Let us start by defining an insight as the discovery of relevant information, within any data set, that could not have been identified at a glance without technology and an analytical eye. An insight is always used to improve decisions with an out-of-the-box way of thinking.
In companies today, the most significant changes will come from the moment attention turns to generating insights.
That statement may be something new in the paradigms of how companies are run and how they relate to their customers, but it will definitely be what makes their evolution possible, and their adaptation to a new way of doing business.
But how is this done? How do I discover and properly interpret insights? Who does it?
Whatever the size of the organisation or the industry, the question above will be resolved by acting to close the gaps in data, technology and the skills of the people who study where the company is going: the analysts.
Without the right set-up and the right skills, insights can come to nothing — which is not ideal for companies that intend to innovate and succeed.
Analysts will have to strengthen their skills in analysing large data patterns in order to provide more accurate information about their area of analysis. They will also need to get up to speed on artificial intelligence and machine learning; in other words, they will have to commit to continuously developing their data-analysis skills.
The difference between a good data analyst and a bad one is that the good one knows which problem they are solving. A good analyst wants to drive change; a bad analyst will simply throw data at a problem. We meet a great many people who say they can structure data, but what matters is knowing how to use it.
Making insight generation easier, as we have said, is only relevant if those valuable ideas can be applied inside the company. There is no ROI in insights if nothing is done with them.
The biggest obstacle companies face has nothing to do with data, technology or analytical methods. It has far more to do with the internal capacity to change strategies, investments and behaviour on the basis of the insights that work generates.
So the keys to success in generating new business will rest on a human team of good analysts and on understanding how to use data.
Some tips for finding the right analyst:
Pay attention to job titles. A social media analyst, for example, might be called anything from a social researcher to a digital ethnographer. 'Analyst' can mean many different things, and the word 'social' can imply just as many — from social networks to social work. Use the job description to clarify the scope of the role.
Qualitative and quantitative skills: social data requires a combination of qualitative and quantitative analysis, so the analyst you hire needs to be fairly ambidextrous.
Experience: do not discourage applicants who may come from different fields, because that can help you build a team that is very rich in backgrounds and disciplines.
Skills and attributes to look for:
An appetite for changing things — someone with experience in change management could be useful.
Curiosity — do you have examples of creative or novel research that candidate has done outside work?
The ability to communicate insights to different audiences, both digitally and in person, so those findings are acted on in the best way.
The ability to manage relationships with different teams.
