Late last year, I attended a future of marketing-styled conference. There was a specific track on data and analytics, so I got the ok to attend. The venue was pretty typical. It was held in a huge conference hall, with break out rooms located in a subterranean galley area lit by very dim, yet very ornate chandeliers. The types of room, where a natural disaster could occur wiping out the entire city and you would have no idea.
Towards the end of one session called the Future of Account-Based-Marketing, we were asked to descend to the bowels of the hotel room and join one of the break out sessions. There were three or four separate sessions focusing on: content, targeting, and of course, data. I joined the data one.
We piled into the room. I became instantly saddened to see that the chairs were arranged in a semi-circle to invite greater participation. There was not one chair by the exit to allow for stealthy pop-outs. The moderator, a youngish guy with nerdy, black-rimmed glasses reviewed the various themes this working group was supposed to solve for. Hands remained firmly in everyone’s lap for most of the themes. But hands shot up to discuss the data foundation for successful ABM. It was a good, in-depth conversation with lots of relevant insights, which I won’t be bringing up here (yet). Namely, because I’d rather talk about the insights about the business analysts that I observed.
Our working group was pretty decently sized. There were about 45 of us, more men than women but not by a significant margin. As the discussion progress from technical aspect to business question, the group seemed to self-select into three camps: a) the data idealist b) the reporters c) the predictors.
The data idealist
I was torn between calling these people quibblers instead of idealist because this group won’t be satisfied until every pulse, vibration from any digital or human interaction is identified, culled, aggregated, threaded and rolled into an attractive bar chart including multiple dimensions. These are not my people. I appreciated their vision but also found it grotesque and although, it may be the way the world is leaning that does not mean I should actively encourage it.
The archetype for this peculiar group was one very earnest, very passionate woman. She worked for the one of the big consulting houses and spoke with quite a bit of authority and experience—the kind of person I typically tend to avoid because they always seem to want to tell me how to do things.
As she was talking, she leaned back in her chair and described how every morning, she reviewed each of her dashboards for any inconsistencies or unexpected changes. That most of her time and energy was spent working with their IT team to understand why certain data was not rendering, the timing of data maintenance, data gaps, etc. She held forth to several people, who nodded their head in agreement, about lack of data, or wrong data, or bad goaling.
Not once did she mention how she was using data to help the business. For her, at least, the goal of data was the data itself.
This type of person has a purpose and it’s to report out on the performance of the organization. They want to provide their teams with the most accurate, most timely insights to help the business understand where they are, how they got here and the progress they are making. They have a solid understanding of their team’s KPIs, and the metrics they need to tell that story. Maybe not the most creative bunch but solid and extremely smart.
One guy talked about how he’s invited to any meeting that is related to big marketing efforts to gather requirements and then ultimately to report out on progress. He spoke confidently about working with his team and as a true partner, helping to influence what was tracked. I smiled to see that he was already wearing the requisite conference hoodie and wondered if he relied on conferences for his traveling wardrobe.
He did echo some of the sentiments of the idealist, but it was in the context of how and what he was reporting out on. Less about data flaws and more about strategic urgency to data issues. It was a slightly yet critically different perspective.
These are the visionaries. The take the characteristics of both the idealist and reporter add a touch of fortune-telling to conceive of a world, where we begin to anticipate the needs of our clients/patients/customers/etc. They don’t appear to get mired in the minutia of the data—this is not to say that they don’t have a deep understanding of the data foundation but I got the sense that they choseto trust the expertise of their data architects.
As this one guy said, “once we have the foundation, we know what metrics to watch for to monitor the health of the company, we’re now free to explore and innovate with data. It’s good to be able to know what’s going on now but it’s better to be able to forecast and potentially influence tomorrow."
He was one of these people who is simply fun to listen to. Someone who has a gift for translating pretty complex concepts and restating them in a way that everyone can grasp. These are not my people either, but I aspire to be.
He worked for a start-up and as a data person actually was actually involved with the executive team so that he could plan his data strategy. Because data architects and data architecture costs money and visualizing KPIs are not free either so data was just part of the way they operated. When I asked him later how large his start-up was, he did concede there were only 10 people. But I still was impressed that any company, especially a start-up, would include their business analyst in planning discussions.
I’m not that type
I suspect many of us in this field rangewithin this spectrum of types and I believe must. Sometimes the situation dictates the need: integrity of the data vs. standardization on KPIs vs. the next waterfall model. The one overriding goal that I think is critical is keeping the business in mind when you’re working with data. Ultimately, make sure that what you areanalyzing helps the business meets its goals.