide effective business decision support. For many traditionally trained accounting and finance professionals, the request is a big ask.

Understanding and influencing the entire value creation cycle of the business is not something that they are accustomed to. Instead, many accounting and finance teams are comfortable working in financial reporting roles.

However, as businesses increasingly leverage new technologies to automate rules-based, transactional and repetitive tasks for a fraction of the full time employee salary, it’s only a matter of time before some finance team members become an endangered species.

Part of the problem is the fact that during our training, the majority of the courses we undertake make us believe that our core role is to deliver compliance-focused tasks.

Think of Financial Reporting, Taxation, Auditing and Assurance, Business Law, and Financial Accounting modules. All are compliance-focused. At the beginning of the learning, the content of each module is the basics and progresses into advanced topics towards the end.

Ultimately, we develop a box-ticking mindset. Having such a mindset will not help differentiate the business from its competitors and create a competitive advantage. I’m not discounting the importance of financial reporting or any other compliance tasks.

They too are important. But, innovative and successful companies do not become so simply by heavily investing in compliance activities.

Innovation and efficiency do not have to be at odds

In The Design of Business, Roger L. Martin highlights that one of the reasons many businesses face a struggle to innovate and create value for their stakeholders is because of an increased reliance on analytical thinking versus intuitive thinking.

The former involves senior management attempt to base strategy on rigorous, quantitative analysis (optimally backed by decision support software). The later is centered on the primacy of creativity and innovation, the art of knowing without reasoning. Roger Martin does not advocate the adoption of one approach over the other. Instead, he advises businesses to seek a balance or reconciliation of the two.

Traditionally, finance transformation initiatives are driven by cost reduction strategies. The focus is on squeezing out as much fat as possible and achieve efficiency. Take adoption of new finance software as an example. Rather than view the adoption as an opportunity to relieve finance teams of rudimentary tasks and focus on initiatives that require critical thinking, CFOs view this as an opportunity get rid of employees and cut costs.

If a business is heavily dependent on analytical thinking, especially where performance and rewards are budget and or forecast driven, maintaining the status quo often prevails. The organization finds itself operating as it always has and is reluctant to design and redesign itself dynamically over time.

When faced with a decision about investing in a new product, market or something new and promising, but not in the current budget, the answer is always no. Many at times the argument is that if something cannot be planned and budgeted for in advance, it is not worth pursuing. This ultimately breeds conformity and stifles innovation as resources are allocated to business units based on past performance.

Finding a balance between exploration and exploitation

Balancing innovation and efficiency demands the organization’s resource allocation not to be based entirely on past performance. Rather, a portion of the resources should be distributed based on the unproved ideas and projects each business unit presents for the coming year.

One of the reasons why a number of promising projects fail to see the light of the day is because management have created a culture that first seeks a predictable outcome before paving way for the project. They seek reliability, which is in direct contrast to a designer’s mindset.

A designer seeks validity over reliability with the goal of producing outcomes that meet a desired objective. The end result is shown to be correct through the passage of time.

The current business environment is awash with mysteries, which take an infinite variety of forms. For example, we don’t know how our product and market segments will continue to perform in future. We are not certain which technologies will have an immediate impact on our business. Or we might explore the mysteries of competition and geopolitical tension.

Data on past performance might help us extrapolate future performance but the future is no guarantee.

Given that the future is a mystery, the business should embrace a new way of thinking that provides a simplified understanding of the mystery and in turn help devise an explicit, step-by-step procedure for solving the problem.

An organization may decide to focus on exploration, which involves a search for new knowledge and the reinvention of the business, or exploitation which focuses on business administration and seeks to increase payoff from existing knowledge.

Intuition, originality and hypotheses about the future are often the driving forces behind exploration. On the other hand, analysis, reasoning, historical data and mastery are the forces behind exploitation. Both approaches can create significant value, and both are important to the success of any business organization. However, organizations struggle to pursue both approaches simultaneously.

More often, an organization chooses to focus on exploitation, to the exclusion of exploration and to its own disadvantage. The solution is not to embrace the randomness of intuitive thinking and avoid analytical thinking completely. The solution lies in the organization embracing both approaches, turn away from the false certainty of the past, and instead peer into a mystery to ask what could be.

In other words, balance exploration and exploitation, invention of business and business administration, and originality and mastery.

Finance plays a critical role in helping the business achieve efficiencies, redeploy the savings and redirect freed-up resources towards exploration of new opportunities.

Building design into finance

As design thinking is frequently associated with marketing and product development, finance is deemed an unlikely place to apply design thinking principles. However, design thinking can be applied to the finance function in every organization. The key is to identify and define the customers clearly and approach their needs empathetically.

