What Makes A Good Analyst?

One current features of the Web analytics market is not somuch the advances in the technologies, but the desperate lack of talent (on both sides of the Atlantic) to drive value from implementing these technologies. Where are all the analysts organization need to interpret the data and advise on potential courses of action?

A recent Forrester report highlights what many of us already know; implementations of analytical technologies are likely to fail if you don’t also invest in resources to maintain and leverage the new capabilities. It’s not just about hard- and software; it’s also about “peopleware.” People are the third and vital ingredient in the mix.

Trouble is, online marketing analysis is a relatively young industry and there aren’t yet enough people out there with the relevant experience. So organisations are faced with the choice of either offering high packages to lure people away from other organizations, or they have to find candidates with potential, then train and develop them in-house (always carrying the risk they’ll then be poached by somebody else).

So with the rush on to find good people, what makes a good analyst?

I wrote my first “Web analyst” job description about 6 years ago. In many ways it wasn’t that different from the job descriptions I wrote for marketing analysts 8 or 10 years before that. It was just that some of the tools were different. Here are some of the attributes I think make a good potential analyst, and what I look for in a selection process.

Presence

First and foremost, a good analyst must be able to put a case across and get action as a result. They need to be taken seriously by the rest of the organization. This requires good communications skills and the ability to influence discussions and outcomes. Someone may be technically very good, but that’s wasted if they can’t get a message across.

When recruiting analysts in the past, a major part of the selection process was getting the candidate to deliver a data based presentation to a group of prospective colleagues and internal customers. If they couldn’t get their point across clearly and concisely, they usually didn’t make it through to the next stage.

Commercial Awareness

In my mind, a good analyst must be as commercially aware as the people they deal with in business. He or she must understand the business implications of their analysis and recommendations. They have to be close to the business and also have a firm grasp of the context in which the business operates. There’s a difference between “insight” and “actionable insight.”

Data Dexterity

Obviously, an analyst must be numerate and feel comfortable with numbers. I also think a good analysts needs to have “data dexterity.” By this I mean the analyst has to feel comfortable working with large volumes of data from disparate data sources, and to be able to spot relevant patterns and trends. This is different to being numerate. Producing an analysis is also different from producing a report.

Another key skill is the ability to spot when data are blatantly wrong and “just doen’t look right.” To often, I’ve seen analysts come a cropper (define) when they make recommendations based on what was obviously dirty data.

Attention to Detail

A good analyst must be able to both think strategically, but also at low levels of detail. The devil is in the details, and often there are problems or issues to be addressed that require close attention to the detail. Above all, the analysts must be suspicious and question things that don’t look right. A simple mistake can prove very costly down the line.

Having said all this, a good analyst should be technically competent but that, in a way, is a hygiene factor. The above list, are the qualities that enable you to separate the winners from the also-rans. It’s an optimistic set of requirements, but someone with the right temperament and attitude can be trained in some of these areas. Look for the fertile ground.

The next generation of Web analysts may be not necessarily be where you expect them to be. They may be in related or even quite separate functions or industries. But if they have the right qualities and attributes, then they’re worth tracking down.

Happy hunting!

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