It's nearly end of financial year, how should I set next financial year to be better?
As the end of the financial year approaches, it's a good time to reflect on the past year's performance and set goals for the upcoming financial year.
As the end of the financial year approaches, it's a good time to reflect on the past year's performance and set goals for the upcoming financial year.
Here are some steps you can take to set yourself up for success in the next financial year:
1. Review your financial performance: Look at your financial statements for the past year, including your income statement, balance sheet, and cash flow statement. Analyse your revenue, expenses, profits, and cash flow to identify areas for improvement.
2. Set realistic goals: Based on your financial performance review, set realistic goals for the upcoming financial year. Be specific about what you want to achieve, such as increasing revenue, reducing expenses, or improving profitability. Make sure your goals are achievable and measurable.
3. Develop a budget: Create a detailed budget for the upcoming financial year that aligns with your goals. Identify areas where you can reduce costs or increase revenue. Make sure to account for any expected changes in the business environment, such as inflation or new regulations.
4. Evaluate your pricing strategy: Review your pricing strategy and consider whether you need to make any changes. Are you pricing your products or services competitively? Are you leaving money on the table by underpricing? Consider adjusting your pricing to better reflect the value you provide.
5. Assess your marketing strategy: Review your marketing strategy and consider whether you need to make any changes. Are you targeting the right audience? Are you using the most effective channels to reach your customers? Consider investing in new marketing channels or strategies to drive growth.
6. Improve your financial management: Consider implementing new financial management practices to improve your financial performance. This could include improving your cash flow management, streamlining your accounting processes, or investing in new financial software or tools.
By taking these steps, you can set yourself up for success in the upcoming financial year.
By reviewing your financial performance, setting realistic goals, developing a budget, evaluating your pricing and marketing strategies, and improving your financial management practices, you can position your business for growth and profitability in the next financial year.
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How do you build a cashflow forecast?
Building a cash flow forecast can help businesses plan their cash needs and ensure they have enough liquidity to cover their expenses.
Building a cash flow forecast can help businesses plan their cash needs and ensure they have enough liquidity to cover their expenses.
Here are the steps to build a cash flow forecast:
1. Determine the time frame: Decide on the period you want to forecast (typically a week, month, or quarter).
2. List all sources of cash: Start by listing all the sources of cash for your business, including sales revenue, loans, and investments.
3. List all cash outflows: Next, list all the cash outflows for your business, including salaries, rent, inventory, and other expenses.
4. Estimate the timing of cash flows: Estimate when the cash inflows and outflows will occur during the forecast period. For example, you may receive payment from a customer in 30 days or pay rent every month.
5. Calculate the net cash flow: Subtract the cash outflows from the cash inflows to determine the net cash flow for each period.
6. Adjust for changes: Review the forecast and make adjustments for any changes that may affect cash flow, such as new sales contracts, changes in expenses, or changes in borrowing.
7. Monitor actual cash flow: Compare the actual cash flow with the forecast regularly to identify any discrepancies and adjust the forecast as necessary. Cash can come from a variety of sources, such as sales revenue, loans, investments, or other income.
By building a cash flow forecast, businesses can better plan their cash needs and ensure they have enough liquidity to cover their expenses.
It can also help businesses identify potential cash shortfalls and take proactive steps to address them before they become a problem.
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The CFO role has many dimensions
The CFO role has never been so important. Companies are navigating uncertain territory and having a strong CFO that can manage the nuts and bolts of finance and help navigate the commercial as well is instrumental to how companies navigate this period.
The CFO role has never been so important. Companies are navigating uncertain territory and having a strong CFO that can manage the nuts and bolts of finance and help navigate the commercial as well is instrumental to how companies navigate this period.
The CFO is expected to know the numbers, manage the numbers and be proactive across the key financial metrics that can impact the ability of the business to do what it needs to do. The CFO needs to have the strength to battle the business when necessary, when the financial performance is below the budget/forecast view.
The CFO is also expected to be the strategist, working with the business to understanding/build and execute on the strategy. The budget and 3-5 year plan needs sufficient investment for the businesss to deliver on the longer term plan.
You can’t forget cash, cash is instrumental to ensure the business can operate, if you have a profit but don’t have operating cashflow, you get yourself into challenges. When COVID landed, many businesses that had not actively managed cash, needed to start, however there are businesses out there that don’t actively manage their cashflow, and this is a mistake.
You need to understand your timing of receipts, timing of payments, working capital requirements (inventory etc.) and understand how this interacts with your budget and forecast.
