How do you turn big data into useful data?
First and foremost, it takes inquisitive people that see the patterns that lie beneath the surface.
As founders of Sweetspot and MaassMedia (respectively), Sergio Maldonado and Aaron Maass both believe that a strong data analytics strategy means not just solving problems and finding answers, but asking the right questions. After working in marketing analytics at Comcast and DuPont, Aaron founded MaassMedia with the mission to train analytics consultants to move beyond crunching numbers and building dashboards. Without focusing on creating a strong foundation, earning trust, and building stronger relationships, analytics insights and growth plans often fall flat.
Similarly, Sergio, who previously founded Divisadero, an analytics consultancy in Europe and South America, also saw an underlying issue in the way that analysts were typically collecting and presenting data. He noticed that incumbent reporting practices across large enterprises often lacked inbuilt systems for monitoring progress towards goals and evaluating the effectiveness of decision making. Moreover, it was difficult to gather and share data from multiple sources across enterprises, making it near impossible to make decisions in a timely manner. With these issues in mind, Sergio founded Sweetspot – a digital dashboard solution that would make it easier for enterprises to act on insights.
As business partners, the work that Sweetspot and MaassMedia do together is founded on our shared belief that it’s important to communicate with clients about their goals, and to help them make an action plan for growth. In the following interview, Aaron and Sergio discuss how training, making a plan for digital transformation, and company values provide value for enterprise clients.
1. What are the biggest challenges that early career digital analysts have when it comes to presenting and drawing insights from data? In your experience, what is the best way to guide them?
Aaron: Early in one’s analytics career, it can be hard to know what the right questions are to ask about data. It’s important to be able to come up with many reasons why an anomaly occurred. But without having the exposure to multiple case studies, early career analysts might not have enough experience to think of all of the answers there might be for a spike or dip in the numbers. I often look for people who are well-rounded because they can apply learnings from a variety of different subject matters and disciplines. But someone who has studied psychology, anthropology, history, or creative writing in addition to math, economics, or statistics might be able to think more critically and less literally. Human behavior is often irrational. It might be contrary to what makes sense.
One of the exercises I use to guide early career analysts is as follows. I take a simple chart and ask them to simply brainstorm every possible reason why a change might have happened. Then we take a break for a little bit. When I meet with them again, I ask them to come up with five more. It’s just a good exercise. It helps you with critical thinking and it helps you to be thorough about your analysis.
Another one of the tricks to presenting data effectively is being compelling. You need to be able to provide context, and to tell a good story. If you just jump to a conclusion without telling a story, you don’t come off as convincing as you would have if you laid the groundwork first. But context also comes from experience.
Sergio: The biggest challenges are usually more associated with communication skills and subject matter expertise than an ability to create visualizations or find insights. After all, insights are only useful when they have a meaningful impact, and this depends on both understanding the business reality behind the numbers, and being able to communicate it in a language stakeholders can understand.
I believe data analysts need to come with a strong statistical background (something that can be obtained in isolation or in more generic academic environments), so that we can focus on guiding them through the specifics of brand building, marketing basics, online retail, or the particular challenges of a given industry (travel, hospitality, CPG… etc.).
2. Which area of digital transformation do companies most struggle with and what would be your advice to them?
Aaron: Often, it takes organizations a while to see the full value of their digital transformation initiatives. A strong digital transformation plan includes a plan for ongoing training, departmental and individual accountability, and cultural change. Purchasing the technology and holding a few classes is not enough to build a database decision-making culture. Analytics adoption takes much more concerted and consistent effort, and requires cooperation from executives and employees.
My advice to leaders is that the “bottom-up” part of analytics adoption is as important as the “top-down” part. After a training program, creating communities of practice which include individuals from different divisions (IT, marketing, sales, operations, finance, etc.) will allow people to ask questions and share knowledge. Participants have the chance to recognize that the same challenges come up in multiple departments, and to strategize around process improvements. Having a facilitator there from the executive team can help identify any stagnancy in growth, and to address any slow-downs or repeated issues efficiently.
Communities of practice also reinforce the idea that transformation is a company wide initiative, and that the new skill sets people acquire are part of a shared mission.
Sergio: I would say that people commonly struggle with redefining any methodologies or processes that they consider basic pillars of their work. This is inevitable in scenarios in which entire offerings are being atomized or unbundled, and the very understanding of that kind of disruption is a huge challenge. This is due to that fact that competition now stems from entirely new corners, and you are forced to compete outside of the market you have grown accustomed to fighting in, which in turn brings new and unforeseen threats.
I do advise customers in banking or insurance sectors (in which regulation shields them from a real tsunami) to be extremely cruel with their real value proposition vis-á-vis their customers, breaking down their offering into the many little services at which anyone out there could beat them. It really is a mindset problem.
3. What is your most important company value, and where do you see this helping you to help grow and maintain strong client relationships?
Aaron: Our most import company value is asking ourselves constantly, “are we delivering value?” Just because we’ve done what we’ve been asked to do doesn’t mean that we have delivered as much as we should. With everything I do, I try and ask myself, “Have I done this in the best way that I possibly could? Have I added value here?”
If I have answered a question that anyone else could answer, then I haven’t really done much. But if I have gone above and beyond and anticipated what the next questions might be, then I’m delivering value. It makes clients feel good about the work that they’re paying for. When we send a report and provide our insights, the goal is not to get a “thank you,” but a “WOW!”.
Sergio: Vision. I think we put plenty of time into understanding what’s coming up next. That in turn is shown in our products and work, with customers and team members benefiting and hopefully growing faster, enjoying the wider perspective and having a sense of purpose.
Attending eMetrics Summit in NYC? On October 31, don’t miss happy hour drinks and snacks on MaassMedia and Sweetspot at the Houndstooth Pub in Hell’s Kitchen. Register here.