Empathy: why insights professionals are still needed in the machine age

Empathy: why insights professionals are still needed in the machine age


Reading time: 5 mins

There was a time, especially in the
United States, when researchers were supposed to be the neutral purveyors of
the truth – unbiased, impartial and uninvolved in the business. You collected
the data, passed it over to the appropriate decision makers and went on to the
next project. What the decision makers did with your data was not something you
involved yourself in.

I discovered this the hard way in 1991. Newly arrived in the US from Europe, I worked on a project related to a failing product for a large Fortune 500 company that shall remain anonymous. The time came to debrief the brand team. The Director of MR and I dutifully traveled to their offices and we spent two hours discussing the results. I thought the meeting went swimmingly. The brand team and I had a robust and highly productive conversation, examining various hypotheses and strategies for moving forward. As we got back into his car, the Director of MR turned to me and said, “don’t you ever do that again. Your job is to present the results that are significant at the 95% level and nothing else”.

Thinking
like business people

If research had remained like that,
it is very likely that it would now be entirely mechanised, with dashboards
taking the place of any human involvement in the dissemination of results.
Indeed, in certain spheres (for example, brand and customer satisfaction
trackers) that has actually been the case. But, for many companies, this is not
how research is any more. In a recent study, conducted by Boston Consulting
Group, of CEOs of major corporations, the majority of those interviewed said
that what they wanted most from their Consumer Insights functions was business
insights that could drive decision-making. They wanted their insights
professionals to think like business people, not like researchers.

So, in the space of a couple of
decades, we have gone from purveyors of the unvarnished truth (data) to the
unveiling of business insights. But insights are not insights unless they lead
to action. In the absence of action, they are merely nice to know. In other
words, the onus is now on the researcher or data analyst to ensure that the
insights they uncover have actual impact. However, for many that it is
easier said than done. How does an insights professional in a major organisation
actually ensure that the insights that he or she delivers really do have
impact?

From data to insights to impact

This is a question that leaders of
corporate insights functions have been grappling with more and more recently.
In essence, it boils down to “what talent mix and skills sets do I need to
maximise impact?”. Invariably, consulting skills come front and center, as do
communication skills and story-telling. The researcher must also be a
consultant or, if that is not feasible, the insights function talent mix must
include consultants. This means establishing credibility not only as a
researcher or analyst but also as a business person who, in possession of
evidence, is able to engage with senior management as an equal and discuss with
them the business implications of a particular set of insights.

That in turn means that not only must
the researcher-consultant really know the business well, but they also have to
have the ability to frame the questions being asked of the data (whether
primary research or secondary analytics) in full knowledge and understanding of
the business issue at hand. This today is still one of the Achilles Heels of
research as, all too often, the stakeholders in any given project might not
know or be able to articulate the business issue themselves. The
researcher-consultant needs therefore also to be a forensic detective to get to
the bottom of the business issue and to gain full understanding of its
implications.

Again using forensic skills, our
intrepid researcher-consultant will then need to synthesise (as opposed to
merely analyse) the data to uncover the insights held within the data. From
there, his or her role morphs into great communicator and influencer. (This is
where traditional researchers spin in their graves). For, now knowing the
insights in her possession and their implications for the business as a whole,
the researcher-consultant needs to communicate both to decision-makers with a
view to delivering impact.

For many researchers brought up in
the traditional mold, this too presents its challenges. Used to delivering all
the data (often in 100-page, densely packed Powerpoint slides), the
communicator-influencer-consultant-researcher now needs to impart not only the
key insights but their implications in a crisp, 10-slide presentation. For, as
a wise CMO said nearly a decade ago, the presentation should last ten minutes,
the conversation should go on for hours.

Throughout this entire process,
however, there is one attribute or skill that our hero needs above all; an
attribute so key that, without it, his or her endeavors will invariably fail.
That attribute is empathy. Empathy is what ultimately converts data into
insights; and empathy is what allows insights to have impact.

Empathy is what ultimately converts data into insights; and empathy is what allows insights to have impact.

Empathy: the secret sauce to gaining
impact

Without empathy, the researcher will
have a hard time really understanding the underlying business issue. Such
understanding comes not only from comprehending the numbers behind an issue,
but also the implications that the results of any given outcome might have for
decision makers and stakeholders personally. Would a particular outcome have
consequences for the manager requesting the research? Would it place key
stakeholders, such as the CMO, in an awkward position? What’s riding on the
decisions being taken as a result of the insights being delivered? The
researcher needs to understand all of this, as it will influence how the
implications of the research should be presented.

Similarly, it takes empathy and an
understanding of how human beings function to be able to join the dots in
synthesis. Are we dealing with System 1 or System 2 thinking? What tangential
factors are consumers involved with that guide their decision-making? (In my
example from 1991 above, the single most important tangential factor was, in
fact, corruption, which posed enormous ethical challenges for the brand team I
was advising). What factors that we can’t directly measure are leading to
choices that might seem irrational? In markets such as pharmaceuticals, such
factors can play an enormous role in choices such as compliance with
prescription advice from doctors. Knowledge of, and empathy for, such factors
is critical in determining whether our insights are true or false.

Finally, without empathy, our
attempts at ensuring impact will be severely constrained. If, during the
presentation, we don’t know why the person at the end of the table with his
arms crossed and his defenses up is behaving as he is – and if we don’t have
empathy for his reasons – we risk losing him when it comes to making decisions.
If we don’t have empathy for the fact that the CEO only has ten minutes to
listen and understand, we risk losing her. And, crucially, if we can’t engender
empathy for the consumer (or research participant) in our audience, then we
fail to bring to the organisation the reality of the market and of customers’
lives, upon which the insights engendered by all research are based.

“I empathise with you”, said no
machine ever.

No dashboard or interactive piece of software
can yet bring the empathy that is needed for real insights to turn into real
impact. No algorithm can converse for hours upon the implications of an insight.
No machine can understand what outcomes mean for real people. Until the time
comes when they can (God forbid), we are going to need flesh and blood insights
professionals.

The key to all this, however, is that
those same professionals and the functions in which they work need to
understand and embrace the importance of empathy and to hone the skills that it
informs. If they don’t, the machines are waiting.



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