Obviously, mining companies do not put all their dollars into one location and hope for the best. Miners are managing a multitude of prospects at once, the more prospects that can be tested, the higher the chances of successfully turning one into a commercially viable mining operation.
Corporate innovation is no different. Innovation teams experiment and use a more iterative approach to better understand critical assumptions. They start small, then invest more and more resources as evidence accumulates.
At least, this is the theory. In reality, they are often not able to place enough bets. Most corporate innovation funnels and portfolios are too small and do not have enough innovation projects to reach a critical mass of disruptive ideas to test. Worse, some corporations have plenty of projects but lack the will to shut down bad bets early and redirect resources.
Failing Fast to Increase the Odds of Success
Large corporations don’t like to admit just how many innovation initiatives have failed. Let’s be honest, they hardly know it themselves. Startups are a good proxy for how likely it is to succeed in transformational innovation. About 1% of all Ventures that raised Venture Capital (VC) in the US reached a $ 1B valuation mark, thus reaching mystical unicorn status. When we take into account all startups that have not been able to raise VC money, the actual ratio of highly successful startups to those who had a go is even worse.
The question becomes not how transformational innovation can succeed with absolute certainty given these odds, but, how can we increase the likelihood of success?
The secret to testing a slew of high risk, high reward ideas is the ability to understand as early as possible if an idea has any hope of returning value and if not, letting it go as soon as possible. Every dollar retained is one that can be invested in another idea until the needle in the haystack is found.
This is where corporate innovation funnels experience a disadvantage, compared to miners looking for gold. Innovation accounting is designed to fill this gap.
Looking for Gold
Why do miners bother at all, when the chances of developing a fully functional mine are so low one might ask?
Inevitably, every mine runs out. If nothing is invested internally in finding new lucrative deposits, or if deposits are not acquired, the company will cease to exist.
So to test as many options as possible and find the “gold”, miners need to rely on a rigorous system that can quantify the likelihood of success and accounts for uncertainty. This allows for testing and killing off prospects with the least likelihood of success early.
Nearly everything about mineral exploration and developing a new mine is risky. Firstly, it is hard to find a deposit and to understand its grade and size. Even if there is a lot of high-grade ore it may simply be too expensive to dig it out. Commodity prices fluctuate almost daily, and this is before other risk factors including non-monetary ones such as environmental, political, social and other issues are taken into consideration.
Mineral explorers understand the variables of their business model and what further insights are critical to decrease the uncertainty of their model. Crucially this means that they can eliminate non-lucrative/viable explorations as soon as possible.
By not wasting any investments on an option that has no further chance of winning allows the dollars to be reinvested in fresh prospects, thereby maximising the number of prospects able to be explored and increasing the likelihood of success.
Mineral exploration is a process for finding economic deposits within the earth. The process is one that involves increasing confidence levels and lowering risk at each stage in the exploration process.
The Exploration Toolkit
There are a number of exploration experiments and research methodologies companies use to gain insights, from initial desktop research to non-invasive methods, geological, geochemical and geophysical methods, and of course, drilling to analyse samples.
When finding new deposits, miners start with low-cost exploration methods that take minimal time. These initial methods have limited accuracy, however, can quickly and cheaply identify and exclude uneconomical sites. As more locations are excluded, only the best prospects remain. Miners can then afford to spend more on expensive exploration techniques, to fully develop the sites into economic deposits with the knowledge that their exploration costs have a greater chance of yielding successful mines.
The steps might vary and can be further subdivided depending on the mineral and company.
The toolset is constantly evolving, the aim being to maximise the amount of useful information with the least amount of resources. 3D modelling is used to visualise and prepare geological and geophysical interpretations. When the lead indicators look good, the company may invest in drilling more expensive holes that further clarify the characteristics of the deposit. It is similar to building an MVP that can capture initial value.
When the first calculations are made a fully-fledged business case with complicated forecasting is not necessary for good decision making. This would be wasteful given the high likelihood that the project will not proceed.
The number of variables and complexity of the budget grows with each phase of the exploration process. The critical factor here is that new insights can be fed back into the model to make go/no-go decisions. This is key to understanding what type of research and experiments to run in the first place by informing what needs to be learned first.
