Insight Creator

I often use the analogy of a restaurant when talking about the three elements that constitute Insight as a discipline. In a restaurant you need:

• Excellent quality raw ingredients
• Someone to combine the ingredients into a coherent dish
• Front of house managers to engage with the stakeholders

My feeling is that the Insight profession has recently focused on the first and last of these three: on sourcing raw data, and managing stakeholders; but the middle role, that of ‘chef’ or ‘content creator’ is being under-represented.

One simple illustration of this, is that we don’t even have a job title for that middle role:

• The first role, sourcing raw ingredients is done by Data Scientists and Researchers
• Stakeholder management is done by Insight Managers (and here, I use the words manager or administrator as a descriptor of what they do, not their level of seniority)
• But what do you call the one in the middle – the person who creates the narratives?

Historically much of the content- or narrative-creative role has been delivered by external researchers; in particular by ‘grown up’ researchers.

External research agencies all provide raw data, in either quantitative or qualitative form; but the good ones, with grown-up researchers. also provide insight. Where ‘insight’ means the thing that happens after all the data is in place; insight is not the data, but the story that explains the data. Its the equivalent of a theory in science.

It is this interpretive role is being bypassed or even attacked by end-clients who think they want direct access to ‘the truth’. The role of researcher is being reduced to well-organised data provision.

You also see this in job descriptions for client-side insight roles, which fall into one of two roles, not three: either Data Scientists who “must have excellent Python and SQL skills”; or Insight Managers (at any level) who “must be able to engage with stakeholders and present to senior teams”. Neither make anything more than a passing reference to content creation, and only then as if it was a performing art.

To illustrate the importance of all three legs of the stool (data, content creation, and insight management), and at the risk of stretching the analogy, let me share with you three failing restaurant models.

Mongolian Barbeque

In the 90s there was a slew of restaurants that seemed to give customers the ultimate choice: the customer selected the raw ingredients, the method of cooking, and any sauces they’d like; and then the ‘chefs’ then prepared it to their exact specification. This model was sometimes presented as ‘Mongolian BBQ’, where you picked a bowl full of raw meat and vegetables from a sort of salad bar, before handing them to a wok-wielding cook; another version was the Borough Market-based fish! where you could cook any fish, any way, with any sauce.

As a customer, you quickly discovered that customers make rubbish chefs – we don’t really know what flavours go together, or the best way to cook tilapia.  The concepts reduced the actual chefs to cooks, who had to try and make sense of the random collection of ingredients and requests, as if they were contestants on Ready Steady Cook.

This Customer-DIY model, however seems to be the current model for Insight: we seem content to let clients choose their own stories from a smorgasbord of random data. The Insight Department is reduced to sourcing the data, laying it out on a smorga-dash-baord, and enabling the stakeholders to help themselves. The content creators are reduced to facilitators.

This has a number of impacts:

• In the absence of a clear brief from a Chef, the raw-data providers conduct vast, unfocussed fishing trips, and supply the restaurant with whatever random shit was in the sea today. Insight Departments spend too much time piping in more and more data, and not enough time thinking about whether it is the right data.
• A second impact is that the customer-stakeholders are dragged into process that they don’t understand or care about: stakeholders don’t know what a good recruitment questionnaire looks like, or what a good topic guide looks like, and sharing both just results in confusion and frustration. Like any well-managed team, a research team should have agreed objectives at the outset, but they should also have the freedom to deliver to those objectives without micromanagement. Let them do their job.
• The lack of an interpretive-intermediary means that stakeholders are deluged with raw data, and then fall into one of two camps: they either give up trying to understand; or they cherry pick data to support their already-held prejudices
• Stakeholders will often get involved in sourcing the raw ingredients: coming to (just) one focus group, or listening in on (just) on interview or transcript. One the basis of this one data point, they decide that they can run a restaurant.

The problem with the Mongolian BBQ model is that it has no chef at its core: so the ingredients are random, none of the dishes make sense and the customers are exhausted and frustrated by trying to micromanage a process that they are not expert in, and has poor quality outcomes.

There needs to be a vision at the centre, that drives both data-acquisition and stakeholder management. But we don’t even had a name for that role. So lets borrow one from Advertising. Welcome: the Insight Planner. Someone (to mix my metaphors) who brings all the pieces of the jigsaw together, spots which pieces are missing, but also tells stakeholders what picture they are looking at.

Tyrant Chef

There is of course, the potential for this all-empowered Chef to turn into a tyrant. These chefs are the legends of Mayfair restaurants. When the customer asks for the dish in a particular way, he is chased into Berkley Square by a cleaver-weilding red-faced man in a tall hat.

The advantage of the tyrant chef model can be spectacular clarity: under a tyrant chef, the raw-data-providers are very tightly briefed to deliver exactly what is needed (no more random fishing trips). The menu is tight, consistent and beautifully balanced. The Front of House Managers know exactly how to sell-in each dish, how to cope with questions.

The downside is that there is no-one to push back against the tyrant, which means that whilst when it is good it is great, when its bad it is terrible: when any element is slightly off the system has no means of correcting itself. If the core vision is wrong, out of kilter with the market, then there must be ways of fine tuning the vision.

The sweet-spot is to have a three way dynamic relationship between the data providers, the chef and the front of house

• The Insight Chef needs to tightly brief the raw-data-providers: given the insight that we already have in the larder, what do we need to fill the gaps
• The raw data providers need to occasionally surprise the Chef with what’s in season: to report-back from the front line of the new things that are coming

The Insight chef needs to tightly brief the Front of House

Front of House Insight are managers need to talk to the Stakeholder-Customers and understand their needs. But just as the Insight Department interprets what customers say, they also have to translate what clients say. To translate from what they say they want, to what they actually need.

What if the stakeholder-customers don’t like it, to which there are two answers: if customers need it but think they won’t like it then reach for the cleaver; but if you’re serving up insights that don’t make business sense, then you’re going to be out of that business pretty quickly.

People think there are only two alternatives: giving customers everything they ask for, or not listening to customers. There is a third way: listen to what customers say they want; think about what they need; deliver that.