categoryBudgeting and Forecasting

Reimagining Forecasting in Uncertain Times

One of the key purposes of forecasting is to help organizations continuously anticipate the future, assess its likelihood, consider the implications and use all the available information and practical techniques to make confident decisions that maximize the potential of the business and improve enterprise performance.

Of course, this is not an attempt to simply predict and control the future as no one is capable of predicting the future with certainty. Instead, it is about building an effective and efficient process that enables decision makers to evaluate alternative courses of action available to them to respond quickly to known knowns, known unknowns or unknown unknowns when they happen.

The novel coronavirus pandemic which started in Wuhan, China and rapidly spread across the globe has killed thousands of people, caused world’s markets to plummet, disrupted global supply chains, and forced non-essential businesses to temporarily or permanently shut down.

Operational and financial forecasts that a few months ago painted a rosy picture of the future have had to be thrown out of the window because of the Covid-19 crisis. Companies have come out in droves and announced revised earnings and profit estimates.

Several governments, academics, research bodies, businesses, and other organizations were caught unaware by this outbreak – demonstrating our inability to predict the future. Considering our inadequate forecasting capabilities, should we therefore abandon forecasting completely? Can we confidently say forecasting is a waste of time and resources? The answer to both questions is a resounding ‘No’.

In order to make confident, reliable and timely decisions, decision makers require information about the past and information about the future. Absent this information, or it is deficient or misleading, then decision-making on key organizational performance matters is no more than guesswork.

Unfortunately, in today’s increasingly unpredictable, uncertain and rapidly evolving world where things can happen at lightning speed, anchoring important future business decisions on historic information alone can misinform decision-making resulting in lost opportunities and catastrophic business failure.

While it’s imperative to understand business trends, it’s also important for management and decision makers to appreciate that they cannot simply rely on the past to guide them in the future given their role is to make the future different to what it otherwise might be.

Forecasting is not supplementary to the annual budget

The traditional annual planning and budgeting process is certainly fraught with many shortcomings and for most organizations it is completely dead. Outdated and meaningless. Most businesses spend several months each year agreeing the budget and then monitoring actual performance against it.

They plan for a desired future in order to make it come about. Any deviation from budget or the initial plan is regarded as a variance and is therefore wrong. But many times, changes in the business environment invalidate the assumptions on which they based their original plan and quickly render the budget obsolete.

The budget is next updated with a forecast with a horizon that declines as the reporting calendar moves towards the fiscal year end. As a result, decision makers have limited visibility about the company’s future considering they are ill-equipped to look beyond the twelve-month planning horizon.

In one of his CIMA FM Magazine articles If the Coronavirus Outbreak Disrupts Your Budget, Bjarte Bogsnes reminds us:

In the world of business today, there is more on a long list of things that we can’t control. The only thing we know about our budget assumptions for next year is that most of them will be wrong.

In such an unpredictable world, we shouldn’t expect budgeting to produce predictable results. It assumes that we can sit down in the autumn and decide everything for next year — what to earn and what to spend and invest, all laid out at the lowest detail level. We believe this gives us control. It gives us nothing but an illusion of control.

CIMA FM Magazine, March 2020

So unlike in budgeting where we consider a single desired future outcome, in forecasting we know the future might not come about because the assumptions might be wrong or have been changed. Thus, instead of continuing on the same path based on existing assumptions it’s imperative that we quickly change course if we are to avoid a catastrophic iceberg crash.

Remember, the purpose of forecasting is not to predict the future with certainty but rather support decision-making. A good forecast highlights a projection of the future with some ranges around it, an informed and reliable explanation of what is driving uncertainty and a cogent plan for the business to mitigate emerging risks or exploit the opportunities.

Talk about possibilities and probabilities, not certainties

In Super Forecasting: The Art and Science of Prediction, Philip E. Tetlock and Dan Gardner shed light on the dangers of organizing our thinking around Big Ideas, whether true or false, when making forecasts. In this scenario, we tend to force complex business problems into preferred cause-and-effect templates and treat those that fail to fit as irrelevant distractions.

As a result, we get awfully confident and less reluctant to change course even if changes in the external environment are clearly nudging us to do so and have invalidated our initial assumptions and projections.

Since we never pause to evaluate whether the evidence at hand is flawed or inadequate, or if there is better evidence elsewhere we suffer from an illusion of knowledge or what Daniel Kahneman termed WYSIATI – What You See Is All There Is.

The problem with zoning on one Big Idea is that it distorts and doesn’t improve our foresight. Instead of viewing and processing new information with a fresh pair of lens, the additional information received is treated as unhelpful because it’s all seen through the same old pair of tinted glasses.

In forecasting, there are no certainties but rather possibilities and probabilities. To be able to produce accurate enough forecasts, it’s critical that we deploy not one analytical idea but many and seek out information not from one source but many. Then consider and aggregate alternative views.

Generating different perspectives (that is coming up with an outside view and inside view) of the business and integrating the two isn’t the end but a good beginning. It helps us understand what other forecasters think, and also what outside and inside views they have come up with.

