How to find your ideal startup to innovate with corporate venturing

Corporate venturing is collaboration between established companies — from large corporations to SMEs — and innovative startups or scaleups to access new technologies, explore markets beyond their core business and accelerate innovation capacity.

For this collaboration to work, companies need to identify their best bets for collaboration. Adopting a scouting process provides a structured way to detect, filter and prioritize the most appealing collaborators.

Despite its growth, 68.9% of corporate venturing initiatives fail to achieve expected results. This is not due to a lack of interest in moving innovation outside the company, but because of organizational barriers.

Common issues include:

• Lack of clear strategy objectives.
• Misalignment between incentives and governance.
• Weak execution mechanisms.

In other words, the problem usually lies not with the startup, but with how the company designs, manages and integrates the collaboration.

Regarding scouting, the process may fail when exploration is fragmented or ad hoc. In such cases, companies struggle to identify opportunities that are both strategically relevant and sufficiently mature. Many companies choose the wrong startup, either because it doesn’t fit real needs, has been evaluated inconsistently, or simply comes into the project too late to generate impact.

Although widely practiced, startup scouting is not always systematic. It should be structured as a process to identify, select and evaluate external solutions aligned with innovation challenges.

This process serves three main functions:

• Structure the search. Organize identification, selection and evaluation sequentially.
• Turn information into decisions. Convert internal and external data into actionable insights.
• Generate opportunities. Build a qualified pipeline of projects for corporate venturing mechanisms (e.g., venture client or strategic alliances).

Putting a scouting process in place adds value, as ad hoc searches are often linked to poorer innovation outcomes.

Without structure, inefficiencies and poor allocation of management attention arise, especially in the early stages of identification and evaluation of opportunities.

A sequenced method can:

• accelerate R&D.
• anticipate trends.
• provide recurring access to disruptive solutions.

More important, it turns scouting into an operating system rather than a one-off activity, with shared goals and clear decision rules that improve collaboration and decision quality.

The process has three phases, each with a clear objective:

1. Identification defines what to look for:

• Strategic boundary setting.
• First search and preliminary filtering.

2. Selection decides who to back:

• Due diligence.
• Decision-making.

3. Evaluation turns selection into real collaboration:

• Engagement and negotiation.
• Integration and support.

The identification phase is the starting point of the process and focuses on defining what to look for. Its objective is to establish the strategic boundaries that will guide subsequent interaction. It is divided into two sub-phases:

• Sub-phase 1: Strategic boundary setting. This involves clarifying the intention (are we seeking operational improvements or exploring new markets?), defining innovation needs (through trend analysis or “hunting zones”), establishing governance, and deciding on the execution model (internal or external, proactive or receptive).
• Sub-phase 2: Search and preliminary filtering. This consists of generating a comprehensive list of potential projects and collaborators. To do this, digital databases (such as Crunchbase or PitchBook), AI tools, industry news, trend indicators and events are used.

Next, an initial screening is carried out to reduce this list to a manageable set of candidates. Criteria such as technology readiness level (TRL), market potential and financial strength are applied, often supported by initial interviews.

The selection phase introduces greater analytical rigor and aims to determine which startups, among those preselected, are most suitable for real collaboration. It is divided into two sub-phases.

• Sub-phase 1: Due diligence. This is a systematic validation process designed to reduce uncertainty and often requires additional interviews. It combines the evaluation of traditional dimensions (financial health, product viability, team) with emerging practices, such as the use of alternative data and artificial intelligence to detect reputational risks or inconsistencies. It may also include scenario analysis to anticipate how the startup would respond to market changes, such as shifts in demand or increased competitive pressure.
• Sub-phase 2: Decision-making. Rather than generating new information, this step involves consolidating and weighing the evidence gathered. Multi-Criteria Decision Analysis (MCDA) tools are typically used to score and compare candidates. It is essential that different stakeholders are aligned on the criteria, as misalignment can delay the final decision. Once the options are prioritized, the selected startups are presented to senior management.

This structured process can help improve the quality of the decision and strengthen its legitimacy, as it is perceived as more transparent and consistent.

The evaluation phase transforms the decision into results. At this stage, the selected startups move from being an option to becoming real collaborations with long-term impact. It is divided into two sub-phases.

• Sub-phase 1: Formalization (engagement) and negotiation. This involves defining the mode of collaboration (e.g., venture client or equity investment) to ensure operational and strategic alignment between both parties. It also requires negotiating critical terms such as success milestones, intellectual property (IP), financial commitments and performance metrics.
• Sub-phase 2: Integration and support. This focuses on operational implementation. It includes onboarding (assignment of liaison teams, communication protocols) and ongoing support (mentoring, access to corporate resources and quarterly reviews) to facilitate the startup’s integration and enable it to scale its solution within the organization.

To successfully lead corporate venturing, executives should consider six key principles.

• Seek clarity. Before searching, define objectives, criteria and governance. “Hunting zones” can help avoid fragmented efforts.
• Balance speed and rigor. Adapt timelines to the context but avoid both analysis paralysis and excessive haste.
• Use multiple channels. Combine desk research (digital databases such as Crunchbase, PitchBook and Dealroom) with fieldwork (accelerators and innovation events).
• Evaluate systematically. Apply clear criteria (such as TRL, market potential or financial strength) and reduce bias through structured templates, AI-driven data analysis and multicriteria scoring models.
• Commit to collaboration. Negotiation, integration and support are often as important as the selection itself. Clear contracts, defined metrics, aligned corporate cultures and ongoing support can facilitate scalability.
• Prepare for the future. Stay attentive to how generative AI, Web3 and corporate venturing squads are transforming interactions with the ecosystem.

As the authors emphasize, innovating with startups is not just about identifying opportunities occasionally, but about building a system that allows them to be identified, evaluated and consistently turned into value.

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