7 metrics to measure the impact of competitive intelligence

The impact metrics proposed by Antara have the primary purpose of ensuring the continuous improvement of the Intelligence Function, thereby maximising the value it brings to the company at all times. After all, what cannot be measured cannot be improved.

In a previous article we analysed the indicators collected in a SCIP survey of companies in the United States, and concluded that most of them were not advisable for a company starting its Competitive Intelligence project.

In that post, we suggested three criteria for a KPI to be applicable:

1. The KPI must be easy to calculate. The collection of improvement metrics should not involve an additional cost that we are unwilling to bear in the long term.

2. The data must be reliable, avoiding estimates or subjective responses wherever possible.

3. The indicator must be genuinely useful for the improvement of Competitive Intelligence. We must be clear about what we want to do with it.

Antara’s Proposal for Competitive Intelligence KPIs

Aligned with the above criteria, at Antara we propose starting with a series of seven basic indicators for a dashboard of the Intelligence Function:

1. Relevance of Competitive Intelligence for professional performance

2. Penetration within the organisation

3. Maturity of market intelligence focuses

4. Total volume of information

5. Intelligence load per analyst

6. Time dedicated per analyst

7. Relevance and quality of information

Let us take a closer look at each of these proposed indicators and how to calculate them.

Indicator 1: Relevance of the Competitive Intelligence Function for professional performance

This is one of the few indicators which, although subjective, meets the criteria of easy, reliable and useful. It is easy to obtain because it is simply a survey. It is reliable, because it captures personal perception, and the survey is carried out individually. And it is useful, as it provides information about internal traction and the support the company’s team will give to the Intelligence Function in order to expand and improve it.

We can survey people from any department involved in the Intelligence Function. Various methods can be used: asking each respondent to rate from 1 (not relevant) to 5 (crucial) how important Intelligence information is for their individual performance, or applying the Net Promoter Score (NPS) method by asking whether they would personally recommend that a colleague join the internal intelligence network.

Whatever method is chosen, the data collected can be classified in such a way that the indicator becomes useful, aggregating the responses according to the following table. This allows us to identify areas for improvement.

The remaining indicators are not only objective and quantitative, but with Antara Mussol we can obtain them automatically, making the generation of improvement metrics much easier.

Indicator 2: Penetration of Competitive Intelligence in the organisation

The penetration of the Intelligence Function in the organisation will be measured by the number of functions and people in the company who use the Intelligence Function.

Any function of the company can benefit from Intelligence, as we explained in the article The Three Musketeers: Competitive Intelligence in Strategy, Innovation and Operations. It may be the Innovation Department with technology watch, or HR identifying new best practices in people management, to name just two examples. The number of company functions that take advantage of competitive intelligence is an indicator of penetration in the organisation.

However, we must also add the total number of people consuming the information. As we will discuss in another article, it is not advisable to involve only a small number of people from each area. This second figure should therefore be combined with the first.

Indicator 3: Maturity of Competitive Intelligence focuses

To make things easier, we will calculate the number of issues being monitored in the market. Antara Mussol users call them intelligence hypotheses, and in some literature they are referred to as critical intelligence factors. For example: mergers and acquisitions in the sector, or the adoption of certain technologies by specific companies.

At the beginning it is easiest to be unspecific and launch questions that are too general to generate truly valuable information. For example: “I want an alert for any mention of any of my competitors.” This monitoring approach forces the same information to be distributed to several users, and obliges them to “dig through” the list of alerts to find something of real interest.

Over time, our interests will become more focused, breaking down the initial general questions into increasingly specific issues. This makes the indicator useful for understanding the maturity of our intelligence strategy.

Nevertheless, regardless of our level of maturity, we must avoid information overload and adapt our objectives to the size of the team involved and their availability to contribute to environmental monitoring — a risk we already discussed in Gargantua: Information Overload in the Intelligence Function.

Indicator 4: Total volume of information

The total volume of information (market signals) delivered to users is an absolute indicator of the coverage of our competitive intelligence.

This value cannot grow indefinitely, as it is limited by the workload and availability of the users involved, which are not infinite. These limits will appear in other indicators we will discuss below.

Indicator 5: Intelligence load per analyst

The intelligence load per analyst is the ratio of information delivered to a user daily, or over a defined period of time.

In our opinion, based on experience with dozens of corporations, a user should not receive more than a dozen market signals per day. This gives the indicator a target range. Exceeding the range can be even more harmful than falling short.

Of course, this is only a general guideline, and depends on each user’s availability and their level of reliance on market monitoring. For example, a sales professional who uses Intelligence to detect market opportunities will pay more attention to captured signals than someone in Talent Management monitoring regulatory changes or best practices. Even within Talent Management, someone tracking staff training opportunities in courses or seminars will use Intelligence signals more intensively.

Indicator 6: Time dedicated to Competitive Intelligence per analyst

This indicator can be obtained from the ratio of market signals read by each user within the defined interval. By multiplying this by the estimated reading time per signal, we can calculate the dedication, and even the cost for the company.

Obviously, the higher the volume of signals delivered, the lower this ratio will be, since the time each user can devote is limited.

This indicator, together with the next one, is particularly important and should be measured both at departmental and individual level. This way, we can detect specific departments and users who are not engaging with Intelligence, analyse the reasons, and either correct them or provide support to overcome obstacles.

Indicator 7: Relevance of the information delivered

The relevance of the information delivered is an indicator of the correct design of intelligence hypotheses; of how we have implemented critical intelligence factors.

As with the other indicators, we can obtain this data automatically with Antara Mussol: by combining the total volume of information read by users (indicator #6) with the ratio of market signals identified as relevant by them. We should also consider the number of opportunities and threats identified.

Again, besides the corporate-level value, we should consider this indicator at departmental and individual levels.

This indicator also has a derivative relating to the quality of the information delivered. Here we can count the number of signals that users identify as noise or as system errors when capturing information. Antara Mussol, in addition to its AI systems for minimising noise, offers disambiguation and context exclusion mechanisms that greatly facilitate this task for Intelligence leaders.

Conclusion

We must use metrics so that the entire organisation recognises the value generated by Competitive Intelligence and supports this key function within the company. Moreover, to improve the Intelligence Function we need to be able to measure performance consistently over time. For this reason, the calculation of metrics must be sustainable.

The Intelligence Function’s dashboard must be easy to implement and as objective as possible. To achieve this, we should rely on solutions that provide this data immediately and in exportable format, to feed our dashboard and allow us to perform our own ad hoc calculations.

Once our initial system of indicators is up and running, we can move on to more complex tasks such as combining these indicators with general business data and departmental performance. This will enable us to identify correlations, since a well-managed Intelligence Function will always generate a positive impact on business performance or the bottom line.

Other indicators could be added, such as the number of information sources under monitoring and their relevance ratios for the company’s intelligence. However, these and others can be considered secondary: for internal use by Intelligence leaders, and with less significance for the overall improvement of impact within the company.

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The opinions of the authors reflect their own views and not those of the company.