Nonetheless, since teams constitute of individual members with different educations, training, experiences, and personalities – a smart leader should not expect consensus of opinion at all times but must treat its appearance as a warning flag that group-think has taken hold.

On the contrary, a display of differing judgments should be welcomed as evidence that the people around the table are actually thinking for themselves and offering their unique perspectives.

Forecast, measure, revise. Repeat

How predictable something is depends on what we are trying to predict, how far into the future, and under what circumstances. The further we try to look into the future, the harder it is to see.

In business, finance organizations rely on robust models to churn out short, medium and long-term financial estimates on company performance. And most of the time after forecasts are produced we hardly measure our forecasting performance and improve the quality of our forecasting process accordingly.

All forecasts contain some level of variation or unsystematic error, but a reliable process maintains this variation at acceptable levels for the purposes of the decision business leaders need to make. Without measurement, there is no revision. And without revision, there can be no improvement.

Certainly, this does not imply setting arbitrary targets such as plus or minus 5%. This approach of measuring the difference between actual and forecast outcomes and expressing that as a percentage is flawed. One of the reasons being that errors are assumed to be evidence of poor forecasting, and success in meeting the numbers is viewed as good forecasting.

Forecasts must have clearly defined terms and timelines. People attach very different meanings to vague verbiage like “significant market share,” “certain,” “seriously possible,” “a fair chance,” and “likely.” Such ambiguous language renders forecasts untestable. The same holds true for forecasts (economic) that claim undoubtedly that something will or won’t transpire in future but fail to explicitly define the time frame.

In their work Future Ready: How To Master Business Forecasting, Steve Morlidge and Steve Player further highlight the importance of comparing ‘like with like’ when measuring forecasting performance. That is, we should not attempt to compare the results from forecasts produced using different time buckets.

For example, comparing the actual for Quarter 1 with forecasts made at the end of December, January and February. Neither can we compare a forecast for Quarter 4 made in January with a forecast for Quarter 4 made in June. Although the time buckets are consistent, the forecast lead times are not the same.

We therefore should measure forecast error within forecast lead times using consistent buckets and consistent forecast lead times.

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.

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.

How Effective is Your Budgeting and Forecasting

The only thing right about a forecast is that it’s wrong. This unavoidable truth is particularly evident in business today. Businesses are grappling with high levels of volatility, uncertainty, complexity and ambiguity.

Increasing regulation, competition, geopolitical tensions, ever changing consumer preferences and a shift in economic powers are making it difficult for finance teams to predict business performance with certainty.

Although no forecast is 100% certain, forecasting is not a futile process. Today’s complex and fast paced environment demands agility, flexibility and confident decision making. Making use of dynamic forecasts to support key operational and strategic decisions can help businesses overcome these challenges.

Single Point Destination

Budgeting, planning and forecasting must evolve into something more relevant to today’s operating environment.

Many organizations prepare budgets to estimate single-point future outcomes and allocate resources required to meet specific goals. Although this works well in a stable environment, this is far from true in today’s unstable world.

Emerging risks and opportunities are forcing the business to regularly re-examine its value proposition model and adapt its strategy. At the same time, the resources required to deliver superior performance are highly volatile and unpredictable.

As a result, goals are often becoming moving targets requiring regular monitoring and adjustments.

This raises the need to adopt modern FP&A processes that empower the business to evaluate performance beyond a specific point in time and swiftly respond to external and internal fluctuations.

The annual budget fails to make the business become forward-looking and plan beyond the 12 month period. On the contrary, continuous rolling forecasts help decision makers to:

  1. Focus more on the future rather than on the past
  2. Model future scenarios based on current business drivers
  3. Get insights in terms of where the organization is heading
  4. Highlight significant gaps between expected performance and defined budget targets
  5. Make informed decisions that are reflective of the business operational environment

Basing future decisions on a single point of view in today’s constantly evolving environment is not ideal. Decision makers should consider a range of potential outcomes, to better represent and understand possible scenarios.

Link Risks and Opportunities 

Many budgets that companies are using are prepared from a numbers perspective only.

The norm here is to pull out past financial results, add or deduct a percentage amount to the chart of accounts line items. In most cases the numbers are dependent on inflation, interest, foreign exchange and GDP statistics.

Other performance drivers specific to the business such as category growth, market share, consumer behaviour, supply chain risk, website traffic, conversion rates and production capacity are often not considered.

Take for example the impact of social media today. Social media is increasingly empowering consumers granting them more buying power. Brand and user experiences are shared 24/7 on these platforms.

Brands that are able to align their value delivery models with consumer expectations stand to benefit above peers in terms of reputation and financial rewards.

As social media continues to provide a communication platform for consumers, it is vital that companies factor in social media risks and opportunities into their financial planning and analysis models.

Building new capabilities capable of integrating and interpreting multiple sources of data and business drivers is the first step towards progress.