A 13-week cashflow forecast, is a must and allows you to look at your CF weekly against the budget and then roll another 13 weeks to understand the ins/outs of each cash. Once you understand cash, you can start to actively manage cash. Cash is king and in the current environment even more important than ever.
The CFO leads a finance team, sometimes owns other functions, works closely with the CEO and Executive Leadership team, and is actively involved with the Board, Shareholders and other key stakeholders.
The CFO also takes a leadership role with other projects, business unit to demonstrate the importance of Finance in supporting the other business units. Your shareholders will determine what kind of CFO you become…as in a private equity environment it’s quite different too, private ownership or founder lead company. Whatever the case, the role is varied, hard, challenging and rewarding.
If you are a CFO and looking for some tools, templates and relevant articles, see below Whiteark has some great tools for you to use in your role and with your teams. Jo Hands, Founder/Director of Whiteark has walked in your shoes and has some great experience with related topics and has some practical tools and templates you can use.
Check our CFO guide HERE .
Explore our thought leadership articles about Finance and CFO’s HERE
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My journey to CFO
I started on a typical path post university, 10 years at EY as an auditor……
I loved every minute of it.
Earnst & Young (EY) had a great culture, good clients, great people in the
I started on a typical path post university, 10 years at EY as an auditor…..I loved every minute of it.
Earnst & Young (EY) had a great culture, good clients, great people in the teams, great training, 360 feedback and opportunities to work on projects outside of client work.
I remember EY with fond memories and I remember the day I finished up there were many tears, it was 15th October 2010. EY pushed hard, but they also rewarded hard workers that delivered. I got overseas conferences (Japan, Venice), to lead a global project for a new tool, which allowed me the opportunity to lead, get people onboard and manage a big roll out for the ANZ region.
I loved my team, and my clients, favourite client being Village Roadshow – what’s not to love about Theme Parks and Movies. I learnt so much, but probably didn’t realise it until I left.
My first job out was Telstra, Sensis business unit – Technical, Reporting role. Likely considered a backward step – you are over-qualified in a lot of respects but under qualified in other respects. I was lucky to have a great team, peers and made some great friends along the way. I loved the industry. I loved being part of something and driving and making a difference and seeing that difference come through.
4 years after I started at Sensis, it was sold to Private Equity, which was where my career went from interesting to super-duper interesting. Working with the private equity firm to carve out from Telstra and set up the businesss under private ownership. It was a big change. I took a lead role in working with new shareholder to manage the transition and help build the business in the new world.
This included zero based budgets, cash flow reporting & forecasting and understanding the capabilities required to deliver on the change in strategy. It wasn’t just a big change for Finance but for the whole business, but finance become central to how the business operated and therefore the role I took was pivotal to the success.
Over the next 5 years, I worked as Deputy CFO, then transitioned to CFO and looked after Strategy, Finance, Operations and IT. My role continued to expand.
I really enjoyed the experience and breadth of the role. Navigating strategy, to building a budget and metrics to measure success and the capability in the business to drive the outcomes required.
We found over the period, people self-selected, and private equity wasn’t for everyone. It was about achievement, delivery and ensuring that all key metrics are met. Incentives ensured that the key metrics were measured, tracked and managed.
The private equity approach was hardcore and a lot of lessons were learnt along the way, but for me I realised this was the environment that I enjoyed, I loved the change, execution and an ability to drive an improved outcome in the results.
Since I finished up at Sensis, I have done a number of roles with other private equity firms – doing interim CFO roles, managing transitions, integrations, operating models, strategy, business plans etc, working with different companies to actively manage an acquisition (from DD) to the first 100 days, which will make or break a business and set the tone for the new world.
These projects require different skillset but a driver that can help move things forward and ensuring that there is a plan to deliver on the synergies baked into the plan. I have done this under the banner of Whiteark. I have other clients, but mainly working with PE on assessing, strategy, plan and execution for deals, and that is what I love.
I love the planning but then being able to get in there and really deliver. My finance experience, private equity experience and breadth of roles, has allowed me the opportunity to jump into consulting to private equity with both feet.
Not sure where my journey will land me, maybe back as a CFO one day, but for now enjoying the freedom, challenge and drive of working for myself and picking my clients and making a difference every day.
With my background as CFO – we have a range of tools and FREE templates that we have generated that might help you with your day-to-day life as well. You can explore and download the templates HERE
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Budgeting & Forecasting - it's not as easy as it used to be
The concept of budget and forecast was simple ….
