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Some firms do. Some don't. beaton wonders why.

Some firms do. Some don't. In which category did this managing principal's firm fall? We asked ourselves this question this week when we received an email from the managing principal of a prominent firm: "We've decided to enter the Client Choice Awards for the first time, and we're hoping to at least be a finalist on the big night....". She was, of course, referring to the Client Choice Awards dinner on 7 March 2017 in Sydney. Clearly, this firm believes in long-range planning, but I asked myself whether there was a deeper intent behind the aspiration? Every year at this time preparation for the Client Choice Awards generates a great deal of interest amongst the larger professional service f

Why firms with the leading industry reputations win

One of the big trends we have seen across the professions over recent years has been firms changing their ‘go to market strategy’ from an internal product focus (expertise/ service line/ practice group) to a client-centric view of the world (industry sector/ market). And the benefit is clear. As the 2016 beatonbenchmarks research shows, firms with the leading industry reputations win more work because this is a key driver of choice across law, accounting, engineering and management consulting professions. Why industry experience and reputation win work The diagram summarises the stages through which clients move in making decisions about their professional services provider. 1. Awareness 2.

Is yours big enough?

This blog was prompted by a question and comment from a client, who asked “Given we provided a database of 6,320 contacts, and you received completed questionnaires from 180 respondents rating our firm, is that enough? The sample seems small compared to the size of the database.” If I rephrase our client’s words, what they are asking are two questions: [1] How do we judge what an adequate sample size is? and [2] what role the size of the population we are sampling from has in deciding whether our sample is adequate or not? Confidence intervals We are interested in sample size because it indicates how confident we should be in our survey estimate. When we are talking about confidence in a sta

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