The Pattern Recognition Mindset and...

...and how business analysts can benefit from it.

Pattern recognition – the ability to identify patterns in data and then use those patterns to make decisions or predictions – is often associated with artificial intelligence (AI) systems.

Fig 1. Pattern matching allows computer vision applications to identify objects like airplanes based on shared characteristics such as lines, shapes, and colors.
Source: Google

But pattern recognition is not only useful for machines: it’s also an underrated skill that can greatly benefit business analysts. This is because the ability to spot patterns in our and other people’s behavior helps us make sense of – and prevent – performance issues that initially may seem unavoidable.

How Pattern Recognition Can Give You a Competitive Advantage

A decade ago, I was one of several business analysts working on a multi-year project to implement a large ecommerce system. Each BA was in charge of one aspect of the work: marketing, sales, customer support, compliance, etc.

A few months into the project, one of my peers asked me for advice. She had noticed that I was able to regularly go home early because my engineering team always had a healthy backlog of items ready when they were about to start sprint planning. In contrast, she was often required to stay late to revise her user stories in order to unblock teamwork.

After we talked, it became clear how our approaches differed:

• When working on requirements, in an effort to keep the peace she’d comply with all stakeholders’ wishes. Conversely, I had no trouble challenging stakeholder assumptions and pointing out any inconsistencies in their thinking.

• When scheduling meetings to review her user stories, she’d send invitations to relevant stakeholders and hope they showed up, which did not always happen. I made sure to have “pre-wire” meetings with major stakeholders to go over the decisions we’d have to make during the next session, and to express how important it would be for them to be there to hear their counterparts’ opinions as we discussed functionality and design decisions.

It wasn’t easy for the BA to change her behavior. But because she recognized a pattern of lackluster performance and made an effort to understand what was causing it, now she had a plan for what to do differently to improve her results.

We often spend a lot of energy responding to problems again and again, forgetting that we could be preventing them instead. Here’s another example that may sound familiar, this time from one of my mentees, “Anne”, a business analyst who had been working on a multi-year legacy system migration project.

Anne’s project kept experiencing delays, waste, and disappointing results. And each time a new crisis surfaced, it certainly made sense to focus on the immediate response demanded of the team.

However, one of my questions made her see a new leverage point: “What if, instead of continuing to deal with a never-ending cycle of reaction, you looked into the possibility that these individual issues are part of a larger pattern that you can change?”

And sure enough, while the surface-level problems varied, digging deeper Anne was able to identify a common cause. The migration team kept being given unrealistic deadlines that failed to account for even things as simple as reviewing team members’ vacation schedule in advance, which in turn created stress, rushed work, and mistakes.

Table 1 - Analysis of a legacy system migration initiative that starts by treating each issue as a symptom of a larger systemic problem.

By systematically collecting and presenting the evidence to stakeholders, Anne was able to make a strong statement about how unrealistic expectations were causing the project’s poor results. Rather than continuing to cope with repeated incidents and errors, the project champion’s efforts shifted to reevaluating work processes, delivery dates, and scope management practices to reduce the need for future corrective interventions.

How to adopt pattern recognition in your business analysis work

In business and life, a lot of our failures steam from the same sources. Understanding those patterns makes it easier for us to go from “problem manifestations” to their true root-cause, so that instead of constantly responding to emergencies we can focus on preventing them from arising in the first place.

How to ensure that, in our quest to put out fires, we don’t myopically ignore the larger patterns that could lead to fixing the systems that are causing the problems? Here are the steps I use and recommend to my mentees:

1. Learn about the common patterns that tend to lie behind surface-level problems

The system migration example may have reminded you of other work situations where a team was stuck in perpetual firefighting mode. When pressured to show progress, rather than producing dynamic solutions that stand up to future challenges, it’s easier to stick to a pattern of technical corrections and responses that only address the immediate problem.

In his book Upstream, Dan Heath explores the reasons we tend to favor reactions and responses (“downstream” activities) over preventive (“upstream”) work:

Because it’s more tangible. Downstream work is easier to see. Easier to measure. There is a maddening ambiguity about upstream efforts.

As Heath points out, with reactive work, the action is demanded of us. A BA can’t opt out of fixing requirements defects that are being called out by the engineering team or causing software to fail user acceptance tests. By contrast, defect prevention activities such as making each requirements document go through a review checklist, is upstream work that is “chosen, not demanded.”

Awareness of patterns like our tendency to focus on reaction over prevention can help us improve how we approach work issues and increase our chances of future success.

Sites like fs.blog, Harvard Business Review, and Modern Analyst are useful resources to gain awareness of both negative patterns like outdated structures and rules that hold people and organizations back and positive patterns that lead to sustained high performance.

2. Get perspective

Gaining perspective is essential for spotting the big patterns. A BA too involved in the creation of individual user stories may fail to realize that the overall solution his team is working on is never going to meet customer needs and achieve the business objectives. To avoid missing the forest for the trees, it’s important to step back to look at the bigger picture and view your subject from different angles.

In the system migration story, questions like, “Why do we keep going off-schedule and off-budget to fix unforeseen migration issues?” helped the team leave the “zone of response” and engage in systems thinking to start avoiding problems rather than constantly dealing with them.

3. Seek collaboration

The Toyota philosophy of continuous improvement, famously drilled to “ask why five times”, is meant to take us from a simplistic “A causes B” to a more nuanced chain of thought required to discover that “C causes B, and D causes C”. And to properly follow the chain of causes and effects back to a problem’s root, we often need to combine forces with others.

To get better at pattern recognition, avoid working in isolation. One of the best ways to develop and strengthen our abstract reasoning and pattern matching is to commit to learning from both experts and novices from different domains.

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Taking a few step backs to focus on the chronic instead of the urgent seems like an obvious choice when a person or organization is consistently underperforming. Sadly, many business analysts are encouraged to put all their attention into the emergency of the moment, which limits their effectiveness when dealing with systemic issues.

One way to change this reality is to develop a keener eye for patterns. To achieve this goal, it helps to incorporate the habit of learning about predictable patterns in business and technology, carve some time out to think about the bigger picture, and surround yourself with people who can bring different perspectives to the table.

When a project or process is facing chronic hurdles, try asking, “I’m finding that our team is having to fix ‘X’ repeatedly. What if we spent some of our time and attention looking into what might be going on more broadly to avoid it happening in the future?”

In a world where most organizations tend to live “quarter to quarter”, it may be hard for a BA to depart from established reactive approaches to problem-solving. But for those who fight this short-term imperative and use pattern recognition to their advantage, the prize can be huge. Before long, you may realize that your primary contribution is no longer the delivery of standalone analysis outputs, but rather the kind of learning and transformational change that creates a large and lasting impact on business results.

Author: Adriana Beal

Adriana Beal spent the past two decades helping innovation companies leverage decision science and machine learning to improve business outcomes. She recently left her job as a principal data scientist with a global AI consulting group to return to her roots as an independent consultant. You can find out more about her work visiting bealproject.com.