Using prior year information and overlaying assumptions, historical changes, investments etc to deliver a new set up numbers for the upcoming year or years. Shareholders wanted to see an improvement and so as long as the percentage changes were going the right way then you were normally ok.
The concept of budget and forecast was simple ….
Using prior year information and overlaying assumptions, historical changes, investments etc to deliver a new set up numbers for the upcoming year or years. Shareholders wanted to see an improvement and so as long as the percentage changes were going the right way then you were normally ok.
Historical trends in all key metrics was the starting position to build the budget and forecasts and then work out what metrics you can improve, how you can improve and the timing to overlay into the budget/forecast.
Companies can take 3-6 months to prepare a budget, it’s a ridiculous amount of time, and time that should be spent executing the plan and driving a positive outcome rather than validating an excel model.
A budget should be driven from key metrics i.e. customer numbers, average revenue per customers, new customers, customer churn rate etc. Understanding what a customer generates and then costs, can ensure that the model is underlying based on key metrics. This means when you are measuring performance against the budget, you can understand why you are travelling higher or lower.
AND THEN THERE WAS COVID…
Covid landed in 2020 and developing budgets, forecasts and understanding the impact was hard if not impossible. Many businesses tried to do a forecast of where the year was going to land for FY20. The budget was useless and metrics and information that didn’t mattered, now mattered.
Companies were focused on building a forecast. CFO and finance professionals developing a forecast for an uncertain period, where history has little relevance and the future is new and therefor every uncertain. The best way to manage this would be to do scenarios that allow you a high and low scenarios and you know what the impact if each of these different book-ends happen.
Most of the forecast were wrong, as there were guesses but got the company through this uncertain period.
We are now in a getting back to normal period, post COVID (even though COVID still around) and this period is tricky…people were buying products online and now going back into stores, so the revenue from online will drop, back to pre-COVID probably not but what will be the level, how will this impact inventory levels, cashflow requirements and how the business operates.
Budgeting and forecasting has never been so difficult. Having clear business drivers and some scenarios to stress test, cash, debt and other key operating metrics and having a plan B if something occurs that was not originally expected.
It might be years, or never that we get back to the guaranteed budget that used history as the basis, but the more data and information we gather to prepare the financial modelling – budget and forecast the better.
If you are a finance person, you will smile at this article…it’s been your life for the last 3 years and it’s still impacts the way things are done.
Doing a zero-based budget, can help reset the way the business looks at the business, less reliance on prior year and resetting the cost base of the business by asking why do we need that expenditure, what is the return on investment?
There are some easy wins, and it might be what you need to balance your budget for FY24 and beyond.
Whiteark has a range of articles and resources for budgets/forecasts that we will share with you.
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How should we think about Complexity? Is it complicated?
Mark Easdown writes about complexity. In the mid 1980s, a school of thought emerged around “Complexity” and “Complex Adaptive Systems” with the formation of the Sante Fe Institute, formed in part by former members of Los Alamos National Laboratory. The institute drew from multi-disciplinary domains and insights of : economics, neural networks, physics, artificial intelligence, chaos theory, cybernetics, biology, ecology and archaeology. Theories on Complexity and Complex Adaptive systems sought to develop common frameworks and understandings of physical and social systems that was an alternate to more linear and reductionist modes of thinking.
Article written by Mark Easdown
Business Planning, Mental Models, Ways of Thinking & Working
“A complicated system is the sum of its parts. You can solve problems by breaking things down and solving them separately. In a complex system, the properties of the whole are the result of interaction between the parts and the linkages and the constraints. In fact, in a complex system how things connect is more important than what they are. So, the properties of that emergent pattern can never be decomposed to the original parts.” David Snowden
“The problem is complexity (in financial markets) …we cannot prepare for every thread of causality through every interaction; in the speed of the event we find there is no time to make adjustments.” Richard Bookstaber
“Nature likes to over-insure itself. Layers of redundancy are the central risk management property of natural systems.” Nassim Taleb
In the mid 1980s, a school of thought emerged around “Complexity” and “Complex Adaptive Systems” with the formation of the Sante Fe Institute, formed in part by former members of Los Alamos National Laboratory. The institute drew from multi-disciplinary domains and insights of : economics, neural networks, physics, artificial intelligence, chaos theory, cybernetics, biology, ecology and archaeology. Theories on Complexity and Complex Adaptive systems sought to develop common frameworks and understandings of physical and social systems that was an alternate to more linear and reductionist modes of thinking. Members sought to better understand spontaneous, self-organising dynamics and found examples in the;
Natural World - Brains, Immune Systems, Ecologies, Cells, Developing Embryos and Ant colonies
Human World – Political parties, Scientific communities and in the economy
Why bother?
