The state-of-the-art report is the starting point, not the end of the monitoring process. These hypotheses make it possible to detect technological, regulatory, competitive and commercial changes throughout the project, even after the results have moved into commercial exploitation.
The state-of-the-art report —SOTA, for short— identifies the current state of the technology, the key players in technological and sectoral innovation, and the principal sources of information. It also informs the decision on whether or not to undertake the project. The next step should be to deploy a series of basic questions about the external environment in order to strengthen the projectand make it more resilient. These questions should remain active throughout the entire execution phase, until the product reaches the market. They should continue to be monitored even after that milestone has been achieved: during the next phase, the marketing and sales teams will become the beneficiaries of that intelligence.
We have compiled ten intelligence hypotheses that are independent of the sector and technology involved and should be considered in any R&D project. Deploying them in specific projects will require these questions to be adapted and possibly complemented with additional ones.
An emerging technology may outperform the one initially selected in terms of performance, cost, sustainability, scalability or ease of adoption.
If a relevant alternative appears, we will need to broaden the scope, conduct a new state-of-the-art report on it and compare both development paths. In some cases, we may have to take the painful decision to discard work already completed, repeat part of the investment in knowledge and resources, and redirect the project towards the new option.
For example, if we are developing multilayer packaging to achieve certain barrier properties and a new coating emerges that delivers similar performance using a recyclable mono-material structure, we should assess whether the development should be redirected before continuing to invest in the initial solution.
Patent applications that did not exist when the initial SOTA was prepared may be published during the execution of the project. They could protect a technology, component, manufacturing process or application close to our own development.
Their detection should trigger a Freedom to Operate review by the technical and legal teams. The response might require us to modify the design, negotiate a licence, protect alternative solutions or abandon a particular line of development before investing any further.
For example, if we are developing a new ingredient through precision fermentation, a patent published during the project could protect the microorganism, the production process or the intended food application.
We should not monitor only products that have already reached the market. Patents, scientific publications, publicly funded projects, job advertisements, acquisitions, technology agreements and pilot programmes may reveal that a competitor is following a similar path.
These signals may lead us to accelerate the project, strengthen its differentiation, protect the knowledge generated more effectively or focus on a less contested application.
For example, if we are developing an artificial intelligence solution for industrial maintenance and a competitor begins recruiting specialists in this field, announces a partnership with a machinery manufacturer and launches a pilot programme, these could be signs that it is preparing a similar solution.
Regulation may change the requirements applying to materials, processes, data, functionality, safety, sustainability or the intended use of the expected product.
Monitoring should cover national and international regulation, as well as the rules applying in all the markets in which we intend to commercialise the solution. A regulatory change may force us to modify specifications, carry out additional testing or delay the launch. Conversely, it may open up a commercial opportunity.
For example, if we are developing an ingredient obtained through cell culture or precision fermentation for commercialisation in several countries, a change in the procedures for authorisation, labelling or demonstrating safety could alter the timescale, costs and selection of launch markets.
Another example: if we are developing new food packaging, a future restriction on certain materials, added substances or packaging formats could force us to reformulate the solution. However, it could also favour our development if it replaces the affected alternatives.
Beyond mandatory legislation, many solutions depend on technical standards, sector-specific certifications, interoperability protocols or architectures that become dominant.
A new standard may render an interface obsolete, impose additional testing or favour an alternative technology. It is therefore advisable to monitor standardisation bodies, industry associations and the decisions of the principal actors within the ecosystem. Whenever possible, the company should participate actively in the committees defining these standards.
For example, if we are developing a healthcare application to support clinical decision-making, the adoption of new interoperability, traceability or validation requirements by key actors —such as data models— could require significant changes to the product architecture and its integration with hospital systems.
In an open innovation environment, a partner may begin collaborating with one of our competitors on precisely the same subject on which it is working with us.
If this situation is detected, at least three teams should be activated. The legal department should review the collaboration agreement and the associated confidentiality commitments. The R&D team, which maintains direct contact with the partner, should ensure that everyone involved understands and complies with the agreed conditions. Finally, the counterintelligence team should review all the information published about the project, whether by our company or by the partner.
For example, we may be developing a product with the support of a technology centre or university institute when a competitor announces a collaboration agreement with the same organisation, or when we detect the announcement of public funding for a joint R&D project between them.
The project may depend on highly specific materials, components, equipment, software, data or suppliers. A supply interruption, corporate acquisition, trade restriction, product discontinuation or significant price increase could compromise its viability. In another article, we discussed how the Intelligence Function can be applied to the early identification of supply-chain disruptions. Here, however, the aim is to broaden the scope and approach the question strategically, beyond monitoring established procurement processes.
