It took me a decade to realize what old clients truly wanted when, years after I had helped them with the software requirements for one of their projects, they’d contact me and ask if I could help them again with a challenging project. “I’ve stopped doing this kind of work a long time ago!”, I’d think. “How come these people don’t have some other business analyst at the top of their contact list that they could be calling to help them now?”
Had I asked, I don’t think these folks would be able to articulate why they thought I’d be a better choice than another BA they had on their team more recently. The few times someone volunteered a reason, it would be, “we like your eye for detail”. But I knew there had to be more than that, as I can’t be the only detail-oriented analyst they had worked with over the years.
It was a recent conversation with a senior professional who sought my help on an application of machine learning models that finally illuminated the answer for me. This senior professional is friends with one of the most respected researchers in the type of machine learning approach he wanted advice on. He told me he had initially thought of going to this friend for help, but then realized I’d be a better source of advice. I asked why, and he said, “I guarantee that [researcher’s name] would immediately jump to a discussion of algorithms and evaluation methods, but I realized that you would be starting from a much broader perspective, one that might help me confirm or dispel the assumption that a machine learning model is the right choice for my problem”.
This exchange made a light bulb go off in my head. The reason why top performing business analysts tend to be so effective in complex projects, even when their domain knowledge is limited, is because of their ability to see things from a higher angle and with more nuanced colors.
“I don’t get it!”, a startup founder or VP of Product would tell me when asking for help to figure out why a solution was underperforming. “Our customers love the demo of our [new feature/dashboard/etc.], but when we look at [conversion rates/usage statistics/etc.], they are pitiful.”
“I don’t get you not getting it!”, I’d think. After a short conversation with stakeholders, I’d know exactly why the solution wasn’t working for its intended audience. The answers may seem obvious as you read them here, but in reality, I’ve been hired as a highly paid consultant more times that I care to remember to provide these obvious answers to a puzzled executive:
- “You’re not converting trials into contracts because you’re only seeking feedback from end-users who are happy with what you offer: information on how much the company spent on cloud services as a whole. But you’re not going after the buyer’s input. Buyers want to be able to charge back individual departments for their cloud spend, and your report doesn’t allow them to see the cost split by department or business unit. You’re not solving the buyer’s problem.”
- “You’re not getting traction with the new dashboard because it requires Internet access to be displayed, and at the time users most need it, they are sitting in front of a manager at a retail store with no guarantee of good WiFi connection. Users are afraid of looking like idiots when they attempt to open a chart and it doesn’t load, so they don’t even try”.
The more I think about it, the more I’m convinced that the best BAs develop “bird’s eye” abilities beyond the traditional definition from the dictionary. Because birds not only can see things from a privileged angle when in flight, but they are also much better than humans at detecting differences between two similar colors. As a result, scenes may appear more varied to them.
And that’s what makes top performing BAs stand out: like birds, they see the world differently than most people, using a broader and more nuanced perspective of the problems, opportunities, and solutions they’re working on.
You may be thinking, “This all makes sense, but it’s easier said than done: how do I develop this ability to see things using a wider angle and a more nuanced perspective?”
I’m not going to lie and say it’s easy. However, like with most things we get better at over time, this is achievable with deliberate practice. Here are some examples of how you can start developing your “bird’s eye” abilities:
- When someone assigns you a new project (“please work with the Customer Support Team to identify the issues they are having with the CST application and document the requirements for the necessary enhancements”), don’t immediately jump to work interviewing customer support agents and writing down individual requirements. Start by asking broader questions:
- “What made this project a top priority now? Has something changed recently that made it more painful for agents to use this tool?”
- “If we didn’t do anything to solve this problem, what would be the consequences for the company and the team?”
- Once you get down to the detailed requirements, make sure to explore the problem in all its nuances before settling on a specific solution. Ask questions that broaden the solution space:
- Example of question you can ask your stakeholders: “I can see how adding the customer details as a widget to this page would make it easier for you to do your job. But let’s assume for a moment that it is impossible to add a new widget here. What else could we do to take away your current pain?”
- Example of question to ask yourself: “Imagine that, six months from now, the alternative you’re currently considering will actually prove to be a terrible decision. Where could you go looking for proof of that right now?
The reason these kinds of questions are effective is because they help us fight a common human trait: confirmation bias, our tendency to seek out information that supports what we want to be true, rather than go hunting for disconfirming data. Questions like these compel you to look for contradictory information, which automatically broadens your perspective and makes your analysis more nuanced.
Even the most talented BAs can get trapped into the same points of salience, the same causal relationships. Due to confirmation bias, they may end up producing the same kind of resolution every time, even when the context demands something different. The next time you’re joining a new project, make a point to “be the bird” on the team. You may find yourself coming up with new ideas that minimize the amount of work required to achieve the desired outcomes, creating innovation opportunities for your organization, and becoming the business analyst that former managers or clients will call years from now when they have a high-stakes project to staff.
Author: Adriana Beal, Data Scientist, Carnegie Technologies
Since 2004, Adriana Beal has been helping Fortune 100 companies, innovation companies, and startups in the U.S. gain business insight from their data, make better decisions, and build better software that solves the right problem. In 2016 she decided to follow her passion for quantitative analysis and got a certificate in Big Data and Data Analytics from UT. In her current role as Data Scientist with Carnegie Technologies, Adriana works with data from IoT sensors and mobile devices in support of the company’s mission to empower businesses and people to connect with greater reach, ease, and trust. She has two IT strategy books published in her native country, Brazil, and work internationally published by IEEE and IGI Global. Her latest publication is the guide How to Get the Tech Job You Want for professionals interested in shifting careers in tech.