Unlike the marketing function which focuses its efforts on external customers, finance’s efforts are focused on meeting the needs of its internal customers. To elevate design thinking in finance, the function should think differently about its structures, its processes, and its cultural norms.

Quite a number of finance organizations are organized around ongoing, permanent tasks. Roles are firmly defined, with clear responsibilities and reward incentives linked tightly to those individual responsibilities. The problem with such a structure is that it discourages employees to see the bigger picture. Individuals employees see their work as own territory to be protected by all means.

There is little to none collaboration. It’s all about “my responsibilities,” not “our responsibilities.” As a result, individuals limit their focus to those individual responsibilities, refining and perfecting outputs before sharing a complete final product with others. This can be routine production of monthly reports.

In contrast, designers are accustomed to working collaboratively with adhoc teams and clearly defined goals in a projected-oriented environment. Rather than waiting until the outcome is right, designers expose their clients to a series of prototypes that improve with each iteration.

Considering that finance business partnering extends beyond traditional month-end reporting tasks and involves working on various business related projects, sharing performance insights and creating value, CFOs should therefore foster a culture that supports project-based work and explicitly make it clear that working on a project is no less important or rewarded than running a business segment.

It is therefore imperative that finance business partners acquire design thinking capabilities that can help them develop a detailed and holistic understanding of their internal customers’ needs and frustrations, and serve them better by formulating and recommending creative and actionable solutions that deliver the desired outcomes.

Equally important too is having the courage to elicit feedback from business partners, develop mastery of the value proposition model and deliver improved solutions.

Rather than immortalizing the past, the focus should be on creating and influencing the future.

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?

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.

3 Common Pitfalls of Performance Reporting and How to Avoid Them

Recently I met up with a close friend of mine whom I hadn’t seen in a couple of years for a chat and catching up. He is a qualified accountant and finance professional working in the financial services industry in Zimbabwe.

On top of the social chatter, we started discussing the evolving role of finance, in particular finance business partnering and the impact of Industry 4.0 on the profession.

As our discussion continued, we shared experiences, what has worked and what hasn’t worked so far in our respective organizations, as well as the way forward.

One thing that intrigued me was that my friend didn’t by any chance try hard to hide his frustrations emanating from his every day job. Chief among the frustrations was the fact that finance wasn’t highly regarded within his organization as he would have loved it to be.

I probed further trying to understand why he had reached to that conclusion.

Although my friend mentioned that his organization has made reasonable progress in ensuring that finance transforms from the commonly perceived scorekeeper function to a trusted business partner, many business leaders still perceive finance’s role as that of balancing books and providing rudimentary analysis.

As a result, finance is not invited to the decision making table and asked for its contribution.

Keen to find out why business leaders didn’t see any value in engaging finance in the operational affairs, I asked deeper questions until we both agreed that his team was clogging business partners with too many performance reports, his organization lacked a clearly defined data management model, and finance personnel need to be empowered to collaborate with the business effectively.

Far Too Many Reports and Far Too Little Insights

As it turns out, it’s not only business leaders in my friend’s place of work who are constantly being weighed down by a mass of performance reports. There are plenty.

With the volume of both internal and external data increasing exponentially, the demand on finance teams to provide insightful, relevant and timely management information to support fact-based decision making isn’t going down either.

Because of this unrelenting demand for more information it is easy to succumb to the thinking that more is better, resulting in finance teams working round-the-clock to produce reports that neither meet the requests of stakeholders nor offer the business an informed, value-adding view of its performance.

The problem with having too many reports is that the business is forced to track and monitor far too many metrics which, in most cases, are in conflict with one another and offer far too little insight.

Additionally, the business lacks a clear line of sight to clearly analyse past and anticipated performance in order to make better decisions. In today’s exponentially growing data age, decision makers are looking for essential information to make more confident and effective decisions that focuses their attention on activities that truly matter, and provide a consistent view of performance across the business.

To avoid this common pitfall of repeatedly creating useless performance reports that no one dares to read, finance needs to regularly engage with business leaders and take time to clearly understand what information they actually need to achieve their strategic objectives and consequently drive value.

Delivering this information in an efficient and effective manner is key to finance generating business trust as well as empowering the business to proactively respond to emerging opportunities and threats.

Lack of a Robust Data Governance Framework

After seriously discussing the problem of too many performance reports, my friend further raised an important question. What if a business leader requests a specific report and we do not have all the necessary information to adequately support our findings? Before answering him, I fired a question back at him. How are you currently handling these requests?

