By Andre Marquis and Diana Jovin
In prior posts, we’ve talked about why large companies need innovation at scale. In contrast to innovation efforts that incubate a small number of ideas, innovation programs that test dozens to hundreds of business model innovations in a systematic way can deliver significant benefits to large companies. This large-scale testing gives valuable data about which new business model opportunities customers are ready to embrace and, just as importantly, which ones they are not prepared for today. With the data obtained from this type of continuous, systematic testing, large companies can make strategy a data-driven discipline and align their innovation investments in a capital-efficient way that generates measurable results quickly.
Why Scaled Innovation Testing Is Essential
Most of the companies we work with have historically taken an organization-centric approach to innovation. They describe their strategy from the company’s perspective – as sustaining or disruptive, design-centered, open or ambidextrous. The challenge with taking an organization-centric approach is that it tends to focus on current capabilities instead of figuring out when important customers are willing to change. Bill Gross of Idealabs analyzed his investments in this TED Talk and showed that timing was the most important factor in startup success, not the idea, team, business model, or investment amount. We can reinforce this observation across the thousands of innovation teams we work with.
A common example we see today – is it essential to invest in blockchain, data platforms, or AI business models? Those are testable strategic hypotheses, yet almost all the innovation programs we see do a very poor job systematically segmenting customers and then systematically testing across business model options to generate strategic insights. At best, a few innovation teams will do some “lean startup” work to try a couple of options.
Getting customer segmentation and timing right is ever more critical because there is increasingly less and less friction in two customer adoption dimension:
- when customers will change their behavior
- how much change they are willing to embrace to adopt new business models
Why Now? Technology Permanently Has Increased The Speed Of Customer Change
The key contributor to this lower friction behind customer change is technology. Successive waves of technology innovation over the last several decades have dramatically accelerated how we communicate in commerce and socially:
| Technology Wave | Market Impact | |
|---|---|---|
| 80s | Semiconductor/PC | Computing productivity to processes formerly managed by phone and by paper |
| 90s | Internet | Disintermediation and self-service to markets that had been serviced by distribution channels |
| 00s | Smartphone/app economy | Scale and continuous presence to community and communication |
| 10s | Realtime economy | Realtime data in business operations and apps, with operational flexibility – the ability to scale resources up and down through cloud-native architectures. |
Each of these waves of technology has enabled markets to change more rapidly, at a greater scale, and with a greater variety of business models. The former mainstay method of relying on one’s distribution channels and salesforce for market feedback and market share is long gone.
Consider, for example, a physical product such as fiberglass insulation. It is essential. It keeps us warm and cool in our homes daily, but we give it little thought. In the early ‘90s, we interviewed a number of dealers around the country who carried this product for the construction market. They stocked physical products, typically allocating warehouse space to three suppliers – one which gave them the best service and price for volume, a second which ensured availability, and third for niche features or significantly lower pricing. This approach to decision-making was repeated in dealers around the country. Fast forward to today – and manufacturers can market to consumers and builders directly. Shipping options have expanded – including drop-shipping where the product is never on a shelf at all. Many more people than the dealer can influence reviews and opinions. And there are now prefab homes (e.g. Tiny Homes and instant ADUs) that are also being marketed directly to consumers. The various ways to reach the end goal – of being the selected product inside a new structure – have increased. And, the channels for contributing and soliciting market feedback have increased. The insulation dealer is no longer the primary influencer in a purchase decision or in the customer-manufacturer feedback cycle.
In almost every industry, the opportunities for business model innovation have increased. Technology has allowed the elements of customer value to be pulled apart and reassembled in new and interesting ways, and then delivered at scale. Thales S. Teixeira and Greg Piechota’s recent book, “Unlocking the Customer Value Chain: How Decoupling Drives Consumer Disruption” has many good examples of how industries have quickly shifted based on value chain reconfiguration. Even with an agile process, delivering new features in existing products through existing value chains is no longer enough.
Continuous Customer-Driven Testing Delivers Continuous Foresight
Companies face the challenge of figuring out what strategies to pursue without good feedback mechanisms. The traditional product development process “feature innovation” race locks companies into their existing marketing and sales feedback channels – a classic innovators dilemma. Innovation incubators don’t test enough opportunities to inform the larger company’s strategy. Idea competitions don’t actually test the ideas generated on customers. Creating “innovation outposts” is still seen as a valid operational model. When we see companies discuss innovation strategy at Board meetings, it is about individual startup teams’ fate instead of reviewing the data from systematically testing a portfolio of options.