Truthfully mineral exploration is far from a perfect science with zero-waste. It has to withstand significant pressure from within the business. New mines can be bought with the subsequent premium, similar to the mergers & acquisitions (M&A) argument corporate innovation often faces. As always, risk and reward are closely linked.
Looking for Unicorns
If the odds of success in creating a corporate venture that pays back 50 times the investment are as uncertain as establishing a new profitable gold mine, why do corporates bother at all?
Corporate business models are eroding faster than ever. According to this Innosight report, companies that have been in the S&P Fortune 500 in 1964 could expect to be there for about 33 years on average. This number is constantly shrinking and might be as low as 12 years by 2027. Continuously improving existing business models won’t be able to stop that trend. Only new internally developed or externally acquired business models will.
The Innovator’s Toolkit
Similar to mining teams, innovation teams have a set of tools to better understand the potential risk and value of their idea. The innovation toolset offers methods like Contextual Inquiry, Customer Discovery Interviews, Paper Prototyping, Product-Market-Fit Survey, A/B Testing and many more. For a more complete list of methods to test your business idea and how to do it well, please check out The Real Startup Book. (Maybe: We offer courses on this. To find out more, feel free to reach out.)
Where innovation teams differ from mineral exploration is the fact that innovation teams are creating new business models. Standard business casesthat can deal with quantities of available historical data are not relevant to evaluating breakthrough ideas. Most available data is either qualitative or has to be guessed because innovation projects by definition have no trading history and no ability to benchmark.
Without the ability to calculate the most likely outcome of an idea at least within a range, understand lead indicators and quantify uncertainty, decision making quality will always be below those of exploration teams. Their ability to test a myriad of ideas is not high enough. No matter how good a team is at qualitative research and experimentation the way organisations do financial and mission modeling will be a limiting factor to achieving the innovative potential and idea velocity needed to succeed. They need something better…
Innovation Accounting – to the Rescue
What we are looking for is the tools and ability to make better decisions. Innovation accounting gives us the toolkit to mimic the processes miners deploy in scouting for new mineral deposits – a metered funding approach to deploying resources through increasing confidence levels.
Innovation teams can’t benchmark their metrics when trying to prove a new business model. What they can do is to build a hypothesis-driven financial model. This model is built on lead, funnel-like indicators. Any trained team that is able to define the assumed customer journey can extract the needed metrics in a matter of hours. Storyboarding is a great vehicle for this. It is able to capture and organise qualitative and quantitative data. All that remains is to feed in assumed values for the most important cost items. Et voila – a hypothesis-driven financial model!
The next step is to define ranges for the variables rather than a single number we all know not to be true or a Best Case / Worst Case calculation we acknowledge is flawed reasoning.
Those ranges enable a Monte Carlo Simulation, the gold standard in analysing uncertain scenarios. Where conventional methods have a hard time modeling loops like virality and nonlinear equations, this innovation accounting approach makes it possible, giving us the most likely outcome as a range of likelihood. Projects can be compared and good choices made even in the earliest stages of the innovation funnel.
A critical advantage of this method is the fact that it quantifies not just the uncertainty of the entire business model but also each variable. This makes the otherwise difficult task of identifying the riskiest assumption clear, allowing innovation teams to know what to focus on when applying their innovation toolkit.
After running an experiment on those risky assumptions, teams are now able to quantify what they have learned by simply reestimating the range of a variable. This increases the predictive power of the model and clearly shows the value of the new insights in a very tangible way – everybody wins.
Most importantly, by quantifying variables earlier and feeding new insights back into the model, companies can make more reliable go/no-go decisions as early as possible just as miners use low cost/effort exploration to weed out early non-viable deposits. That’s exactly what we are looking for, the ability to better understand what is of value and being able to pull the plug as early as possible. The resources saved can be reinvested at the top of the funnel, thus allowing for a greater range of ideas to be tested, resulting in a higher chance of success.
Mineral exploration and transformational innovation is very risky
Miners know their metrics innovators need to figure them out
Effective innovation funnels can greatly benefit from innovation accounting