Complex Spreadsheets Standing in the Way of Progress

To succeed in a hyper-competitive environment, the business must be able to make informed decisions and move on with speed. This requires the company to incorporate a flexible budgeting and forecasting framework that helps it to instantly develop and analyze different scenarios.

A lot of companies are incapable of producing this analysis quickly, mainly because the majority of systems in place are not essentially fit for purpose. Complex spreadsheets only the creator understand are dominant.

Challenges arise when individuals attempt to add additional budget and forecast line items or change formulas and are unable to do so. The file is sent back to the creator for amendments.

This review-revise-redistribute cycle increases data latency and slows down decision making.

Finance should replace complex spreadsheets with new collaborative technologies. This will help streamline and standardize FP&A. Cloud solutions improve collaboration and response times between users, enhance governance and control by reducing version control problems. Also, the likelihood of input errors getting unnoticed is reduced.

Centralizing budgeting and forecasting across the business ensures that inputs to the process follow common standards and classifications. This reduces the need for people to add additional budget and forecast line items, helps track progress across all business areas and enable easy re-forecasting without changing the entire model.

Given this current world of advanced analytics and IoT, machines keep on getting smarter. Leveraging improved computing power, they are now able to aggregate large data sets, identify patterns and correlations and inform predictions within shorter time frames.

Although adoption of emerging technologies is not yet mainstream, the potential for companies to augment human and machine capabilities and shift from reactive to anticipatory driver-based planning is massive.

Budgeting and forecasting transformation is not achievable overnight. Learn from past failures and understand why a prediction went wrong. The idea is not to seek certainty, but rather to influence the future.

Instead of setting the organization on a particular path, Finance should focus on identifying a range of potential outcomes and help decision makers make rational strategic decisions based on the most plausible set of scenarios.

Rethinking the Annual Budgeting Process

Human beings are creatures of habit. Once they have mastered certain habits, especially bad ones, it is extremely difficult to let go. Even though we are fully aware that the immediate, medium-term or long-term consequences of our bad behaviours are dire, we still cling unto them. Could this be because of our ignorance or maybe lack of understanding of what is at stake?

The annual budgeting process has been around for a very long time, and organizations across the globe have been using budgets to allocate scarce resources, monitor and manage performance. In a perfect stable world, the annual budget process works. Unfortunately, a stable economic environment is a thing of the past.

Volatility is the norm today

In the majority of organizations that operate an annual budgeting cycle, the final budget is fixed in nature, covering a specific time period. Finance executives and business managers spend a significant amount of time inputting and debating the final budget. As soon as the final budget figures are agreed, IT department uploads the budget on the company’s accounting and finance system. Nothing changes after this, except comparing actual performance to budget.

The challenge for many finance executives is which approach to use to prepare the budget. Base plus or zero base? Many make the grave mistake of using prior year’s actuals as the base for formulating the current year’s budget and then make arbitrary adjustments. This approach is acceptable in an environment where market conditions are stable, predictions are easy to make and key budget assumptions remain valid for the entire budgeted period.

Unfortunately, volatility is the norm in today’s global economy. Increasing global pressures, uncertainty, ever-changing consumer behaviours and disruption are all rendering initial key budget assumptions invalid by the time the final budget is completed.

The result is often an outrageously inaccurate budget with little management commitment and minute relevance to the organization’s strategic plan.

This new dynamic global economy calls for modern approaches to budgeting, planning and forecasting. Organizations need to be adaptive, ever ready for unpredictable events and quickly responsive to changing marketing conditions.

In his book Thinking, Fast and Slow, Daniel Kahneman talks about the Knowing Illusion.

The core of the illusion is that we believe we understand the past, which implies that the future also should be knowable, but in fact we understand the past less than we believe we do. What we see is all there is. We cannot help dealing with the limited information we have as if it were all there is to know. We build the best possible story from the information available to us, and if it is a good story, we believe it. Paradoxically, it is easier for us to construct a coherent story when we know little, when there are fewer pieces to fit into the puzzle.

The fact that we think we have a clearer understanding of the past does not automatically mean that we are capable of comfortably predicting and controlling the future. Learning from the past is a reasonable thing to do, but it is also important for us to understand that this can have some dangerous consequences.

If we lack knowledge of all the information there is to know, the limited information we have on past performance can mislead us during budgeting and planning processes and negatively affect future outcomes.

Link Budgets to Strategy

Despite the widespread challenges of the annual budgeting process and prominent rise of the beyond budgeting proponents, the annual budget still has a place in the hearts of many finance executives.

They are not yet ready to ditch the budgeting cycle completely, it is too risky for them to run the business without a financial plan.

Rather than ditching the budgeting process entirely, implementing driver-based budgets and rolling forecasts can help organizations address the challenges of the traditional budgeting approaches.

Although most of the variables in the budget are financial, it is important to also take into consideration non-financial information as this is key to developing an understanding of business performance drivers and constraints.

Very few organizations make an attempt to link budgets with their strategy, in fact the planning process is influenced more by politics than by strategy. Leading organizations are using the Balanced Scorecard to strategically allocate resources.

