Get the balance right! • 5
Service providers need to leverage resources effectively to drive innovation and achieve desired outcomes over time. Smart visualizations of the innovation pipeline and portfolio might help leaders and teams drive fruitful discussions, uncover interconnections, make informed choices, build alignment, and ultimately get the balance right. In the first four blog posts, I expanded the scope of service innovation and explored ways to visualize the innovation portfolio of a service provider. In the final blog post of the series, I cover alternative ways to visualize uncertainty and risk.
Spreading bets in an uncertain world
Operating in an uncertain world, service providers place strategic bets and take calculated risks on innovation projects to unlock value in the core/legacy business and uncover new sources of value in transformational endeavors. (Adapted from Meyer, 2020, to fit the three tensions of service innovation.)
Strategists and innovators spread their bets across the innovation portfolio, balancing sure and safe bets that may have lower returns with solid, side, and slim bets that may have higher returns. At one end of the spectrum, sure bets are no-regret options with a high chance of success in all future scenarios (for a specific time horizon). At the other end, slim bets are long-shot options with a chance of success in only one or two scenarios. (Adapted from Meyer, 2020, to fit the three tensions of service innovation.) See figure 1.
Figure 1. Five types of strategic bets placed on a spectrum from low to high chance of success (slightly adapted from Meyer, 2020)
Strategists and innovators take calculated risks, placing bets after careful consideration of potential benefits, required commitments, and the chance of success/failure (based on Meyer, 2020).
Potential benefits cover financial impact (↑ revenue, ↑ productivity, ↓ waste, ↓ costs, ↑ customer lifetime value, etc.) as well as non-financial impact (↑ differentiation, ↑ brand equity, ↑ customer engagement, ↑ organizational learning, ↑ leadership commitment, ↑ organizational responsibility, ↑ employee engagement, ↑ barriers to entry, etc.). (Inspired by Meyer, 2020.)
Required commitments include resource commitment (dedicating money, capabilities, time, and attention), political commitment (securing internal support and putting your reputation on the line), cognitive commitment (embracing certain perspectives and endorsing certain scenarios), and emotional commitment (investing your heart and attaching yourself emotionally). In other words, people invest financially, reputationally, intellectually, and emotionally to make their strategic bets a success, limiting their ability to ‘play the field’ and pursue other options. (Meyer, 2020)
Failure is broadly defined as significantly missing the objectives that were used to justify the investment (Day, 2007). In a world of uncertainty, the chance of failure increases (the chance of success decreases) when:
The process of developing, implementing, launching, and scaling envisioned solutions is deemed ‘difficult’ due to internal and external innovation hurdles (adapted from Matheson & Matheson, 1997; Matheson, n.d.).
The evidence to support the desirability, viability, feasibility, and adaptability of envisioned solutions is limited to ‘slides and spreadsheets’ (Osterwalder et al., 2020).
The familiarity/fit of envisioned solutions with existing business models, technical competencies, and markets is deemed distant/poor (Abernathy & Clark, 1985; Day, 2007; Pisano, 2015; McGrath, 2020a).
Visualizing levels of uncertainty and risk
One way to visualize uncertainty and risk in the portfolio is by mapping the relative impact of individual projects against the chances of success/failure.
According to Matheson & Matheson (1997), impact is defined as the expected size of commercial value (NPV, net present value) and chance of success as the probability of overcoming internal and external innovation hurdles (the level of ‘difficulty’).
Subsequently, using a classic two-by-two matrix, innovation projects fall into four categories. Bread-and-Butter projects (low impact, low difficulty) produce reliable, if unexciting, returns. White Elephants (low impact, high difficulty) should be killed or repurposed. Oysters (high impact, high difficulty) are typically early-stage projects with blockbuster potential. Pearls (high impact, low difficulty) are exceedingly rare, only found by ‘opening a lot of oysters.’ (Matheson & Matheson, 1997; Matheson, n.d.)
According to Osterwalder et al. (2020), impact is loosely defined as how lucrative the business idea could be for the company if it turned out to be successful (‘financial potential’). Chance of failure is determined by the lack of evidence beyond slides and spreadsheets to prove desirability, viability, feasibility, and adaptability (‘innovation risk’). Subsequently, innovation projects fall into four overlapping categories: Safe Plays (small financial potential, strong evidence of success); Niche Opportunities (small potential, weak-to-no evidence); Promising Concepts (large potential, weak-to-no evidence); and Rising Stars (large potential, strong evidence).
In figure 2, I have combined Matheson & Matheson’s Innovation Screen (R&D Grid) with Osterwalder et al.’s Explore portfolio into one 2x2 matrix.
Figure 2. Mapping the relative impact of innovation projects against the chances of success/failure (Matheson & Matheson, 1997; Osterwalder et al., 2020)
A second way of visualizing uncertainty and risk is to map different types of uncertainty against each other (based on the familiarity or fit with existing business models, markets, technical competencies, etc.). For example, McGrath’s Opportunity Portfolio (2020a, 2020b) visualizes how the service provider is investing across different levels of uncertainty. Other similar visualizations include Day’s Risk Matrix (2007), Nagji & Tuff’s Innovation Ambition Matrix (2012), and Pisano’s Innovation Landscape Map (2015).
On a similar note, it is possible to map three levels of uncertainty to the innovation portfolio of service providers (see blog post Get the balance right! • 4). Uncertainty is here defined as the lack of organizational (or ecosystem) knowledge required to improve existing solutions and/or create new solutions. Projects with medium or high uncertainty require knowledge that the service provider (or ecosystem) does not yet possess. Strategies to reduce uncertainty include: strategic foresight; exploratory research; sensemaking; experimentation; prototyping and evaluative research; continuous deployment; and piloting. See figure 3.
Figure 3. Mapping three levels of uncertainty to the innovation portfolio of service providers
References
Abernathy, W.J. & Clark, K.B. (1985). Innovation: Mapping the winds of creative destruction. In: Tushman, M.L. & Moore, W.L. (Eds.), Readings in the management of innovation (2nd ed.). Harper Business.
Day, G. (2007, December). Is it real? Can we win? Is it worth doing? Managing risk and reward in an innovation portfolio. Harvard Business Review.
Matheson, D. (n.d.). SmartOrg has invented methods that support great portfolio conversations. SmartOrg.
Matheson, D. & Matheson, J. (1997). The smart organization: Creating value through strategic R&D. Harvard Business Review Press.
McGrath, R. (2020a, December). Building a proficiency for game-changing innovation and growth: Mastering the Opportunity Portfolio. Medium.
McGrath, R. (2020b, December). Put your resources against your best opportunities! Innovation Roundtable. YouTube.
Meyer, R. (2020). Strategic bets framework. TIAS School for Business and Society.
Nagji, B. & Tuff, G. (2012, May). Managing your innovation portfolio. Harvard Business Review.
Osterwalder, A. et al. (2020). The invincible company: How to constantly reinvent your organization with inspiration from the world’s best business models. Wiley.
Pisano, G. (2015, June). You need an innovation strategy. Harvard Business Review.
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