Monitoring should identify alternative suppliers, new production capabilities, obsolescence announcements, price changes and geopolitical risks. The objective is to prevent the project from reaching its technical milestones while relying on an excessively fragile supply chain.
For example, if a software solution depends on an artificial intelligence model, cloud infrastructure or a third-party API, a change in pricing, terms of use or availability could force us to redesign the architecture before launch. As we have seen recently, geopolitics also affects supply chains, including those of software products.
A technology may work in the laboratory but fail when transferred to production. We should monitor new manufacturing methods, industrial yields, energy costs, rejection rates, equipment availability, maintenance requirements and the scaling experiences of third parties. Expected financing and profitability should not be overlooked either: banks and investment funds are often influenced by trends, and the trend may begin to show signs of fading while we are still in the development phase.
The question is not simply whether we can build the product, but whether we will be able to manufacture it repeatedly, profitably and safely, and at the capacity required to serve the market.
For example, if our project focuses on the transportation of green hydrogen and requires external financing to build infrastructure or achieve industrial scale, the cancellation of investment projects, withdrawal of investors or reduction in expected demand could force us to review the timetable, scope or even the continuation of the project.
A project may successfully address a need that is no longer a priority by the time the product reaches the market. Customers may have changed their processes, adopted an alternative solution, reduced their budgets or raised their expectations.
We should therefore monitor how needs, purchasing criteria, essential functionality, willingness to pay and internal barriers to adoption are evolving. This intelligence may require us to revise the product requirements, value proposition or even the target segment.
For example, if we are developing packaging whose main benefit is recyclability and detect that the sector is beginning to prioritise reusable systems, absolute reductions in material use or lower logistics costs, we may need to reconsider the value proposition, even though the general need to move towards more sustainable packaging remains.
During the project, direct or indirect signals may emerge indicating that an organisation is seeking, evaluating or requiring a solution such as the one we are developing.
In that case, we should act immediately: contact the prospective customer, explore its need and propose its participation as a beta user, pilot customer or validation partner. Even if it cannot yet become involved in the development, it should be qualified as a future opportunity and transferred to the marketing and sales teams.
For example, if a food manufacturer announces an innovation challenge, tender, pilot project or search for partners related to the technology we are developing, we should contact the company and assess whether it could participate as a beta user or launch customer.
These hypotheses should not be closed when the project ends or when the product reaches the market. Commercial launch does not eliminate uncertainty: it changes the decisions that need to be made and the people who need to make use of the resulting intelligence deliverables.
During the early stages, monitoring will primarily serve those responsible for R&D, Innovation, Intellectual Property, Regulation and Operations. Its purpose will be to reduce technological risks, detect alternatives, protect freedom to operate and ensure that scaling remains viable.
As the product approaches the market, some responsibilities should be transferred to, or shared with, Product, Marketing and Sales. Monitoring will then focus on identifying changes in the needs of the target segment, competitor movements, collaboration opportunities, prospective customers and early signs of adoption.
The objective is therefore not to create a temporary monitoring system for each project and dismantle it when the project ends. The knowledge, sources and hypotheses developed should be integrated into the company’s Intelligence Function, with responsibilities reassigned and the questions adapted to each new stage of the product life cycle.
Defining the questions is only the first step. To generate value, they must become part of a continuous monitoring system: they need to be translated into search and filtering criteria, the appropriate sources must be selected, responsibilities assigned, the resulting signals analysed, and the conclusions delivered to the people who make the decisions.
Antara’s solution greatly simplifies this entire process through the straightforward modelling of intelligence hypotheses supported by structured sectoral and technological vocabularies. This makes it possible to express complex questions, monitor information in several languages and apply the same criteria to very different sources: news, scientific publications, patents, corporate websites, alerts, newsletters and internal repositories.
The combination of sectoral semantics and artificial intelligence helps reduce noise and prioritise information that is genuinely related to each hypothesis. Analysis is conducted using traceable signals linked to their original sources, enabling teams to interpret the information, discuss its implications and justify the decisions taken. The process also includes AI-assisted analysis while avoiding hallucinations, which are particularly dangerous when critical decisions are involved.
The collaborative environment also makes it possible to assign each hypothesis to the appropriate specialists and modify that allocation as the project progresses. A question initially managed by R&D can subsequently be transferred to Product, Marketing or Sales without losing the history, monitored sources or accumulated knowledge.
In this way, the state-of-the-art report ceases to be an initial snapshot and becomes the starting point for a living intelligence system capable of accompanying the project from its conception through to commercial exploitation.