Linking budgets to strategy helps management and their subordinates identify the organization’s critical success factors and how they relate to the KPIs used to measure company success. This in turn, will help them design initiatives needed to close the gap between current performance and desired performance.

Aligning spending with strategy also helps fund only those initiatives deemed strategic and with the potential of propelling the organization forward. This is in direct contrast to the base plus and zero base approaches which allocate resources on the basis of chart of accounts line items, resulting in the funding of non-strategic initiatives and wastage of resources.

Implement rolling forecasts

Compared to traditional budgets which cover a fixed period, rolling forecasts allow organizations to get a vision of the future and support improved decision making. By using rolling forecasts, the company will be able to project performance four to six quarters ahead.

Each quarter the plan is reviewed, and key decision makers are able to understand problems, challenges and trends sooner than later, and change directions or fund strategic projects based on current economic conditions. Instead of reacting to changing business conditions, executives will become more proactive in their approach.

One of the advantages of rolling forecasts is that they are driver based. Drivers help eliminate detail when creating a realistic expectation about the future resulting in managers focusing on what is vital for the success of the organization.

With time, the drivers are evaluated to determine if they are still a key predictor of higher performance. If not, new drivers will be identified and selected for monitoring.

As volatility and uncertainty continue to increase, organizations need to be prepared always in order to navigate successfully towards the future.

Why Implement Continuous Rolling Forecasts?

The annual budgeting process has been around for decades and still forms part of the performance management framework for the majority of organizations. As the economic environment has evolved and become more dynamic, has the budgeting and forecasting capabilities in your organization also evolved and adapted to this change?

Unfortunately, for many organizations, the annual budgeting process still rules. Despite the evident drawbacks of the traditional budgeting process and developments in financial planning technologies, there is still widespread reluctance by top management to embrace alternative planning processes. The traditional annual budget used by many companies is static in nature, not aligned to strategy setting and execution, and focuses mainly on cost reduction as opposed to value creation.

In today’s volatile, uncertain, complex and ambiguous economic environment, in order to make effective decisions, management must be able to understand and respond quickly to the impact of competitive forces and rapid changes affecting their businesses. They must be able to look into the future, assess risks and potential opportunities and proactively manage them. Different decisions require different time horizons and planning capabilities.

The problem with the annual budget is that it distorts this long-term visibility and stifles innovation. Much emphasis is placed on the current fiscal year, which is normally twelve months. As a result of this short-term focus where management is driven to achieve the predefined annual targets, a culture of predict-and-control becomes prevalent. The focus is on making sure that the forecast numbers are achieved.

What do I mean by the above? In the traditional budgeting and forecasting processes, management come up with an annual performance targets, mostly financial, broken down in a twelve-month period. Every month, actual results are compared against planned results and variances (Monthly and YTD) identified. The computation for the monthly forecast therefore becomes:

forecast

 

The problem with the above approach is that the forecasting process is disconnected from the specific drivers of the business. It fails to understand that the purpose of forecasting is to map the strategic direction of the organization, identify risks and potential opportunities, and coordinate future activities. It is not a performance evaluation tool and a re-validation of the company’s commitments. When forecasting is used as a performance evaluation yardstick, chances are that management will purely focus on achieving the targets set at the beginning of the year.

What is critical to note is that forecasting should be based on real business demands and the real business environment. At the same time, rewards must be according to the value created and not based on meeting set financial targets because the later can easily be gamed.

Does this therefore mean that the traditional annual budgeting and forecasting process should completely be abolished? Some scholars and professionals have called for a complete elimination of the entire process raising some of the issues already mentioned here. I personally believe that combining a number of practices such as driver-based planning, rolling forecasts, Strategy Maps and their associated Balanced Scorecards is key to addressing traditional budgeting and forecasting drawbacks. No one practice offers a remedy for all these issues. Remember enterprise performance management (EPM) is the integration of various managerial techniques to support strategic decision-making and improve performance.

 

The Benefits of Implementing Rolling Forecasts

Enables Management to Adapt to a Changing Economic Environment

One of the mostly mentioned disadvantages of the annual budget is that it is static in nature and ignores changes in the market place. Targets are set based on the various assumptions identified at the beginning of the year and by the time the final budget is signed-off, most of these assumptions are out-of-date and irrelevant.

For example, in many companies, the annual budgeting process lasts on average between three and six months, and sometimes even longer. The process is back-and-forth with revision after revision. In today’s volatile economic environment, a lot can happen in the six-month period which has far implications on the strategic performance of the business. Because of the amount of time taken to agree and sign-off the final budget, these changes are not factored in.

Implementing continuous rolling forecasts offers a remedy for this issue of adaptability. Most continuous rolling forecasts are prepared at least four to eight quarters past the current quarter’s actual results. This gives management greater visibility into the business and prepare agile responses to changing market conditions.