Just say you and your team are facing a complicated problem, then you may break down the problem into component parts, build an expert team internally or partner with external consultants, you may take a data driven or fact-based approach, you may identify best practices create a strategic plan and solve the problem incrementally. However, is that all? Is there a one size fits all solution to problem solving?
What if your problem could be categorised with traits such as;
Levels of uncertainty, ambiguity, unpredictability, dynamic interfaces - many diverse and independent parts that were interrelated, interdependent and linked through many interconnections into a network
The properties of the whole cannot be predicted from the behaviours of the component parts, in fact the network of many components may be gathering information learning and acting in parallel in an environment produced by these interactions – the system co-evolves within its environment
There may be significant political, social or external influences
“Wise executives tailor their approach to fit the complexity of the circumstances they face.” David Snowden & Mary Boone
Where in the real world might it be useful to have sound thinking about complexity and solving problems?
In Project Management
Programs of work and problems to solve come in a variety of forms, at the simpler end of spectrum process re-engineering and best practices serve us well to achieve desired outcomes. Yet increasingly, our problems to solve are complicated, we need to analyse things to figure out what to do and cause and effect are distanced. Complex projects are harder still, they display behaviours such as self-organising, emergent properties, non-linear and phase transition behaviours. We need a different mindset, structure and strategy to wrestle with these problems.
In Financial Markets
These are complex adaptive systems, tightly coupled with unexpected feedback loops, with investors of different investment styles & horizons, the sum of the parts will not explain the whole in a linear manner, there are infrequent extreme price moves, not normally distributed.
In Nature
Complex collective behaviours are displayed when individual ants forage for food and lay down a pheromone trail on the way out from the colony and if successful finding food lay down even more on way back to the colony. Other ants follow this stronger pheromone trail to the food adding their pheromone. So, the pheromone trail becomes the whole colonies best path to food, it is an ant colony optimisation algorithm. Interestingly, this insight has helped form the basis of swarm intelligence and a wide array of solutions across routing and scheduling problems and bayesian networks.
The twenty-first century will be the "century of complexity" Stephen Hawking
COMPLEX PROGRAMS
“Strategy in complex systems must resemble strategy in board games. You develop a small and useful tree of options that is continuously revised based on the arrangement of the pieces and the actions of the opponent. It is critical to keep the number of options open. It is important to develop a theory of what kinds of options you want to have open” - John H Holland
In complex situations "cause and effect are only coherent in retrospect and do not repeat" - Sarah Sheard
Complex problems to solve are unique and they challenge some of the traditional approaches to program and risk management thinking, which may emphasise a need to identify risks in order to control them or completely plan and control programs of work. Examples of complex programs may include: computer systems and networks, buildings, bridges, planes, ships and automobiles.
Let’s take a look at what makes complex programs unique;
Sophisticated structures with many component parts interacting with each other, giving a degree of uncertainty whereby you may not know what you don’t know until it occurs
Unknowable interdependencies across domains, a need for agility and structures that favour the decentralised and local to the centralised approach.
There may be interfaces with complementary projects which present challenges in scheduling of these interconnected systems, teams and resources
The environment may have a political realm where new government decisions or public policy arises
So, what is a desirable mindset for complex programs?
A Forward focus, a willingness to proactively manage project development and critical issues through agility, collaboration and adaptability. You may need nuanced responses and local innovation.
Analysis of likely origins of complexity and thinking through dependencies, seek critical junctions, vulnerabilities & countermeasures. Contingency planning around time, buffering on sequencing, budget and people skills
Dynamic reporting and monitoring, a willingness to pick up early warning signs and take corrective actions
Communications will be dynamic, real time & high visibility (as small changes can have oversized consequences amplified by scale of some projects)
Program planning may have both a single view and multiple integrated project schedules
Cynefin is a framework to deal with predictable and unpredictable worlds (David Snowden)
In 1999, David Snowden described a framework and problem-solving tool which helps to adjust management style to fit circumstances, and has relevance across product development, marketing, organisational design and BCP/DR and crisis management. The framework had 5 domains;
OBVIOUS. Options are clear, steps to success are known, variables well known, cause-effect relationships are apparent, you are able to assess the situation, follow a procedure, categorise its type and base your response on best practice (processes & procedures) and feasible to achieve best possible result. Examples: Product mass production, cooking with a recipe, known scientific issues, known legal issues.