To my complete surprise he responded, finance produces reports that we believe are correct and if we do not hear back from the business leader all is considered in order. At this point in time, I was quickly reminded of the expression Garbage In – Garbage Out. No matter how logical our thinking and analysis is, as long as the inputs are invalid the results will be incorrect.

The same applies to business performance reporting. In today’s data-driven and tech-enabled economy, optimized and appropriate use of data is central to helping the business make enhanced decisions, create competitive advantage and successfully execute its strategy.

Thus, data quality is imperative, requiring finance leaders to ensure that there is absolute trust in the information provided to the business.

From discussing with my friend, it became clear that a business requires the right data to support its integrated set of defined key performance indicators (KPIs) and to maintain the integrity of this data, it must be supported by a robust governance structure.

Today’s volatile and dynamic business environment means the organization’s strategic priorities are always changing, as well as its information needs. As a result, the reporting function also needs to keep pace with this constantly changing landscape.

Building a cohesive information and data governance framework ensures common KPIs linked to strategic and operational decision making are used consistently across the business.

KPIs, regardless of their focus are only as consistent as the underlying data, and poor data input will produce inconsistent measures, even if they are labelled as the same KPI. This is why getting the basic data structures and data feeds right is so fundamental in providing decision support that can be trusted.

Additionally, due to the fact that different functions of the business use data for multiple different information needs, a robust data governance framework leads to a single version of the truth via enforcement of consistent information standards, creates awareness of where the performance data is housed and how it can be accessed.

Since the main goal of performance reporting is to provide management with real-time information with proactive comparators, a constant review of the information requirements and data governance framework ensures that performance measures remain relevant.

What I also picked up from my friend is that despite significant growth in the potential use of external data to drive better decision making, many businesses remain predominantly reliant on internal data to drive key business performance decisions.

They are grappling to incorporate this type of data across different business processes, mainly because of the differences in the structure of internal and external data sets.

By incorporating external comparators in their decision making processes, management will be able to identify areas where the business needs to ramp up through investments, and often more prominently, where it is already ahead of the competition, but must continue to focus on to uphold or create a new advantage.

Without this crucial information at their disposal, it is impractical for finance teams to clearly understand the major drivers of their business performance, produce insightful analysis, partner with key decision makers and support strategic decision making.

Business Leaders Discounting Finance’s Capabilities

In order to become effective business partners and provide relevant decision support it is imperative for finance teams to get as much exposure as possible to business-wide decision making. Unfortunately, getting this exposure remains a distant dream for many capable finance teams.

Because business leaders see finance personnel only as gatekeepers and not strategic business advisors, there is little motivation on their part to empower finance to collaborate effectively with the business on a larger scale.

As we started discussing the promises and perils of Industry 4.0 with my friend, he was very much surprised with how far behind his organization is in terms of digital transformation and process automation.

My friend is not alone on this boat; many finance teams are still stuck with legacy financial systems, tools and processes; spending a significant portion of their time on low value-adding transactional activities such as arduous data extraction and manipulation or traditional month-end activities, and little time on positive analysis and decision support. This is detrimental to effective performance reporting.

Performance reporting will only succeed if finance teams are suitably equipped to deliver high-quality insights that support decision making empowered with deployment of reporting technologies.

Even if the business presents an opportunity to collaborate, time alone is not sufficient. There is also a need to create an environment that allows finance people to develop appropriate capabilities, some of which may not come innately to many technical finance people.

One way of fostering this environment involves running finance training programmes that focus heavily on softer skills such as leadership development, communication, change management and stakeholder management, as well as on-the-job training for traits such as commercial acumen, and less on the technical or transactional processes which are easy candidates for automation and do not constitute a large portion of finance’s everyday job.

As with any other form of investment, the organization must be able to reap rewards from the training programmes. It makes no economic sense to spend substantial amount of resources trying to boost finance function productivity and in turn get rewarded with mediocre results.

It is therefore critical that finance personnel sent out for training exhibit the right behaviours and have the confidence to work with the business to interpret reports and constructively challenge strategic decision making to drive more effective decision making.

This in turn will assist finance shed its image as a mere service provider, elude mundane tasks, enhance its reputation and become part of the decision making crème de la crème informing business decisions with deep insights and recommendations.

In addition to training programmes, the organization also needs to invest in appropriate enabling technology that help with data analysis and interpretation in real-time, providing the organization with the necessary speed and quality that it requires to stay ahead, as well as allowing finance to demonstrate their analytical skills and become more influential as business partners.

Addressing the above common pitfalls is key to streamlining an organization’s performance measurement and reporting processes, and ensuring that senior management regularly receive relevant, insightful and near real-time information necessary to improve strategic decision making and ultimately business performance.

What other common pitfalls have you experienced in delivering high-quality performance reporting?

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