Running a successful innovation program is a portfolio management problem, not a brainstorming problem. Most organizations generate plenty of ideas. The harder work is making explicit decisions about which bets to fund, which to kill, and how to allocate effort across fundamentally different types of work.

This hub orients you in that territory. It links to the concepts, guides, and related hubs most relevant before your organization makes its first moves.

What Innovation Strategy Actually Means

Innovation strategy is a set of explicit decisions about which types of innovation to pursue, how to fund them, and what outcomes will signal progress. Without it, innovation programs fill with activity but produce no durable change in what the organization builds or how it competes. Strategy is what separates innovation as a repeatable capability from innovation as a quarterly mood.

McKinsey research on innovation performance consistently finds that 84% of executives consider innovation critical to growth, yet fewer than 10% are satisfied with their organization’s performance. The gap is almost never a shortage of creativity. It is a shortage of explicit portfolio decisions backed by accountable leadership.

Alphabet illustrates what disciplined looks like. Its three units — Google, Other Bets, and investments — each run with distinct resource rules, success metrics, and governance structures. Each type of bet is protected from the short-term economics of the others.

Why Innovation Programs Break Down

Most innovation programs fail at the selection stage, not the ideation stage. Organizations collect ideas well but have no shared criteria for deciding which ones deserve resources, and no single decision-maker with both authority and accountability for the portfolio as a whole.

BCG’s annual study of innovation leaders finds that top-quartile innovation performers are 2.5 times more likely than average companies to maintain explicit portfolio allocation rules and hold leadership directly accountable for the portfolio balance. The fix is not a better brainstorming workshop. It is a governance structure that protects different types of bets from competing for the same pool of resources.

The second most common failure is measuring too late. Revenue from new products appears years after the decisions that produced it — which means organizations relying on financial results to steer their innovation program are always making corrections in the wrong quarter.

Three Decisions to Make Before Designing Any Process

Three strategic questions must be answered before any process design makes sense. Skipping them produces a well-designed process aimed at the wrong target.

What types of innovation are you pursuing? The three-horizon model — core improvements, adjacent opportunities, and transformational bets — provides a working frame. McKinsey research suggests a 70/20/10 allocation across the three horizons as a starting point, though the right ratio depends heavily on industry dynamics and competitive position.

Who owns the portfolio? In most organizations, innovation is distributed across product, R&D, strategy, and business units simultaneously. Unclear ownership creates duplication and allows each function to optimize locally rather than for portfolio health.

How will you measure results before revenue arrives? Useful leading indicators include the number of experiments running per quarter, the cycle time from validated idea to funded project, and the portfolio balance across horizons. These give you something to steer by now rather than waiting for lagging financials.

Concepts to Understand First

Get clear on these terms before designing your process:

  • Innovation Strategy — The decisions that shape which innovations to pursue, how to fund them, and how to measure success.
  • Innovation Portfolio — A structured view of all active innovation bets across different horizons and risk levels.
  • Innovation Types — Incremental, adjacent, and transformational work serve different purposes and require different governance.
  • Innovation Funnel — The end-to-end process for capturing, evaluating, and advancing ideas toward impact.
  • Innovation KPIs — The metrics that tell you whether your innovation investments are producing results.

Guides That Show You How

Frequently Asked Questions

What is the first step in building an innovation program?

Define what you are optimizing for before designing any process. Most programs start with idea collection tools, but the real constraint is decision-making: who decides which ideas get resourced, by what criteria, and with what budget authority. Answering those three questions makes every downstream design choice considerably easier.

How much budget should innovation receive?

McKinsey benchmarks suggest allocating roughly 70% of innovation investment to core improvements, 20% to adjacent opportunities, and 10% to transformational bets. Absolute totals vary by industry. Capital-intensive sectors typically invest 3–5% of revenue. Software companies often run higher.

What is the difference between innovation and R&D?

R&D is one specific input to innovation. It describes structured research and product development activities, usually inside engineering-heavy organizations. Innovation is broader — it includes business model changes, process improvements, service redesign, and organizational capability building that have nothing to do with formal R&D.

How do you measure innovation performance before projects ship?

Use leading indicators: experiments running per quarter, time from validated idea to funded project, portfolio balance across horizons, and the rate of ideas advancing through the funnel. Revenue from new products is the right long-term measure but arrives far too late to function as a steering signal.

Does an innovation program need a dedicated team?

Not always. Distributed ownership — roles embedded across business units with a small central function providing methodology and governance — often works better than dedicated labs for core and adjacent innovation. Transformational bets, which need protection from short-term business economics, tend to benefit more from structural separation.