COMPLICATED. Solutions not obvious to everyone but most variables involved are well known, cause-effect relationships are apparent, you may assess a situation, build a diverse team or utilise experts to deliver the best response. The best that can be achieved is a good result, maybe not the best result. Examples: Existing product enhancements, coaching a team, adopting new approaches, hiring process.
COMPLEX. The context is often unpredictable, many factors uncertain, many variables may intervene, data may be incomplete, it may not be possible to determine right options, make predictions or find cause-effect relationships, there may be multiple methods to address issues. Exploring what has a proven record in past situations, small tests or business experiments, simple guidelines, brainstorming, innovation and creativity may drive solutions. Examples: weather predictions, stock markets, poker, epidemic controls.
CHAOTIC. The situation is where nobody knows what to expect, anything can happen, it is impossible to make predictions. You may have to act towards the urgent and important, then check and evaluate result before responding to that result and acting again. Examples: Innovate new products, anything which predicts people’s preferences or behaviours, crisis event and crisis management, warfare
DISORDER. The situation is not known, you need to firstly move to a known domain & gather more information.
COMPLEXITY IN FINANCIAL MARKETS
“In the last few years the concept of self-organising systems – of complex systems in which randomness and chaos seem spontaneously to evolve into unexpected order – has become an increasingly influential idea that links together researchers in many fields, from artificial intelligence to chemistry, from evolution to geology. For whatever reason, however, this movement has so far largely passed economic theory by. It is time to see how the new ideas can usefully be applied to that immensely complex, but indisputably self-organising system we call the economy” - Paul Krugman 1996
“By one estimate, 90% of international transactions were accounted for by trade before 1970, and only 10% by capital flows. Today, despite a vast increase in global trade, that ratio has been reversed, with 90% of transactions accounted for by financial flows not directly related to trade in goods and services.” - Didier Sornette 2003
“Fundamental analysis seeks to establish how underlying values are reflected in stock prices, whereas the theory of reflexivity shows how stock prices can influence underlying values. One provides a static picture, the other a dynamic one.” - George Soros
Financial markets have all the basic components of complex adaptive systems, namely:
Investors have differing investment strategies and horizons from trading at the speed of light to long term cyclical horizons. They take external information and combine it with their own strategic intent and these compete in financial markets => this is adaptive decision making
Financial markets is the aggregation of large-scale collective decision making and actions => these are developing, complex and emergent
Financial markets exist in a non-equilibrium state , are non linear, they experience non-frequent extreme price moves with the aggregate behaviour more complex than would be predicted by the sum of the individual parts.
Financial Markets are subject to feedback loops, where the result of one iteration becomes an input of next iteration
So, how has the emerging knowledge of complexity and financial markets framed regulators thinking?
The global financial crisis highlighted the complexity, leverage, inter-connected and tightly coupled of financial markets. In response we have seen;
Efforts to reduce interconnectedness (intra-day local trading halts, regional collateral exchanges)
Enhanced capital rules (increased contingency buffers and incentives for some activities to be managed by non-bank sector & efforts to reduce concentration of risks)
Enhanced liquidity rules (increase quantum and quality of contingency buffers)
Speed, agility and quantum of central bank and treasury initiatives to address market panics and crisis
A re-think of the rule-making complexity and mental models applied to finance;
“Modern finance is complex, perhaps too complex. Regulation of modern finance is complex, almost certainly too complex. That configuration spells trouble. As you do not fight fire with fire, you do not fight complexity with complexity. Because complexity generates uncertainty, not risk, it requires a regulatory response grounded in simplicity, not complexity. Delivering that would require an about-turn from the regulatory community from the path followed for the better part of the past 50 years. If a once-in-a-lifetime crisis is not able to deliver that change, it is not clear what will.” - Andrew Haldane Bank of England Speech 2012 “ The Dog and the Frisbee” [https://www.bis.org/review/r120905a.pdf ]
COMPLEXITY IN NATURE
In her TED Talk, Deborah Gordon: The emergent genius of ant colonies: highlights an example of a complex adapative system with no central control or management in an ant colony: [ https://www.youtube.com/watch?v=ukS4UjCauUs]
So, what is the strategy of the ant colony to constantly adapt to its complex environment? As per Deborah Gordon studies;
The ant colony allocates simple roles
At any given time 25% are patrolling, foraging and doing maintenance, 25% are inside with queen ant doing maintenance and looking after larvae, and finally 50% appear to be contingency and in reserve, able to surge as required to collect more food, patrol or more maintenance.
