A few years ago I was running a team of analysts who provided business intelligence in the form of data, information etc. for a variety of business disciplines across a major corporation, we will go one to discuss what data is later in the article. I was trying to establish how well each of the analysts were performing based on the level of interaction and insights they were providing and the relative use of this to their clients. Some seemed to be doing well as determined by their clients, whilst others appeared to be struggling and a couple of them seemed to have gone “native” within the departments they were supporting actually making decisions for them. What I needed to do was establish the levels of relative effectiveness and determine where the “sweet spot” was across a range of activities and the levels of trust held by the clients.
What exactly is Data?
Before we go on it may be prudent to remind ourselves of the data hierarchy defined by Nonaka 1994.
Nonaka provided a hierarchy of knowledge ranging from Data to Wisdom, see definitions below. This maps well across the 5 levels of trusted advisor. With the Source providing Data, the trusted source providing Information, the advisor providing Knowledge and the trusted advisor providing Wisdom.
Data is described as facts and statistics collected together for reference or analysis.
Information is Data that has been collated into an order
Knowledge is information tested through argument and with context and insights
Wisdom is combining Knowledge with experience and good judgement to provide deeper meaning and reason.
The Advisor scale of competence and effectiveness.
The scale of competence and effectiveness for the trusted advisor is as follows.
Source: Someone who provides data without much added value, has no real insight or context as to the client’s needs causing the client to verify the value and source of the data provided.
Trusted Source: Someone who provides verified data again without much added insight or context with the client having to provide that context.
Advisor: Someone who can add value to the data provided but who hasn’t built a sufficient relationship or trust with the client to avoid further checking by their client.
Trusted Advisor: Someone who understands the client and their requirements and has built a strong relationship and trust over a period of time.
Decision Maker: Someone who has embedded themselves with the client to such an extent that they appear to be part of the decision making team within that organisation.
None of these are a particularly bad place to be as it is dependent upon the level of time and experience of the individual analyst and the relationship they held with their client. However over time we would be expecting to see an improvement as the relationship build with the client. A number of you will have noticed that there are 4 levels from Data to Wisdom and 5 levels from Source to Decision Maker. The reason for this is that we believe that decision making is best left to the business owners not the Trusted Advisor, they are there to use their wisdom to advise their client.
As a result of this competence scale we found it easier to assess the amount of development each of the analysts required and where to focus their education and training. Along with the clients we also had a bench mark to work on regarding assessment and the level of maturity gained.