If we have data, let’s look at data. If all we have are opinions, let’s go with mine.
-- Jim Barksdale, former CEO of Netscape
The majority of IT business analysts spend their careers in “reactive mode”. They are assigned to tasks like define the requirements for a new partner loyalty program, create user stories for an enhancement to a billing system, and go about delivering their artifacts.
While these BAs can create value for their organizations by executing these tasks with competence, their level of contribution will always be considerably smaller than the contribution achieved by BAs who adopt a more proactive and data-centric approach to their work. I call this other category of BAs “data-inspired analysts”.
Data-inspired analysts are those analysts who make a conscious decision to “go upstream” and find data to help their organizations identify the areas of value creation with the highest return on investment before jumping into “solution mode”.
Let’s look at an example. Imagine an American university that is trying to find ways to improve its financial situation. The global pandemic caused the institution to lose millions due to deferred admissions, housing and dining refunds, etc. A data-inspired BA could decide to take a look at opportunities to increase registration in the university’s online noncredit certification programs, a good source of revenue that is not reaching capacity.
Unasked, this analyst could investigate the data from logs of web-based form submissions and conclude that 30% of the forms requesting registration to an informational session were raising a server-side error due to a misconfigured field. The BA could then write a report demonstrating how the 5-figures online courses are being negatively impacted by a “leaky sales funnel” as 30% of the “hot leads” are denied the opportunity to learn more about a program to decide if it’s a good fit. Those leads are likely to get frustrated with the bad user experience and switch their attention to a competitor’s offering. The report could include a recommendation to fix the issue for a potential return of an upper 6-figure value in additional revenue.
Photo by Campaign Creators on Unsplash
A BA doing “detective work” using available data may uncover big opportunities for value creation.
The same kind of initiative-taking can be used in the context of assigned projects. Let’s say you have been asked to work on enhancements for a field management dashboard. Leadership has evidence that the dashboard acts as an effective decision support tool for field managers, helping increase company revenue. The goal is to improve user experience and functionality in order to increase the percentage of field managers who use the dashboard on a weekly basis, currently below 50%. The project sponsor would like to see near 100% weekly usage across the user base.
Digging deeper into dashboard usage data, you might identify three segments of users among field managers:
Regular users. Field managers who are already using the dashboard on a weekly basis, as expected.
Occasional users. Field managers who are using the dashboard monthly or in lower frequency.
Non-users. Field managers who never open the dashboard.
Suppose that data tells you that 48% of field managers are regular users, 3% are occasional users, and 49% are non-users.
Armed with this information, you could go back to the project sponsor and say, “The dashboard enhancement project would make sense to pursue now if the non-regular users population comprised a large number of occasional users that might be motivated to log in more often based on an improved user experience. However, data shows that 94% of non-regular users never use the dashboard, while only 6% are occasional users. This means that presently the lift in weekly usage that can be achieved via dashboard enhancements is very small. The best next step would be to investigate why the non-user segment is refusing to even open the dashboard, and get them to join the occasional user segment so they can provide feedback into what would help them become regular users.”
You may be thinking, “that makes sense, but I already have a full plate with existing projects. How would I find time to go look for data to identify underserved opportunities in my organization?”
One of the secrets of data-inspired BAs is that they are intentional about how their workday unfolds. In order to have time to find and pursue higher value creation opportunities, you need to restrict the time you spend on low return tasks. Create a list of hard-to-change commitments (e.g., providing status updates to the project manager on a weekly basis) vs. highly changeable commitments that you can modify to save time (e.g., replacing ad hoc interruptions every time the project manager has a non-critical question with a daily 15-minute Q&A at a specific time of day). Then, block time on your calendar to dedicate to the higher-level thinking required to find a value creation hypothesis, go after the data to support it, and build the business case for your recommendations.
As a result of COVID-19, many companies have seen a dramatic shift in their sources of value creation. Some pre-pandemic initiatives may no longer make sense. Leaders are having to make quick decisions to address challenges using new ways of working based on digital technology, automation, artificial intelligence.
All those changes create big opportunities for BAs willing to become data-inspired analysts to shine and develop an advantage over the competition. In today’s work environment, any BA who isn’t putting the effort to back their recommendations with hard evidence is going to face a steep uphill climb to sell their ideas. As the famous quote by Jim Barksdale states, if all we have are opinions, decisions will be based on HiPPO (highest paid person’s opinion).
Data can take the emotion and opinion out of decision-making and shed light into the opportunities with the greatest potential for growth. By being curious about the data, and constantly asking how the pieces fit together, data-inspired analysts help their organization identify, size, and prioritize the biggest opportunities, and develop solutions that are measurably better than before.
Author: Adriana Beal
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. Since then she has been working in data science projects related to healthcare, IoT, and mobility. Currently the Lead Data Scientist at Social Solutions, Adriana has two IT strategy books published in her native country, Brazil, and work internationally published by IEEE and IGI Global. You can find more of her useful advice for business analysts at bealprojects.com.