Communications are not centralised, they are dynamic, simple and local rules to adapt to emergent environment
The process is noisy, messy, imperfect and requires individual dynamic communications
Ant colonies can learn at the individual level by trial and error over many generations but this can nurture collective memory and problem-solving skills. The local instructing the central.
“So, the key to unlocking the efficiency of a leaderless system will rely on, among other things: clear role definition, flexible task allocation, a sense of responsibility toward the group, and shared understanding and response to communication patterns. Organizations would need to make an incredible investment in their employees, and vice versa.” Amanda Silver – Organising complexity – How Ant colonies self-manage. [https://medium.com/swlh/organizing-complexity-how-ant-colonies-self-manage-50455358f3cd]
How we should think about complex domains is still evolving, a multi-disciplinary lens across research and practice has been adding to this knowledge pool for decades. It is a vital enquiry for humankind, especially as our challenges become more complex to solve and our climate is as a complex adaptive system.
‘“he climate is a common good, belonging to all and meant for all. At the global level, it is a complex system linked to many of the essential conditions for human life.”- Pope Francis 2015
LOOKING TO CURATE YOUR BUSINESS STRATEGY? REACH OUT.
Whiteark is not your average consulting firm, we have first-hand experience in delivering transformation programs for private equity and other organisations with a focus on people just as much as financial outcomes.
We understand that execution is the hardest part, and so we roll our sleeves up and work with you to ensure we can deliver the required outcomes for the business. Our co-founders have a combined experience of over 50 years’ working as Executives in organisations delivering outcomes for shareholders. Reach out for a no obligation conversation on how we can help you. Contact us on whiteark@whiteark.com.au
Article written by Mark Easdown
Forecasting
Mark Easdown writes about forecasting. The prediction process starts with propositions, then verified, quantified and made actionable. A robust peer review occurs and 95% of predictions are modified along the way. Plummer routinely scrutinises predictions with actual events and these results are highlighted at conferences – championing the successes and sharing insights across those that were wrong. “Nobody here is hired because they’re psychic; there hired to generate insights that are useful – even if they turn out wrong. It’s useful to get you thinking”.
Article written by Mark Easdown
Decision Making & Planning, Ways of Working with Uncertainty
“The only function of economic forecasting is to make astrology look respectable.”
“Forecasts usually tell us more of the forecaster than of the future.”
“There is great value in bringing together people who attempt to address a common problem of forecasting from different perspectives and based on very different kinds of data.”
“Your assumptions are your windows on the world. Scrub them off every once in a while, or the light won’t come in.”
“For superforecasters, beliefs are hypotheses to be tested, not treasures to be guarded.”
“I prefer true but imperfect knowledge, even if it leaves much indetermined and unpredictable, to a pretence of exact knowledge that is likely to be false.”
“The Lucretius underestimation, after the Latin poetic philosopher who wrote that the fool believes that the tallest mountain there is, should be equal to the tallest one he has observed.”
A forecast is a statement about the future. (Clements & Henry, 1998)
As authors of “Forecasting” (J.Castle, M.Clements, D.Henry) note; a forecast can take many forms;
Some are vague and some are precise, Some are concerned with near term and some the distant future
“Fore” denotes in advance whilst “Cast” might sound a bit chancy (cast a fishing net, cast a spell) or might sound more solid (bronze statues are also cast)
Chance is central to forecasting & forecasts can and often do differ from outcomes
Forecasts should be accompanied by some level of certainty/uncertainty, time horizon, upper/lower bounds
The domain in which the forecast occurs matter, especially if no-one knows the complete set of possibilities
The authors consider the history of forecasting;
Forecasting likely pre-dates recorded writing with hunter-gatherers seeking where game of predators might be, edible plants and water supplies. Babylonians tracked the night sky presumably for planting and harvesting crops
Sir William Petty perhaps introduced early statistical forecasting in 17th Century and thought he observed a seven year “business cycle”
Weather forecasting evolved with Robert Fitzroy in 1859, who sought to devise a storm warning system to enable safe passage of ships and avoid loss of vessels &/or ships staying in port unnecessarily. Forecasting of nature extended to hurricanes, tropical cyclones, tornadoes, tsunamis and volcanic eruptions.
Yet, history is littered with failures in forecasting, large and small;
Ambiguous forecasts from Oracles of Delphi and Nostradamus
UK storms 1987, with lives lost and approximately 15million trees blown down
Failure to predict 1929 Great Depression or severity of Global Financial Crisis, mid-2007 to early 2009
“When the Paris exhibition closes, the electric light will close with it and no more be heard of it” – Sir Erasmus Wilson & “a rocket will never be able to leave the earth’s atmosphere” – NY Times 1936
What do we want from forecasts ?
