It’s a familiar scenario for many large organizations: Great ideas for digital innovations never make it past the minimum viable product stage. A small subset of users benefits, but wider deployment — and value creation for the organization as a whole — never materializes.
There are both strategic and operational barriers to “scaling at scale,” as described in a new research briefing from Nils O. Fonstad, Martin Mocker, and Jukka Salonen at the MIT Center for Information Systems Research. Strategic barriers prevent executives from committing to digital innovation, while operational barriers typically include the lack of technology or skills to widely deploy an innovation to the end-user population. As a result, there’s no framework in place to help companies scale multiple digital initiatives, and realize significant value from them.
Drawing on the example of multinational energy company Repsol, which realized 800 million euros in cash flow from bringing more than 300 digital initiatives to scale over a five-year period, the researchers identified five key steps to overcoming the most common obstacles to scaling digital innovation.
1. Build business commitment.
Most initiatives will be doomed to fail if they are merely delegated to digital or IT units. For each innovation initiative, a business unit should select a product owner and a business sponsor who will be jointly accountable for hitting that initiative’s cash flow targets. Meanwhile, representatives from the CFO’s office should be ready to validate the numbers. At the C-suite level, executives should be expected to own innovation initiatives and identify strategic targets for them, such as profitability, efficiency, or sustainability. Taken together, these actions help ensure that business units actively lead digital initiatives.
2. Minimize business risk.
The corporate level should cover all costs during an initiative’s ideation, conceptualization, and early production phases. Only once initiative leaders have sufficient evidence that the innovation can generate value and proceed to the scale-up stage should the business unit be on the hook financially. This lets business units test freely in the early stages without the fear of financial liability for something that ends up not quite working. At Repsol, business units were able to test and learn whether investing in an initiative would yield value before they committed fully. This helped contain costs, because most of the total cost of each innovation — about 70% — accrued after the MVP stage.
3. Provide shared technology and talent.
While initiatives need autonomy, they also need to be sufficiently coordinated to avoid wasting resources on building essential yet nondifferentiating components (and indebting the organization with technology and data “spaghetti,” risky operational complexity, and redundant costs). Instead, businesses should set up hubs of shared technology and talent for data storage, analytics, robotics, user experience design, and other relevant tasks and commit them to helping initiatives succeed. At Repsol, each initiative is led by both a product owner from the business side and a technology lead from the shared technology hubs. The hubs develop shared resources based on what initiatives need. This allows them to better and more quickly address common challenges while reducing the development cost per initiative, thus enabling the business to realize more value.
4. Streamline handoffs.
Transitioning an MVP from the business unit that created it to the operational unit that puts it into production shouldn’t be painful. Repsol transformed the handoff experience from one that was like “pushing a boulder up a mountain” to one where the innovation “slides down a mountain,” according to an employee. Embedding operational staff members within the innovation teams in the early stages of an initiative helps enable more seamless handoffs by identifying and addressing potential operational issues before they have a chance to blow up and impact the entire business.
5. Embrace continuous change.
Companies should view both digital innovations and the shared resources that produce them as living products that evolve as market conditions change. Executives need to consider the value of internal talent to monitor initiatives, measure success, and make adjustments accordingly — for example, by assigning internal data scientists to take ownership of all aspects of developing artificial intelligence models.