Even at the time of budgeting, at the end of the second quarter of the financial year, you would have already gained insights that relate to first half of the next fiscal year and this immensely reduces the time required to produce the final budget.

Management need to be able to look at what is possible, rather than merely react to what has occurred. Hence the need for forward-looking forecasts which act as early warning systems when you have drifted off-course.

 

Allows Management to Perform What-if-Analysis

Most budgeting and forecasting processes are a series of one-off annual or quarterly events. They are prepared based on historical data imports from the company’s ERP system thereby ignoring the key business drivers of the business. Plans are often extrapolated from historical performance and end up being a simple accumulation of financial trends.

With rolling forecasts, management are able to focus on key assumptions and drivers of strategic performance, model possible future outcomes and identify the events that might trigger them, evaluate the impact of these events and design contingency plans to remedy the negatives.

Unlike budgets that may have hundreds of line items to focus on, continuous rolling forecasts focus on the strategic key business drivers. This reduces the amount of time spent on planning and frees up time on other initiatives that drive greater value and high performance. Because rolling forecasts challenge management to have a continuous business outlook, the focus is on leading indicators which helps the organization identify future performance gaps and re-adjust.

 

Shifts Management’s Mind-set from Annual Planning to Continuous Planning

Traditional budgeting often creates a fixed performance contract that limits an organization’s ability to be responsive to ever-changing market conditions. Because of this, there is natural tendency for management to ignore changes after the fiscal period even if they do have negative impact on the performance of the business.

On the contrary, rolling forecasts help management eliminate this annual mind-set, are aligned to business cycles and help managers continuously look into the future and proactively design counter-measures to remedy the drawbacks of the annual budget.

As already mentioned, it is time-consuming to produce the final budget and get it signed-off. By the time the budget is finalized, the market has changed dramatically and its assumptions are out of date. Because the budgeting process is an annual exercise, there is no room to adjust the levers that drive business performance.

Quoting a great quote by one of the Chinese Philosophers, Lao Tzu:

A good traveller has no fixed plans, and is not intent on arriving.

 

The same applies to businesses. The fiscal year end must not be the destination. It is therefore imperative that management considers all scenarios when making key strategic decisions. By implementing rolling forecasts and continuously updating the forecast to reflect current business conditions, management will be able to mitigate the risks of traditional budgeting and forecasting inaccuracies.

In order to fully benefit from rolling forecasts, the budgeting and forecasting capabilities must form part of the organization’s integrated enterprise performance management (EPM) framework. Additionally, there must be strong executive buy-in with regards to use of rolling forecasts to drive business performance. This buy-in is key to ensuring greater acceptance of the use of rolling forecasts by the organization’s business unit managers.

I welcome your thoughts and comments.

Are You Using Scenario Planning To Improve Decision Making?

As the business and macro-economic environment continue to change at rapid paces and increasingly getting complex, the pressure on the finance organization to support the core business by strategically addressing volatility, uncertainty and risk is also intensifying.

This fast changing environment is making it extremely difficult for organizations to forecast business performance with a greater degree of certainty. What we used to consider extraordinary is now the ordinary and the previously unthinkable is now reality. In this environment, organizations need to become more proactive, flexible, adaptable and not reactive. Traditional planning cycles such as the static annual budget are no longer ideal for this dynamic economy.

Past Performance is Not a Predictor of Future Performance

Despite significant evidence indicating this rapid change, many organizations are still relying on the annual budget for planning and evaluation purposes. What we tend to forget is the fact that the annual budget gives a false view of a stable future. By the time the annual budgeting process is over, the majority of the assumptions used to compile the budget are outdated. Additionally, most budgets solely use historical performance as a baseline for predicting future performance. Again, this ignores the fact that past performance cannot be used to mirror future performance.

Most budgets prepared by companies only have a financial focus, normally adding or deducting a percentage to previous year’s numbers. They lack specific consideration of the forces driving the business and value creation. The link between the strategy, planning, resource allocation and performance reporting processes is broken.

With the current volatility, uncertainty and complexity in today’s environment, companies need to adopt an agile mindset and new ways of planning. Working together with the other business functions, Finance can drive this process and lead its success. Taking advantage of the function’s analytical and risk management strengths, finance executives can use scenario planning to help decision makers identify and understand possible future events and their impact on strategy execution and business performance.

Scenario Planning

Instead of taking a static view of the future and basing key decisions on gut feel, scenario planning helps business leaders understand their business environment (any significant emerging threats and opportunities), identify the critical drivers of value and correlate their impact on performance, both operationally and strategically. It achieves this by enabling decision makers frame a number of questions on the strategic intent of the organization.

Regardless of your business’s industry sector, scenario planning is useful for getting different views of the future that reflect volatility, uncertainty, and complexity thereby helping you identify gaps in your organization’s ability to respond to threats and opportunities. Once you have identified the blind spots and gaps in your company’s response capabilities, you can then start building a dynamic risk management framework and gain knowledge of the risks you have direct control of or influence and those that you do not have.

