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I recently watched a Ted Talk by Professor Tali Sharot, a specialist researcher in Experimental Psychology at University College London. She described how optimism bias is rooted in our brains to the point where it’s an evolutionary trait.

Human brains integrate positive evidence more efficiently and faithfully than we do negative evidence. Our tendency is to overestimate the likelihood of experiencing good events in our lives. In short, we are more optimistic than realistic, and we are oblivious to the fact. 80% of the population display an optimism bias to some degree, so it comes to no surprise that this translates into the business environment.

This got me thinking about optimism bias in the world of product forecasting – how we adapt our behaviour, especially regarding new or recently launched products where there is a significant judgemental contribution. New product launches typically show a forecast accuracy of 40%-55% (after the first year of launch) and forecasts are heavily reliant on the judgement of stakeholders.

The optimism bias challenge is so prevalent in the real world that the UK Government’s Treasury guidance now includes a comprehensive section on correcting for it. A real-life example is the cost of hosting the Olympic Games which, since 1976, is over forecast by an average of 200%. If future bidders wanted to safeguard against this bias, they should bear this in mind.

Tackling optimism bias is therefor crucial. Research done by Professor Sharot shows that being aware of the bias does not shatter the illusion. This is key to our understanding as having a bias KPI in forecasting is not enough for it to go away- though it is certainly a step in the right direction. It shows us the magnitude of our bias but measuring alone is not enough to eliminate the human and organisational behaviours that drive it.

To add to the above, let’s also consider that there are two types of optimism. One is closely related to belief in our success and essentially backing ourselves. Studies consistently show that this type of optimism is valuable as it leads to success in academia, sports, and politics. For a new product forecast, we are backing ourselves and our team’s ability to outpace the competition and all our assumptions being right as we are personally invested in its success. This type of optimism is in fact necessary for stakeholder buy-in and team motivation, even though the reality is that not all our efforts will bear 100% commensurate results; some might deliver higher results while others will go the opposite way.

The second and more alarming type is blind unrealistic optimism, i.e. overconfidence in our assumptions and our ability to deliver. Overconfidence is “the most significant of the cognitive biases” for new launches according to research by the Tuck School of Business at Dartmouth. It leads to the setting of unachievable goals which initially might look tempting but, once the hoped-for results do not transpire, can lead to a demotivated workforce underperforming. This is often manifest by overlooking the basic facts and fundamentals and not planning for “What if” alternative scenarios. This is where mature forecasting and S&OP processes can play a vital role as they define risks and opportunities, drive scenario planning, and encourage get stakeholders from Commercial, Marketing, Finance, and Supply Chain on the same page.

From my experience, here are some of the steps that I have seen work best when it comes to ensuring that a forecast reflects all the opportunities without being unrealistically optimistic.

1. Promote Diversity of Thought

The question here is, who has input into your forecasts? We should be wary if only one team is influencing the forecast as this could lead to homogenous personality types dominating the inputs who will inevitably have blind spots. It is common to see teams who are so invested in their new product that they discount some basic facts around its launch assumptions. The more diverse the teams who have a say in the process, the more likely we will have a robust set of assumptions which have been pressure tested. We must ask the question: Does our culture actively encourage individuals to speak up and have a say, especially if they have a different opinion?

2. Document the Assumptions That Underpin the Forecast

On occasions you may hear from a colleague who has been intimately involved with new products saying, “I feel this will perform better than the competition or better than we previously thought”. But as demand and S&OP managers, we need to understand the assumptions behind the “feel” factor and what is driving this. Feelings don’t have numbers, however assumptions driving price, competitive intelligence, and market share can be analysed and documented to be shared with stakeholders. This is where we need to keep investing in soft skill training for demand and S&OP managers.

3. Do Scenario Planning

We live in a world where our decisions are influenced by our environment and work culture. There might be pressure to hit growth P&L targets, internal politics, or an individual is overriding everyone else. In new products, it is important to acknowledge we will always have the “known knowns vs known unknowns” in our assumptions. Setting up a Base vs Ambitious case scenario opens this debate at the S&OP table in a constructive way and forces us to break down what we know and what we are less confident about. We can prepare and execute both plans and, importantly, know what indicators will show which trajectory we are on. Base vs Ambitious do not have to conflict with each other. Having this discussion early sets us up for decisions on safety stock, late-stage customisation, inventory order points, and risk of write off, among other parameters.

4. Peer Review your New Product Forecast

One of the most effective S&OP practices I saw practiced in my FMCG career was cross-checking of assumptions by an internal, non-aligned stakeholder. For example, in Pharma this could be the commercial lead of Antibiotics stress testing a Respiratory channel forecast. In retail, this could be somebody from Health and Beauty looking at Clothing channel forecast assumptions. If this is done in an open environment and constructively, it produces a robust discussion that ultimately ensures the strongest forecast possible. This works best where the leadership culture of the company is open to taking feedback from the broader organisation and doesn’t work in silos.

5. Learn From Historical Launches

What caused you to be off your forecast last time you launched? Which assumptions turned out to be incorrect? This might sound like a fundamental building block of the process, but it’s important to review your recently launched products on a 3 and 6 month rolling basis (shorter in FMCG) and have a learning feedback loop. Documenting this early on in a central repository is helpful. Often after-action reviews are in presentations that get lost over time as people move to new roles, thereby losing the institutional knowledge gained along with it.


To have success in our launches, we must believe we are equipped to execute every opportunity without becoming overconfident. A new product launch that has its forecast backed up by a robustly evaluated plan that considers all eventualities will have a significantly better chance of being a resounding win.