Do we want just accuracy? To what degree is that even possible across complicated and complex domains?
Do we want cognitively diverse teams to make us more aware of extreme events? Thus, minimising downside risks?
Do we just want comfort, ideological support and evidence of our existing beliefs? Do we want entertainment?
Do we want to influence a target audience, shift consensus or established beliefs?
These answers may differ if you are a CEO, CFO, Head of Sales, Head of Innovation, an Insurance Actuary, Epidemiologist, Politician, Economist, Intelligence Agency, Shock Jock or Sports Commentator.
For example, it was a mainstream view of epidemiologists across last 20 years that a pandemic was a prominent risk;
“The presence of a large reservoir of SARS-CoV-like viruses in horseshoe bats, together with the culture of eating exotic mammals in southern China, is a time bomb. The possibility of the re-emergence of SARS and other novel viruses from animals or laboratories and therefore the need for preparedness should not be ignored.”- David Epstein 2007
https://davidepstein.com/lets-get-ready-to-rumble-humanity-vs-infectious-disease/
https://cmr.asm.org/content/cmr/20/4/660.full.pdf
So, is COVID19 perhaps SARS2? Clearly, forecasting a pandemic is desirable. How do we give prominence to diverse voices & data and what are the better practices to observe and implement?
SUPER-FORECASTING
In October 2002, the US National Intelligence Estimates (a consensus view of the CIA, NSA, DIA and thirteen other agencies with > 20,000 intelligence analysts) concluded that the key claims of the Bush Administration claims about Weapons of Mass Destruction in Iraq were correct. After invading Iraq in 2003, the US found no evidence of WMDs. “It was one of the worst – arguably the worst - intelligence failure in modern history” notes Philip Tetlock and Dan Gardner in their book “Superforecasting : The Art and Science of Prediction”
In 2006, IARPA was formed to fund cutting-edge research with the aim of potentially enhancing the intelligence community work. IAPRA’s plan was to create a tournament-style incentive for top researchers (intelligence analysts, universities & a team of volunteers for the Good Judgement Project (GJP)), to generate accurate probability estimates to questions that were;
Neither so easy that an attentive reader of the NY Times could get them right , nor
So hard that no one on the planet could get them right
Approximately 500 questions spanned: economic, security, terrorism, energy, environmental, social and political realms
Forecast performance was monitored individually and in teams, and Tetlock’s GJP team proved 60% more accurate in year 1, 78% more accurate in Year 2.
What did these forecasting tournaments learn about the attributes of super-forecasters that may be of relevance in Commercial or Government organisations? Here are a few;
Superforecasters spoke in probabilities of how likely an event would occur (not in absolutes : yes/no), this better enabled them to accept a level of uncertainty – it made them more thoughtful and accurate
Superforecasters were often educated yet ordinary people with an open-mind, an ability to change their minds, humility and an ability to review assumptions & update forecasts frequently, albeit at times by small increments
Actions which were helpful included;
Breaking the question down into smaller components and identifying the known and the unknown, focus on work that is likely to have better payoff, actively seek to distinguish degrees of uncertainty, avoid binding rules. Consider the “outsiders” view, frame the problem not uniquely but as part of a wider phenomena
Examine what is unique about problem and look at your opinions and how they differ from other people’s viewpoints. Take in all the information with your “dragonfly eyes” and construct a unified vision, balancing arguments and counterarguments, balancing prudence and decisiveness – generating a description as clearly, concisely and as granular as possible
Don’t over-react to new information – a Bayesian approach was useful
The GJP found that while many forecasters were accurate within a horizon of 150 days, not even the super-forecasters were confident beyond 400 days, forecasts out to 5 years were about equal with chance.
What about forecasting teams versus forecasting individuals?
o With good group dynamics, flat and non-hierarchical structures and a culture of sharing – teams were better than individuals – aggregation was important. In fact teams of super-forecasters could beat established prediction markets.
o The note of caution around low performing teams came when people were lazy, let others do the work or where susceptible to group-think.
“Unchartered : How to map the future together.”
Daryl Plummer of Gartner, a technology advisory firm who produces forecasts for customers who wish to discern hype from reality.
The prediction process starts with propositions, then verified, quantified and made actionable. A robust peer review occurs and 95% of predictions are modified along the way. Plummer routinely scrutinises predictions with actual events and these results are highlighted at conferences – championing the successes and sharing insights across those that were wrong. “Nobody here is hired because they’re psychic; they’re hired to generate insights that are useful – even if they turn out wrong. It’s useful to get you thinking”.