When conducting a scenario planning exercise, organizations must:

  • Define the purpose and scope of the exercise.
  • Examine the internal and external environment for emerging trends and issues.
  • Identify possible realistic future scenarios and evaluate their impact on the business.
  • Formulate strategic and operational responses to each scenario.
  • Monitor performance related triggers and regularly challenge assumptions

Scenario Planning is Not About Predicting the Future Accurately

Instead, it is about understanding the environments in which your business operates, discovering new insights, and increasing adaptability to changes in these environments. By constantly taking uncertainty into account when making decisions and also encouraging alternative thinking, you will be able test and evaluate the robustness of your company’s strategies against a range of possible futures. This in turn will assist you broaden your perspective and develop robust response plans.

Critical to note is that scenario planning is a continuous process rather than a once-off exercise and must be incorporated into processes for managing the business on an ongoing basis. The macro-economic environment is constantly changing and as such, an ongoing review of the drivers of performance and trigger points is necessary.

You need to constantly ask questions on the social, technological, economic, environmental, political and legal influencing factors and indicators.

Examples of questions that you might ask include:

  • If you are an automaker, what is the impact of autonomous and electrical vehicles on our current business model? Are self-driving cars the future and how should we respond?
  • If you are consumer company, how would the organization respond to growing emerging markets and the rise of the middle class workers?
  • How would the organization respond to unexpected loss of a major contract that has sustained the company for a long time to a competitor?
  • What are the short-term and long-term implications of a major product recall on your market position, reputation and the organization’s ability to meet strategic performance?
  • What is the range of likely impacts on our brand, customers and supply chain, if one of our key suppliers files for bankruptcy?
  • What competing products or disruptive forces will have the potential of threatening and forcing us out of business?
  • What is the impact on our quarterly and annual performance targets of material short term changes in key external variables such as commodity prices, inflation rates, interest and exchange rates, GDP and consumer spending?
  • How would the organization respond to unexpected external events such as a major natural disaster, political or regulatory actions, or occurrence of a pandemic?
  • What are the likely advantages and disadvantages of moving our enterprise systems to a cloud-based platform versus retaining them in-house?
  • What are the global business implications of UK leaving the European Union, and how would our organization react to such a move?
  • What are the implications to the business of a data breach on key account information?

By systemically monitoring a series of performance related triggers, the organization will be able to anticipate major trends and changes in the industry or broader business environment, respond dynamically, gain competitive advantage and seize growth opportunities in both developed and emerging markets.

Scenario planning is more than a business threat analysis tool. It also helps you identify emerging opportunities, improve your business model and proactively address industrial and environmental uncertainties.

Improving Finance’s Financial Planning & Analysis Capabilities

As the role of the finance function continues to evolve from reporting on what happened in the past to driving business performance and creating enterprise value, the function’s financial planning and analysis capabilities need to be improved.

More than ever, increased volatility and uncertainty is placing considerable pressure on finance leaders to support business decision-makers by delivering actionable real-time insights.

Finance leaders are required to have a 360 degrees view of the risks and opportunities the organization is exposed to and respond promptly to change.

Recently, CFO Research in collaboration with SAP conducted a global survey of senior finance executives across various industry segments to better understand how finance leaders are supporting decision-making and value-creation purposes within their organizations. Based on 335 senior finance executives’ responses, the survey revealed the following four key findings:

  1. Being agile is becoming an increasingly source of competitive advantage. In a volatile, uncertain, complex and ambiguous business environment, having the ability to respond and adapt to change is the key to survival and value creation. Unfortunately, volatility and uncertainty is the norm these days. This in turn is requiring finance to provide real-time analysis and decision support. Of the surveyed finance executives, 84% are expecting senior management demand for adhoc decision support and analysis from finance to increase more in the coming years.
  2. Current financial planning and analysis IT systems are failing to deliver actionable insights. Organizational CFOs are hungry to see their functions conduct highly sophisticated, predictive business analysis, such as scenario planning, “what-if” analysis and risk modelling. However, current IT systems are falling short of intensifying demands for real-time analysis. For example, 53% of the senior finance executives responded that they are trading off sophisticated, predictive business analysis in order to produce reports in a timely manner. Furthermore, 14% are currently able to instantly respond to ad-hoc reports for business analysis via interactive, self-service interfaces. The majority (61%) of senior finance leaders are responding within one day of receiving request and 20% are responding more than one day after receiving the request.
  3. Lack of integration between financial planning and core ERP systems. Only 36% of survey respondents indicated that their company’s financial planning systems are well integrated with each other, with minimal manual intervention. Further worrying, only 15% of the respondents indicated that those financial planning systems are very tightly integrated with their core ERP systems and require minimal data migration.
  4. There is increased pressure on finance teams to drive business performance and create value. One of the critical mandates of the organization’s finance function is delivering more forward-looking and more interactive information and analysis into the hands of business decision makers. As the business environment continues to evolve, 88% of the surveyed finance leaders agree that this mandate will increase more in the coming years.

