Innovation management · Evidence · Portfolio decisions
A successful pilot can still be a poor investment if nobody can operate the solution at scale.
Arcus helps leaders connect innovation opportunities with customer or service needs, testable assumptions and practical implementation choices. The aim is to allocate money and scarce operating capacity to initiatives with a defensible path from evidence to use—not simply to generate more ideas.
The decision before the programme
01 / Which uncertainty could overturn the investment case?
02 / What would justify continuing, changing or stopping the initiative?
03 / Who will own adoption, operating costs and results after the pilot?
Separate learning from proof of a scalable solution
An illustrative organization pilots a new service with enthusiastic volunteers and substantial support from the project team. Users like the experience. Management proposes expansion, yet the pilot has not tested normal staffing, integration with existing work or willingness to pay. The result supports further inquiry, but does not settle the scaling decision.
Arcus’s central thesis is that innovation management should connect three distinct decisions: whether the problem is worth solving, whether the proposed solution addresses it and whether the organization can sustain delivery. A positive answer to one does not establish the others.
A portfolio can contain many busy projects while producing little usable innovation. Leaders need to know which uncertainty each activity resolves and which commitment comes next. Progress should be visible as better decisions and implemented value, rather than presentation quality or the number of prototypes.
Four explanations for stalled innovation
Identify the mechanism before commissioning another idea-generation workshop.
01 / The problem is weakly evidenced
An appealing solution may address an occasional inconvenience rather than an important unmet need. Examine current alternatives, user behaviour and the consequence of leaving the problem unresolved.
02 / The proposed solution is not working
The need may be real, but the design may not deliver an adequate outcome. Test the critical mechanism with representative users and conditions. Distinguish polite interest from actual use or commitment.
03 / Adoption and delivery are constrained
Procurement, integration, workforce capability or operating ownership may prevent use. Another feature may not resolve these barriers. Involve those who will run and support the solution before expansion is proposed.
04 / Portfolio commitments exceed capacity
Too many initiatives may compete for the same specialists, managers or customer attention. A project can be worthwhile individually and still be a poor next commitment. Compare sequencing and opportunity costs across the portfolio.
What authoritative evidence contributes
The OECD/Eurostat Oslo Manual 2018 distinguishes innovation from an idea or invention through implementation: the product is made available or the process brought into use. This is a measurement framework, not a claim that every implemented change creates value. It gives leaders a useful reason to distinguish research activity, experimentation and operational adoption.
Camuffo and colleagues’ 2024 large-scale replication on scientific entrepreneurial decision-making covers 759 firms across four randomized trials. The authors report an increased tendency to terminate ideas and a more nuanced pattern of major changes in direction. The finding challenges the assumption that stopping projects always signals poor innovation performance. Its entrepreneurial settings and specific intervention do not establish a universal result for large organizations or public services.
Arcus’s interpretation is to make disconfirming evidence useful. A test that leads to a well-supported stop decision can protect resources. A pilot that produces encouraging feedback but leaves the investment-critical uncertainty untouched may have less decision value.
The Arcus evidence-to-commitment review
Use this original management framework for one initiative before expanding it across a portfolio. It is a decision aid, not a validated forecast of commercial success.
01 / Need — What consequence matters?
Define the customer, user or service problem, current alternative and desired outcome. Establish why the problem warrants attention and whose behaviour or experience would need to change.
02 / Uncertainty — What could invalidate the case?
State the important assumptions about demand, technical performance, cost, risk and adoption. Identify the assumption whose failure would most change the next investment decision.
03 / Test — What evidence will change the decision?
Choose a proportionate test and define the interpretation before results arrive. Specify representative conditions, relevant comparison and the evidence that would support continuation, redesign or stopping.
04 / Commitment — What happens after learning?
Define the next funding and capacity decision, operating owner, dependencies and remaining uncertainty. Release resources in a way that matches the evidence and consequences of being wrong.
Worked example: customer interest versus viable demand
Suppose a fictional service concept attracts 80 positive responses from 100 research participants. The team describes this as strong demand. A subsequent test asks users to commit at the intended price and normal delivery conditions; only 12 do so. Neither figure should be treated as a guaranteed market conversion rate. The samples, questions and conditions differ.
The difference prompts competing explanations: price, unclear value, an inconvenient process, low urgency or a sample dominated by people unlikely to buy. A useful next test isolates the assumption that matters most. Reducing price without understanding delivery economics could improve uptake while weakening the investment case.