Rapid, scaled business model innovation is a different approach. Rather than considering whether customers need an incremental product feature or employee-generated ideas, companies use their innovation process to generate ideas across a spread of new product and business model opportunities structured way that spans potential future strategy options. Each new business model tested can now consider:
- Does a new business model affect existing customers?
- Does it “resegment” existing customers into adopters and laggards based on their desire to adopt a new offering immediately and what are those segment boundaries?
- Does it capture completely new customers?
- Does it require a customer acquisition and value delivery pipeline that is different from existing lines of business?
- Does it require Open Innovation – collaboration with partners and startups – deliver?
- Is there evidence that massive customer is likely to happen relatively soon, that is, there are the makings of a unicorn?
- What span of business model innovations is important to consider to detect potential unicorns and big wins?
Early Customer Traction With New Business Models Becomes The Key Indicator
By conducting continuous large-scale experimentation, companies can gain a view of how a particular business model innovations affect customer segments across a market. For example, are no customers interested based doing customer interviews, are some willing to try minimum viable products but will not commit to buying, or is there growing segment-by-segment adoption? Companies can then visualize:
- How the composition of customer segments in their market is changing
- How understanding new customer segment boundaries and adoption patterns affect their current customer mix and revenue patterns
- What upcoming product and new business model portfolio changes are needed to contribute to customer mix and retention goals?
- Whether strategy needs to direct new business model testing at retaining customers, growing revenue from customers, or creating new customers
Understanding how markets are changing and how that intersects with innovation investment can help companies be proactive about leading market change rather than be reactive to trends and trying to catch up to startups that already have traction.
Driving Strategy with Continuous Foresight: The Value Of Innovation Programs
Broad-scale business model innovation testing also helps lay the foundation for an agile, continuously adaptive strategy. This should be a conscious goal of innovation programs – contributing to strategy and forward-looking investments based on real customer traction data.
Two key elements to driving an agile, adaptive strategy are continuous testing and broad testing:
- Continuous testing is necessary to understand the timing and consequences of market change. For example, if you think back to the iPhone introduction, it was initially perceived as a niche product, focused on early adopters who appreciated the design and were willing to pay for it. Nokia still dominated the market with its broad portfolio of flip-phone designs, and consumers expected keypads on their phones. One could think about the iPhone as “not my market,” or “not likely to be the mass part of my market.” The introduction of the app store in 2008 was the key driver of the mass adoption of the iPhone. It then became a vehicle for an application universe that customers wanted. As it turns out, the phone itself was only a small part of the customer value. Continuous testing helps companies stay on top of assumptions about market dynamics and market direction.
- Breadth of testing across types of business model innovations and customer segments is also essential. By considering many business model innovation dimensions – customer, product, channel, delivery, finance, etc. – companies can obtain an unparalleled view of predictive markers about where a market is headed. This, in turn, drives focus on the strategic themes that are getting customer traction.
Remember, that timing – having the right offering at the right time for the right customer – is the key to innovation success and avoiding disruption. The bigger idea is that larger companies can be well-positioned to out-compete startups by using their innovation programs as a sensing network for strategies. Visualizing business model tests’ success across customer segments and strategic options is a way to generate continuous foresight.
We see lots of companies investing in startup scouting and corporate venture capital, which is another way of trying to generate strategic foresight. Unfortunately, that foresight often happens too late – after startups are already successfully disrupting the market and taking customers. We also worry that outsourcing to startups is simply giving up on creating the capacity to continuously innovate inside a company. That strategy ensures disruption!
Finally, we also see companies using trend research, scenario planning, technology mapping, and the like as their primary way of setting strategy. Those all assume we can predict the future. Unfortunately, when it comes to innovation, No One Can Pick Winners.
This is why our work has been so focused not only on running business model innovation as a scalable business process at the team level and putting each team’s validation results in the context of strategic hypotheses. It allows companies to visualize where early customer traction is occurring relative to strategic options. So foresight is based on real data from real customers in real-time. How do you visualize your innovation portfolio?
Ask Us!
If you want to learn more about our system for launching new businesses while generating continuous foresight, contact us here. Now is an exciting time in business model innovation!