In light of these findings, what should senior finance executives and their teams do?

  1. To be the organization’s sought-after trusted adviser, finance must move beyond focusing only on the company and its profits and start seeking new opportunities to grow the business and expand. A team is as good as its leader. The finance leader must make sure that his team constitutes people with diverse backgrounds but all working towards the same goals of delivering real-time actionable insights, managing enterprise risks and creating sustainable value. It is critical to have people who possess the ability to challenge current assumptions and ask the right questions. People who do not possess a herd mentality but are prepared to go against the status quo as long as they are bringing something tangible to the group.
  2. The finance function must become agile, innovative and adaptive. Disruption in the business environment demands the function to develop new management models, standardize processes and be responsive to threats and opportunities. Keeping abreast of what is happening in the business environment, both externally and internally, helps sense and respond to changes quickly. Playing a “wait-and-see” game is no longer sufficient in today’s ever-changing business landscape. Business leaders need to be able to thoroughly scan their operating environments, understand risks and opportunities and take immediate strategic action.
  3. In order to improve the function’s financial planning and analysis capabilities, senior finance executives must ensure that their organizations have invested in IT systems that meet the demands of real-time, ad-hoc analysis. For example, the IT system must be able to conduct highly sophisticated, predictive business analysis in timely manner. Finance must be able to deliver more than just reporting on historical data and have the ability to deliver clear, actionable, forward-looking and real-time insights. Furthermore, it is important that finance provides reports and analysis that is easily understood by all managers to enable them make effective decisions.
  4. The organization’s financial planning and the core ERP systems must be integrated to ensure more effective decision-making. As the providers of information and analysis for sound decision-making, finance should ensure that it is providing one version of the truth always. It is therefore critical to have tight integration of financial systems with the other ERP systems if the function is to provide decision support and help create value. The integration of the systems should require minimal manual intervention and minimal data migration. In other words, there should be a reduced amount of time, attention and resources devoted to data migration and manual reconciliation connected with financial planning and business analysis. Having an integration of systems helps achieve consistency in processes and transparency of data throughout the consolidation data to financial results.
  5. Not all data is important for decision making, some of it is just noise. One of the barriers to improving financial planning and analysis capabilities is lack of data standardization across the organization. In today’s information age, it is critical that finance leaders and their teams are able to separate the wheat from the chaff. Data used for planning purposes must be validated and consistent throughout the company. How reliable and timely are your data sources? Also, there is need to train employees on the importance of data decision-making and data science.

As the pressure on senior executives intensifies to manage increasingly complex businesses and improve the organization’s competitive position, finance leaders will always be expected to deliver insights and analysis that are able to make the most difference to the business.

Factoring Risks into Financial Forecasts and Planning

VUCA, short for volatility, uncertainty, complexity and ambiguity is an acronym used to describe the world we live in.

Since the onset of globalization, CFOs have had to deal with a variety of uncertainties and risks. From the traditional operational, financial, credit and market risks to strategic risks, the list goes on.

Yet despite having knowledge of these risks and how they can derail the company from its successful course, very few CFOs and their teams factor risk management into their financial forecasts, budgets and plans.

As custodians of the forecasting and planning function, it is the responsibility of CFOs to ensure that risks to the operational existence of the business are identified, assessed and properly mitigated.

Unfortunately, regardless of its limitations, some CFOs still rely heavily on the annual budget to drive business performance. A lot has been proven and written on the shortcomings of the traditional budgeting process.

For example, the annual budgeting process is time-consuming and by the end of the first quarter, most of the assumptions used to prepare that budget no longer hold true hence the need to adopt driver-based rolling forecasting and planning.

To successfully take advantage of emerging opportunities and help empower strategy, the Financial Planning and Analysis (FP&A) team must embrace risk-adjusted forecasting.

Instead of focusing entirely on single-point estimates that fail to identify risk exposures, risk-adjusted forecasting enables CFOs to look at possible outcomes and probabilities based on multiple risk variables.

The macroeconomic environment is always changing and as a result CFOs ought to be proactive rather than being reactive.

It is no longer sufficient for CFOs to know what happened in the past. There is need to move on from the traditional cost-variance analysis towards a more forward-looking approach.

Thanks to developments in analytical technologies, through the use of descriptive and prescriptive analytics, CFOs are able to gain insights on why something happened as well as model the future.

In other words, technology is addressing the challenge of preparing forecasts based on gut feel.

Through risk-adjusted forecasting, forecast models can be built that are based on facts such as competitor activity, production activity, regulatory pressures, supply and demand changes etc.

Having an expanded view can help many companies address interconnected risks, some of which may have been previously identified, others that may have gone unnoticed.

Rather than entirely focusing on hitting one set of given numbers, CFOs should stress tests their forecasts and rigorously challenge the assumptions used to create those forecasts by asking the right and hard questions.

This will help identify an understatement or overstatement of risks and take corrective action. Given that growing a business brand and improving revenue growth and operating margins all come with a bag full of risks, if CFOs turn a blind eye and ignore these risks, they definitely are bound to steer their organizations towards an iceberg collision.

