TagFinance Transformation

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?

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