A mildly traumatic experience taught me one of my first lessons about data storytelling. Early in my career, after completing the first year of my Master of Business Administration (MBA) program, I secured an internship at a well-known, multichannel retailer based in the Midwest. At the time, the economy was in the middle of a tough recession, and many US corporations weren’t interested in hiring international students like me who would incur additional fees to sponsor. Fortunately, my online marketing experience in Canada appealed to this retailer, and I was offered an intern position in its acclaimed ecommerce department.
As one of several MBA interns vying for a job offer at the end of the summer, I had an important midpoint presentation coming up with the senior vice president (SVP) of ecommerce. It afforded me a crucial opportunity to ensure my project was heading in the right direction before my final presentation. With a pregnant wife and two young kids counting on me to secure a full-time position, I was feeling substantial pressure to make a good impression on this influential executive.
The SVP in question wasn’t your typical business leader. He was a former military captain and special forces helicopter pilot. If his austere demeanor wasn’t intimidating enough, he was also extremely sharp and had graduated from a top-tier business school. Over the years, many MBA interns saw their carefully crafted presentations shot to pieces in review sessions with this senior executive; it was not uncommon to see shell-shocked faces and tears after his meetings.
Not intending to become one of his many casualties, I worked diligently to prepare for my midpoint presentation. I was pleased with the progress I had made on my project, and I was confident in my ability to present what I had accomplished so far. However, during the course of my project, I had stumbled across an interesting data point while reviewing customer survey responses. The data indicated a commonly held practice related to order shipping wasn’t as important to customers as the ecommerce team supposed. Even though this insight wasn’t central to my project, I decided it was worth sharing because if the data turned out to be true, it could have a significant impact on the ecommerce team’s approach.
When the day came for me to present, everything went well—until I got to the slide with the customer survey insight. It generated a reaction from the SVP . . . but not the one I expected. He leaned forward and blurted out “Bullshit”—not under his breath but forcefully for everyone in the room to hear. His emphatic response ensured no one in the room would challenge his authoritative opinion on the matter—including me. It felt like I had just stepped on a landmine—a cultural one. A paralyzing feeling of panic swept over me as I realized how ill-prepared and exposed I was at that exact moment. Luckily, a daring mentor jumped in to provide some needed cover fire so I could recover and stumble through my remaining slides. While my ego was a little shaken, I survived the meeting and left the boardroom with a valuable insight of my own.
As I reflected on the experience, I realized I had made a serious miscalculation. In my naive excitement to add value and contribute a potentially meaningful insight, I assumed the potential merit of the insight would ensure its acceptance and further investigation. Unfortunately, sheer merit alone wouldn’t be enough to safeguard its adoption. Like so many other promising findings that have never seen the light of day, my insight was dismissed. It died in the boardroom that day. While noble and aspirational, the meritocracy I ascribed to was an illusion. People and organizations aren’t always open to new findings—deliberately or unintentionally—that can better their performance or position.
Many factors contributed to the demise of my insight: my poor delivery, the executive’s closed-mindedness, and cultural inertia. However, a key contributing factor that sealed the insight’s fate was the level of change it would incite. Insight and change go hand-in-hand. Whenever we uncover an insight, it inescapably leads to changes if the data is acted upon.
Often, the potential value of a discovery is directly proportional to the level of resistance it will face. While we may want to believe insights are harmless gifts, they can have subtle-to-significant repercussions that may be difficult for people to accept. Generally, the bigger an insight is, the more disruptive it will be to the status quo. People can struggle with giving up what’s routine and familiar. When a new insight isn’t well understood and doesn’t sound compelling, it will have no chance of overcoming resistance to change. After this experience, I discovered if you want to be insightful and introduce change, you can’t just inform an audience; you must engage them.
Why Change Is Important
The ancient Greek philosopher Heraclitus viewed change as being central to the universe and is attributed with the saying “change is the only constant in life.” We live in a constantly evolving world that is more random, noisy, and unpredictable than we want to admit. It’s important for individuals and organizations to be adept at adapting to shifting environments. As former General Electric CEO Jack Welch said, “Change before you have to.” Instead of becoming stagnant or settling for less, we often search for new ways to improve ourselves and the world around us.
Throughout time, mankind’s innovations have been driven by people seeking to make things better—faster, cheaper, safer, more efficient, more productive, and so on. Groundbreaking innovations such as the printing press, telephone, automobile, computer, and internet have introduced significant change. These scientific breakthroughs necessitated the tearing down of established beliefs, skill sets, and systems in order to replace them. Change becomes an unavoidable byproduct of progress. If you want to advance and improve, you must pursue new insights and implement new ideas that inevitably introduce change.
Not all change has to be massively disruptive. Post-war Japanese manufacturers developed the kaizen philosophy (“change for better”), where employees were encouraged to continuously introduce small, incremental improvements throughout their factories. Eventually, the culmination of these small process refinements over the years helped Japanese firms such as Toyota and Sony gain a major competitive advantage in terms of product quality and manufacturing efficiency. Today, most innovative startups and even large companies embrace a similar lean methodology that involves incremental experimentation and agile development.
An essential underpinning of both the kaizen and lean methodologies is data. Without data, companies using these approaches simply wouldn’t know what to improve or whether their incremental changes were successful. Data provides the clarity and specificity that’s often needed to drive positive change. The importance of having baselines, benchmarks, and targets isn’t isolated to just business; it can transcend everything from personal development to social causes. The right insight can instill both the courage and confidence to forge a new direction—turning a leap of faith into an informed expedition.
Everyone Becomes an Analyst
For the greater part of the past 50 years, data has been primarily entrusted to only two privileged groups within most business organizations: an executive who required data to manage the business; or a data specialist—a business analyst, statistician, economist, or accountant—who gathered, analyzed, and reported the numbers for management. For everyone else, exposure to data has been fairly limited, indirect, or intermittent.
In today’s digital age, data has become more pervasive, exposing more people to facts and figures than ever before. The volume of data is expected to grow 61% each year, reaching 175 zettabytes by 2025 (1 zettabyte is a trillion gigabytes) (Patrizio 2018). Much of this explosive growth can be attributed to the increasingly connected world in which we live and the additional data that is being created by machines—not just by humans or business entities.
Data has rapidly become a key strategic asset, shifting from being “nice-to-have” to essential at most organizations. For example, for tec...