Risk types and risk drivers vary by company, business and industry.

Thus, it is critical for CFOs to have an enterprise view of risk if they are to be successful in addressing any material concerns facing the finance function and the organization as a whole.

At the same time, factoring risks into the forecasting and planning processes ensures effective allocation of investment resources based on multiple risk-return positions.

Identifying the various risks the organization is exposed to as well as their drivers requires both a bottom-up and top-down approach.

A bottom-up approach is helps identify, assess and evaluate the risks operating at the shop floor level. A top-down approach looks at the risks of the strategy and to the strategy and how they can be mitigated.

Understanding common risks and how they cascade and interact provides a foundation from which risk-adjusted forecasting frameworks can be developed and then set up throughout the entire organization.

Care must be taken that you get a balance on the number of risks and their drivers based on perceived importance, data availability and practicality. The idea is to get valuable insights that drive effective decision-making as opposed to overburdening the business.

Producing Reliable Forecasts That Improve Decision-Making

Although almost every organization uses forecasts to predict and manage future business performance, only a few of the produced forecasts are reliable despite the amount of energy and time invested in producing them. The problem with unreliable forecasts is that they have far-reaching strategic and operational implications.

They lead to poor decision-making which in turn costs the organization a lot of money. Analysts from the investment community closely monitor the forecasting capabilities of the companies they track.

Failure to hit forecast targets can result in the share price getting hammered and eventually a “sell” call by the analysts. This has negative repercussions on the market capitalization of the organization. Of course no one can accurately predict the future.

However, producing forecasts that are within five percent of the actual performance is considered accurate.

Accurate forecasts are a potential driver of business performance and investor confidence. They help identify opportunities to drive business improvement, manage risks, determine growth strategies and reinforce stakeholders’ confidence in the business.

One of the reasons why so many forecasts lack reliability is because the data used to produce these forecasts is either erroneous or incomplete. For example, some organizations depend largely on internal data to predict future performance at the expense of external data such as consumer demand, competitor activity, economic drivers etc.

To be able to forecast with confidence, it is imperative that those individuals tasked with the forecasting responsibility leverage information more effectively.

In addition to internal reports, they should make use of government reports, market reports and competitive data as well as data on non-economic risks that could have important impacts on markets or operations to produce forecasts. Also, operational managers who are closer to the business scene must be involved in the forecasting process.

There is a mistaken belief that forecasting is the sole responsibility of finance. Surely finance plays the leading role, but it is important to give the operational managers that drive business performance greater ownership and responsibility for key parts of the forecasting process.

By constantly liaising with their operational counterparts, finance will be able to quickly pick up changes in the business operating environment, perform what-if-analysis, update their forecasts accordingly and provider better insights that assist executives make informed decisions.

Despite the advent of reliable forecasting software, there is still a huge reliance on spreadsheets by a majority of organizations to produce forecasts. Although it is possible to produce reliable forecasts using spreadsheets, this is dependent on the size of the organization or business.

As the business grows, it becomes increasingly difficult to continue sticking to spreadsheets. This is because spreadsheets are great for building a single department budget and forecast but don’t work well for rolling up the budget and forecast for tens of departments and divisions.

Furthermore, spreadsheets are more prone to errors. Poorly constructed spreadsheets make it worse by mixing formulas and data so it is easy for users to type over formulas. Think of organizations that have lost millions of money just because one individual misplaced a comma or incorrectly typed a figure to a certain cell or row.

At the same time, it is worth knowing that technology alone is not the answer. Getting the processes and data right is a critical first step. Thus to obtain the necessary benefits, alignment of both processes and data with technology is key to avoid the risks of automating a broken process that uses unreliable data.

Then there is the issue of “sandbagging” the forecast to protect bonuses. Costs are a bit overstated and revenues a bit understated. If performance is rewarded mainly on the basis of hitting financial targets, managers are more likely to deliberately become conservative in their estimates. Such behaviour should not be encouraged.

Sandbagging and gaming interferes with good decision-making. Although such managers appear heroic in the eyes of their peers, it means that important decisions such as resource allocations and investment choices are being made on the basis of inaccurate or incomplete information.

Thus, to make better decisions, senior executives need to instill a culture where reliable forecasting is encouraged and rewarded. They should demand honest forecasts regardless they like or don’t like what they see. Additionally, incentives must be aligned to relative performance rather than targets.

As the business environment increasingly becomes dynamic and turbulent, managers and senior executives need to review the forecasting capabilities of their organizations and implement reliable rolling and driver-based forecasting.

Without reliable forecasting, key opportunities and risks are likely to be missed. On the contrary, reliable forecasts enable the organization to become sensitive and responsive to business conditions and make appropriate changes in real time.

They can improve the effectiveness of monitoring by recognizing the context of changing circumstances as these occur. This in turn assists managers to make bold decisions with greater confidence despite whichever direction the market moves.

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