The author notes “that what matters most isn’t the predictions themselves but how we respond to them, and whether we respond to them at all. The forecast that stupefies isn’t helpful, but the one that provokes fresh thinking can be. The point of predictions should not be to surrender to them but to use them to broaden and map your conceptual, imaginative horizons. Don’t fall for them – challenge them.”
“How to Decide” : Annie Duke – Simple Tools for making better choices
The author presents some useful tips that teams can use to elicit uninfected feedback and leverage the true wisdom of the crowd in decision making. This is especially useful where key forecast & value chain insights and institutional knowledge is held across multiple SMEs and stakeholders;
The Problem;
“When you tell someone what you think before hearing what they think, you can cause their opinion to bend towards yours, often times without them knowing it”, “The only way somebody can know that they’re disagreeing with you is if they know what you think first. Keeping that to yourself when you elicit feedback makes it more likely that what they say is actually what they believe”, “To get high quality feedback it’s important to put the other person as closely as possible into the same state of knowledge that you were in at the time you made the decision”, “Belief contagion is particularly problematic in groups”
Tips to elicit those insightful cross-functional perspectives;
Elicit initial opinions individually and independent before the group meets. Specify the type of feedback or insights required and request an email or written thoughts be provided before meeting. Collate these initial opinions and share with group prior to meeting. Now focus on areas of “diversion”, “dispersion”, avoid using any language around “disagreement”
Anonymise feedback to group – this removes any influence from the insights or opinions of higher status individuals
Anonymising feedback also gives equal weight to insights and opinion and allows outside-the box perspectives to be heard
Anonymised feedback will also allow mis-understandings to be discussed and the team to grow in knowledge together
If the team needs to make a decision within a meeting; try
Writing down insights and passing to one person to write on a whiteboard – maintaining anonymity
Writing down your insights and pass to another person to read aloud to the group
If you must read your own thoughts to group – start with most junior member and work towards most senior
“Radical Uncertainty: Decision Making for an unknowable future”
Authors: John Kay & Meryn King
“The belief that mathematical reasoning is more rigorous and precise than verbal reasoning, which is thought to be susceptible to vagueness and ambiguity, is pervasive in economics”& Jean-Claude Trichet of the 2007-2008 GFC; “As a policy-maker during the crisis, I found the available models of limited help. In fact, I would go further: in the face of the crisis, we felt abandoned by conventional tools”
The authors draw a number of helpful lessons in the use of economic and financial models in business and in government;
Use simple models and identify key factors that influence an assessment. Adding more and more elements to a model is to follow the mistaken belief that a model can describe the complexity of the real world. The better purpose for a model is to find “small world” problems which illuminate part of the large world radical uncertainty
Having identified model parameters that are likely to make a significant difference to your assessment, go and do some research in the real world to obtain evidence on the value of these parameters to customers or stakeholders. Simple models provide flexibility to explore the effects of modifications or scenarios.
A model is useful only if the person using it recognises it does not represent the world as it is really is, rather it is a tool for exploring ways in which decisions might or might not go wrong.
Uncertainty : Howard Marks : https://www.oaktreecapital.com/insights/howard-marks-memos/
In his May 2020 newsletter to Oaktree Clients, Howard Marks notes the field of economics is muddled and imprecise, there are no rules one can count on to consistently show causation, patterns tend to repeat, and while they may be historical, logical and often observed, they remain only tendencies. Excessive trust in forecasts is dangerous.
When considering current forecasts, he notes the world is more uncertain today than at any other time in our lifetimes, the ability to deal intelligently with uncertainty is one of the most important skills, the bigger the topic (world, economy. Markets, currencies, interest rates) the less possible it is to achieve superior knowledge and we should seek to understand the limitations of our foresights.
A forecast is a statement about the future, a future we cannot know everything about , yet it remains a useful tool for decision making, scenario modelling, stress testing and planning. The map is not the territory, so with forecasting we should learn from better practices around collating diverse views and data, building cognitively diverse teams, constantly challenging assumptions, leverage the wisdom & insights of your subject matter experts, maintain intellectual humility & resiliency facing uncertainty, use models wisely and adopt a bayesian approach.
“No amount of sophistication is going to allay the fact that all your knowledge is about the past and all your decisions are about the future.”
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Article written by Mark Easdown
If your business is having issues with cash, it's important to take proactive steps to address the problem before it becomes a crisis.