HDG #015: Breaking the “so what?” cycle
Read time: 3 minutes
Greetings, Gurus! Today’s edition might ruffle a few feathers, but it’s high time we address one of my biggest pet peeves—the infamous “so what?” showdown.
Does this scenario sound familiar?
🔵 Business: "Dear analyst, could you kindly craft us a [report/dashboard/analysis]? We are attempting to understand x, y, and z."
🟡 Analyst: Puts their heart and soul into the request, adhering to the provided specifications.
Produces a comprehensive analysis, delving into numerous rabbit holes to anticipate potential questions.
Compiles it into an engaging presentation.
Presents fascinating findings, highlighting at least 3-5 intriguing aspects, and meticulously explores all of them during the presentation.
🔵 Business: Gives a blank stare, followed by, “This is great, but where’s the ‘so what?’”
🟡 Analyst: Stares back, feeling a bit lost because they've just spent an hour discussing the ‘so what’.
🔵 Business: “Ok, let’s meet again after you’ve added xyz.”
Lather, rinse, repeat…
Ad infinitum…
Everyone gets frustrated…
And this same request comes up a year later because nothing was ever done to address the problem due to a “lack of data”…
. . .
Stop the insanity!
For all my esteemed business folks out there, this one's for you. Please, I implore you, stop alluding to the "so what?" after analysts present you with data. I understand the instinct, I truly do. But here's the kicker: at the end of the day, you are the one responsible for understanding and possibly even identifying the "so what?”
And for all my analysts out there, this does not mean you can produce lackluster insights or absolve yourself of the responsibility to explore all the angles and communicate things in a way that your stakeholder will resonate with/understand/care about/and need in order to answer the “so what?”
But we can’t keep letting it be a nonstarter or impasse if we actually want change in healthcare.
The problem isn’t that the data didn’t answer the “so what.”
It’s that no one knew what to do with the information.
Data is a means to an end, and analysts are the data ninjas, adept at slicing through the noise to present you with valuable insights that help inform your decisions. But it's crucial to remember, while analysts can guide you, they cannot—and should not—do your job for you.
The paradigm shift I’m advocating for here revolves around the "so what?" It's a shared responsibility. Analysts play a significant role in revealing this, but the requester and business owner, i.e., you, bring something the analyst can never have—intimate knowledge of your domain, its context, and its nuances.
Under the current status quo, an unfair expectation is placed on analysts to not only present the data but also single-handedly provide all the answers. This shifts the onus of decision-making entirely onto analysts who, despite their data and even analytical expertise, lack the intricate business-specific context that you possess. Secondly, it creates a culture where data is viewed as an end in itself rather than a means to drive strategic decision-making. This false dichotomy between the role of the analyst and the business team cripples the potential for productive action.
Oftentimes: it results in business teams absolving themselves from the responsibility of data interpretation and subsequent action planning.
Sometimes: this inaction may be blamed on a perceived lack of data or insufficient analysis.
Other times: they may find themselves unable to comprehend/synthesize what is being presented into a tactical action plan.
Worst case: nothing ends up getting done about the initial problem.
So what is the Analyst’s role?
An analyst can assist in evaluating the situation, exploring options, assessing risks, quantifying different scenarios, presenting pros/cons, and even making calculated recommendations. However, interpreting and applying the "so what" ultimately falls on your shoulders.
Breaking this pattern requires a conscious shift in mindset. Analysts and business stakeholders must collaborate, with the latter stepping up to take their rightful role in the data interpretation process. Recognizing that the "so what" is both of yours to decipher and answer is crucial.
. . .
Actionable Idea of the Week:
Here's a radical idea on how we can start to break this paradigm: start a conversation!
For Business Stakeholders:
Invite your data analyst for a coffee chat or a virtual hangout, whatever works best in your work context. Use this opportunity to share more about your department’s goals, challenges, and strategies. Explain the nuances and intricacies of your domain. This knowledge transfer will empower your analyst to provide more context-aware insights.
Moreover, don’t shy away from diving into the data yourself. Familiarize yourself with the basics of data analysis - there are plenty of resources online. This understanding will enable you to interpret data better and ask more targeted questions, enhancing your collaboration with the analyst.
For Analysts:
Reach out to the business teams you're supporting. Ask for a better understanding of their work, their challenges, and what decisions they’re grappling with. Try to understand the context in which your data will be used.
It's equally important to develop your communication skills. Tailor your data presentations to the audience’s understanding. Use plain language, avoid jargon, and focus on making your insights clear, concise, and actionable.
Try these steps this week, and watch how this simple change in approach can help break down barriers and elevate your data-driven decision-making process. Collaborating and ideating together, in my career, has been when the best ideas have come about.
Remember, the aim is to foster a culture of shared responsibility for the 'so what?'.
The more you understand each other’s work and challenges, the more effective your outcomes will be. And I think we can agree that is a shared goal that we all want—It is why we work in healthcare, after all!
. . .
Figuring out the "so what?" is a shared responsibility.
As for the "now what?"
That's a fascinating topic tied to program design, but let's save that discussion for another day 😃
See you next week!
-Stefany
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