Eight Leaves is a Data Agency
Posted by Sridhar Mutyala at 01:28 AM · No Comments

Businesses have been using computers to collect and analyze data for decades. What’s changed? First, the scale: there’s more data, more sources of data, more features in the data, and more connections between data sets. Second, the speed: data moves faster and can be processed faster — decision-making must keep pace. Third, the stakes: business leaders must get increasingly complex, high-stakes decisions right; they need to correctly frame problems and evaluate alternatives; to do so, they need better information and better analysis, not more data.

Extracting meaning from data and communicating it effectively is a specialist’s game. It requires a unique mix of skills, talent, and judgement. The IT department warehouses data and creates reports. Business analysts drill down and uncover trends. This is good work, but it leads to better questions: What should I look at and why? What does it mean? What’s driving it? Can I predict when it’ll happen again?

I call Eight Leaves a data agency to sum up what we do and to suggest our role in your supplier ecosystem. An ad agency works on creating and delivering advertising. A data agency works on uncovering and interpreting meaningful patterns in large data sets. An ad agency works long-term to develop a client’s image and shape the perception of its target customers. A data agency works long-term to improve a client’s understanding of customers and its decision-making around strategic concerns. An ad agency is creative. A data agency is objective.

Advertising has the advantage of being in the open. It’s meant to be seen. To attract prospective clients, an ad agency can simply point to the good work it’s done over the years. We don’t have this advantage. Due to the proprietary nature of data (and the competitive edge that analytics provides), our good work stays locked inside our clients’ walls. To attract new clients in new industries, we’re forced to describe what we do in abstract rather than concrete terms. This puts us in a bind: we can’t show you what we do until we actually start doing it.

There are some nuggets from studies we’ve done with public data sets which I’ll begin to share in future posts. For now, I’ll briefly describe the services we provide to our long-term clients and leave it to you to decide whether you, in fact, need a data agency.

What Does a Data Agency Do?

We organize and clean data. Not very glamorous but necessary work. The data sets we analyze tend to be messy. Records are duplicated. Values are missing or entered incorrectly. The data contains outliers which are sometimes anomalous and sometimes just unusual. The data set is at times a distorted sample of the population under study. These potential problems affect the quality of subsequent analysis. Because insights drawn from contaminated data are of little practical value (even misleading), we put in considerable effort to keep client data as clean as possible.

We help clients understand what their data is telling them. During meetings with our clients, we’ll hear opinions fly back and forth on why a store over performs, why customers leave, or why business units don’t collaborate. Someone at some point will suggest “Let’s see what the data has to say.” It’s a favorite phrase for long-term clients. They no longer see data as a sort of eye-rolling chaos or formless commodity. They instead rely on it to help them understand what’s really driving the events and behaviors that affect their world. Data grounds their thinking and decisions in reality.

We predict what happens next. Not always, but often enough, the past predicts the future. A customer that bought two suits every year for the past ten years is likely to buy two suits this year. A customer that doesn’t return in a fixed window of time from her most recent visit is likely lost. Patterns in customer data sets lie hidden in a background of randomness. Data specialists, like Eight Leaves, attempt to discover these patterns and test whether they hold up over time and under varying conditions. We’re supported in the effort by an arsenal of algorithms and computational tools and techniques. We bring to the task a mix of critical thinking, imagination, and care — so that our predictive models help our clients choose the best course of action, in circumstances big and small.

We communicate our findings clearly. One of our first presentations to a prospective client didn’t go as we expected. We felt our analysis was impeccable and that our findings were game-changing. But the reception to our many detailed slides was muted. Those present paid polite attention, asked polite questions, and politely showed us the door. We didn’t fail in the substance of our work; we failed to communicate the substance effectively. Happily, we learned our lesson — then we learned more lessons from information design, advertising, and cognitive science. We now take as much pain in crafting the message as we do in piecing it together, so that clients can see what we see and why it matters.

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