Compare launching a smaller service, redesigning the offer, partnering with an established provider or stopping. The decision should consider contribution after delivery and support costs, realistic reach, repeat use and operating constraints. Do not keep extending the pilot solely because the initial concept has an influential sponsor.
Compare practical innovation routes
The right route depends on uncertainty, strategic importance and implementation capability.
Build internally
Can develop distinctive capability and control. Requires specialist capacity, ownership and a credible support model. Risks include underestimating integration work and continuing because substantial effort has already been invested.
Buy or partner
Can provide established capabilities and reduce development time. Requires assessment of fit, supplier dependence, economics, information requirements and exit arrangements. A capable partner does not remove the organization’s adoption responsibilities.
Run a bounded experiment
Can resolve a material uncertainty before a larger commitment. Requires a specific learning question, proportional safeguards and a decision date. Repeated small pilots become expensive if none has a route to an operating decision.
Defer or stop
Can protect resources for stronger opportunities or await a necessary dependency. Requires a clear rationale and treatment of useful learning. Avoid rewarding project survival so strongly that teams conceal evidence against their own initiative.
Make implementation economics part of the experiment
Distinguish the cost of a pilot from the cost of sustained delivery. Include integration, training, service support, maintenance, governance, acquisition or outreach and any transition from the old process. Project staff may absorb costs during the pilot that an operating team cannot absorb later.
For example, a hypothetical solution that releases 1,000 staff hours annually but requires 600 hours of ongoing support leaves 400 hours before other effects. This does not automatically create cash savings: the value depends on whether the capacity can be redeployed, service outcomes improve or expenditure can actually be reduced. Validate both estimates under realistic use.
Agree the evidence needed for scale, the operating owner and the capacity that must be reserved. Compare the initiative with other demands on the same people. A positive financial forecast is incomplete if the implementation depends on resources already committed elsewhere.
How Arcus supports innovation decisions
An engagement can address a single growth opportunity or the effectiveness of a wider innovation portfolio.
01 / Frame the opportunity
Customer and stakeholder research, problem definition, strategic fit and assessment of current alternatives. Deliverables make the opportunity and important evidence gaps explicit.
02 / Design the learning
Assumption maps, research and experiment plans, decision criteria and a comparison of solution routes. The work connects each test to a funding or operating decision.
03 / Compare the commitments
Options analysis, cost and capacity scenarios, implementation dependencies and a portfolio recommendation. Leaders receive a clear distinction between demonstrated evidence, estimates and unresolved assumptions.
04 / Prepare adoption
An operating ownership and implementation roadmap, responsibilities, measures and review milestones. The goal is a supported transition into use, with a clear basis for continuing, changing or stopping.
Bring Arcus the uncertainty behind the initiative
Tell Arcus which opportunity you are considering, what has already been tested and which decision remains unresolved. We can scope focused research, an innovation workshop with a defined decision purpose or a broader innovation strategy. Please begin with the business question rather than confidential technical or customer records.
Related services include market research and cost-benefit analysis. View advisory experience through the central consultant directory.
Historical client example
The following case is retained from Arcus’s published portfolio. It describes research and strategic recommendations; no launch, revenue or investment-return outcome is claimed.
Case study: Fortune 500 Food Company
Problem: We have a roster of mature brands. How can we find new vectors of growth? What needs to change in our growth strategy?
Insight mining: Arcus researched 36 food and beverage segments and how these segments have evolved over the past 30 years. The findings were surprising. With increased travel and appreciation of other cultures, consumers have become more open to an experimental world view on food. This means that food has been given new meaning: it is about experimentation, discovery and surprise.
Solution: Arcus recommended strategic options at a brief 15-minute presentation to the management team at their weekly meeting. Our focus was on fast growing segments where ethnic foods intersected with convenience. We found some of the most promising options in ethnic frozen foods.
Historical roadmap endorsement
This endorsement concerns the innovation roadmap. The attribution below is historical; it does not establish current platform availability or deployment volume.
“The innovation roadmap provides a high level framework combined with detailed step by step explanations, which is grounded in the executional realities of new product developments. In my view, it is value-adding to both seasoned practitioners looking for a frame of reference for innovation projects, as well as to individuals looking to build or improve their innovation management competencies.”
– Mr. Ricardo Moreno, Global Marketing Manager, Sustainable Operations at DuPont Sustainable Solutions