A lag on a dimension is only a problem if that dimension actually counts in the deals you want to win. So the first step is not closing the gap, but determining whether this is a dimension on which your peer group actually wins or loses, and that becomes clear from which dimensions determine whether you win in a market.
A company of 150 employees in professional services may, for example, score low on 'implementation speed'. That feels like a shortcoming, until the evidence matrix shows that customers in that market mainly choose based on 'proven results at comparable companies' and that speed of implementation barely played a role in the deals that were lost. A lag on a dimension that doesn't count then costs no deals. It then becomes a choice whether to address this, not a necessity. The reverse also applies: a small lag on a dimension that does weigh heavily in every deal is more urgent than that first impression suggests.
If the dimension does count, there are essentially three directions. Closing means actually eliminating the lag on the dimension itself: solving a lack of cases by gathering references, solving a lack of speed by revising the process. Compensating means leaving the lag as it is and building a lead on another dimension that weighs heavily enough to make up the difference in the customer's ultimate choice. Accepting means deliberately not pursuing part of the market, because the dimension on which you lag is precisely the dimension that segment weighs most heavily. A software company of 80 employees that is consistently found to be more expensive than the peer group can choose to compensate for that lag with a lead in ease of integration, instead of forcing a pricing strategy that eats into the margin.
A lag on price means something different than a lag on brand awareness, and that in turn means something different than a lag on product breadth. Price can often be moved in the short term, brand awareness takes time, and product breadth requires investment that doesn't always pay off in the short term. For those who want to know specifically where a price lag comes from, the free loss-on-price check is a first point of entry: eight questions that indicate which dimension within the pricing is leaking, whether that lies in the proposition, in the substantiation of value, or in comparability with competitors in the eyes of the customer. That distinction is needed before a route is chosen, because closing the wrong cause yields nothing.
A score of today is a snapshot at a moment in time, and that snapshot changes due to market movement, due to an acquisition at a competitor, or due to a new player rearranging the dimensions in the market. That is also why how often should you repeat a competitive analysis is relevant in the case of a lag: a dimension that scores weakly today may have been resolved a year from now, or may have slipped further, and only repeating the measurement shows which of the two it is. A company of 200 employees that half a year ago accepted a lag on 'digital visibility' because the peer group wasn't far ahead there either, may find at a next measurement that two competitors have since invested in it. Then an acceptable lag shifts into an urgent one.
The reason closing, compensating, or accepting is not a gamble lies in the evidence behind each score. A lag that emerges from customer quotes, lost deals, and direct competitive comparison weighs differently than a lag that is based only on an internal estimate. In a merger or acquisition that distinction is needed even more sharply, because two organizations are then suddenly placed side by side on the same dimensions, and the question is which lag of the acquired party is a real problem and which one only looks that way due to a different scoring framework; that is precisely what how do you compare your position after an acquisition addresses. Without that underlying source, every choice remains guesswork, even if the score itself seems clear.
First check whether the dimension on which the lag lies counts in the deals that matter in your market, and only then determine in the evidence matrix what is causing that lag: price, proposition, visibility, or something else. If the lag runs through price, the free loss-on-price check on the homepage of competitivebenchmark.net gives a first indication of where the leak is. Actually closing a gap is then implementation work in processes, people, and systems, and what that concretely costs and which part of it can be absorbed with AI is worked out in the work scan on ftetoai.com.