Across all industries, companies face ever-increasing pressures to generate new sources of revenue. As competitors accelerate the rate of innovation to meet revenue demands, senior leaders are asked to drive more and better innovation initiatives. Innovation is no longer just a buzzword; organizations are now dedicating significant resources to the art and science of innovation. Consider these findings from two recent surveys on innovation:
- 72 percent of CEOs believe rapid technological change is their biggest challenge.
- 95 percent of respondents consider innovation a management priority.
Point B Perspective
Financial analysis is fundamental to creating an innovation path that aligns with a company's strategic priorities. Unfortunately, most innovation teams are hamstrung by traditional financial analyses that don't account for the uncertainty and unpredictability of the type of projects they take on. As a result, innovation strategy often ignores a company's financial imperatives.
To overcome this challenge, innovation teams can leverage the power of Monte Carlo simulation to gain clarity about the goals they should aim for.
Unlike traditional analyses that tell you what is possible, Monte Carlo simulation tells you what is probable, such as:
- How likely are we to achieve our revenue goals in five years?
- What is the likely gap between our five-year revenue goals and our likely five-year performance?
Tackle false assumptions
Monte Carlo simulations can help banish the false assumptions that inhibit innovation teams from using financial analyses.
Some organizations assume that having flexible goals for their innovation teams will lead to more creative outcomes. However, recent research shows the opposite is true. Companies that approach innovation with a strategic focus actually end up being more flexible in their execution, whereas those that approach innovation opportunistically become rigid in their ability to innovate.
Second, most people in organizations are used to static financial analyses that appear to share the “right” answer. When uncertainty is high, as it is in most multi-year innovation projects, Monte Carlo simulation becomes an invaluable way to assess key assumptions to gain clarity on strategic direction.
Understand your growth gap
Organizations are frustrated when the case for innovation is stated obliquely, with statements about "unlocking new sources of revenue" that may never materialize. A key problem is that companies often do not effectively address the uncertainty in their five-year revenue goals. Traditional financial planning tools provide only a couple of possible scenarios to consider. Consequently, companies only plan for what they want to see happen, not for what is likely to happen.
Calculating the difference between planned five-year revenues and likely five-year revenues can lead to a powerful insight—the probability that a company will either hit, miss or exceed its five-year goals. Depending on the health of your core businesses, this growth gap can be minor or extremely significant. Whatever your finding, the information will help clarify where your innovation team can best focus its efforts.
Embrace probability, not possibility
Monte Carlo simulation can enhance the effectiveness of a growth gap analysis by generating compelling and digestible insights.
To help a client set its innovation strategy, we used Monte Carlo simulation to estimate its five-year growth gap. Subtracting the five-year strategic plan goals from the simulation results led to a crucial insight: The company had only a 38 percent chance of meeting or exceeding its five-year goals, with an estimated average growth gap of 20 percent. This insight led the client to rethink whether the innovation team should focus on closing this growth gap or set its sights higher.
Collaborate to build support
Like all financial analyses, the success of using the results from a Monte Carlo simulation depends heavily on the buy-in and support of key decision makers. Rather than bringing a completed growth gap analysis to key decision-makers as “the answer,” consider engaging key stakeholders in defining, refining and conducting the analysis. The true value of the analysis will emerge when decision-makers throughout the organization understand and shape the key assumptions used in creating the model. With approval of the model inputs, the rest is just math.
The Bottom Line
Growth gap analyses that leverage Monte Carlo simulation are a valuable way to incorporate uncertainty into innovation strategies. These simulations will improve the overall quality of your predictions as well as your ability to make more timely decisions.