2020 will go down in the books as the year where the acceleration of digital during the COVID-19 pandemic shaped the next normal. A study from Psychology Today concluded that it takes an average of 66 days for a behavior to become automatic. If that’s the case, then that’s great news for business leaders who have spent the past ten months running their companies in ways they never could have imagined.
“Business leaders are saying that they’ve accomplished in 10 days what used to take them 10 months,” says Kate Smaje, a senior partner and global co-leader of McKinsey Digital. “That kind of speed is what’s unleashing a wave of innovation, unlike anything we’ve ever seen.”
Now, leaders must be wondering how to keep the ball rolling to stay virtual, digitally centric, and data-driven- because everyone is talking about innovation but there are still lots of questions as to how to move forward.
In our early days at Datagran, we learned to listen to our customers and what they needed in terms of business and technology so we could improve our product. In tandem, we also became our own customers, by running models from our entire company’s data with the tools we were building. We wanted to build, but we didn’t want to miss the opportunity to understand what companies truly needed, so we needed to shift from a product-centric approach to a customer-centric one. And that had to be achieved by also applying it to our own day-to-day needs. We wanted to reinvent ourselves by harnessing technology, and then help take our customers from working on analog to digital, a place we believed would power their companies to be the best they could be. We’ve done this by offering demos to prospective customers as part of our sales machine strategy, and what we’ve noticed throughout this process, is the excitement in their eyes when they discover insights that we gather from data they provided and that they never knew existed. We learned pretty fast, that giving people the right tools opened their spectrum to new possibilities to make the business better and truly understand their customers, operations, processes, and more around their organization.
Narrowing the scope and starting with small strategies like choosing the right tools for your teams, is a safe passage to keep the momentum going. For example, starting our by choosing the right ML tech stack is a great starting point. Large companies who are leading in the digital transformation space do this, but they do it with a certain flair. Here are some key elements that have placed them on the top of the race:
Digital Speed: These types of companies act fast. They reallocate funds and talent 4x faster than their competitors.
Reinvent: As business gets stagnant, these companies reinvent themselves and often by harnessing new tech.
Risky bets: If you can’t beat ‘em, join ‘em. This is their mentality and their bets are usually big in the forms of major acquisitions.
Data-driven: “The road to recovery is paved with data,” Smaje says. High-performers are three times more likely to say their data and analytics initiatives have contributed at least 20% to EBIT (from 2016–19). Data shines the light on black boxes, providing the tools to make better decisions.
Customer-Centric: Being “customer-centric” (in addition to operational and IT improvements) can generate economic gains ranging from 20% to 50% of the cost base according to a McKinsey study.
As 2021 unravels, we see AI becoming as accessible, democratized, and affordable as it could be. Starburst's Borgman says "ML/AI will become more accessible to a broader base of users." He adds that while data science backgrounds have been necessary to take advantage of AI up until now, that this "is changing to include anyone in the organization who needs data access to make more intelligent decisions." Years ago the IT department was completely siloed from the rest of the business units within the organization. Today, anyone in the company, whether that’s sales, the CEO, a marketing manager, and even a PM can log in to a data modeling dashboard, export the results to a business app and start iterations right then and there. Datagran for example, offers a No-Code platform for coders and non-coders who need to optimize their ML modeling. Anyone in the company can open an account, integrate all of their data without having to clean and process it, then run ML models with Spark algorithms, and send the results to Facebook Ads as a Custom Audience for example.
For Domino’s Pizza, building a stack that connected data from their database, into their business application of choice like Intercom, would take months. With Datagran, their team of data scientists is now able to build ML models and put them into production in minutes, not months, a process that was hurting their efficiency.
In terms of introducing new technologies and shift the culture within the organization, business leaders should understand that individuals are now being mindful that they must learn data literacy and leave behind the days of gut feelings to make decisions. Aaron Kalb, Alation's Chief Data and Analytics Officer, believes that 2021 will be the year that "data literacy goes mainstream." He continues: "In 2019, most people found math, stats, and data to be boring, intimidating, or irrelevant. But after a year of scrutinizing margins of error in election polling, watching exponential COVID case curves, and learning about "R-naught," those topics certainly seem important and impactful, and more accessible too." Having these monumental events as examples will empower people to learn to read data until it becomes a given skill. 2021 will be the year where we will see the real data-culture shift, where leaders will emerge as examples, proving that the right mix of tools, people, and processes enables innovation.
Now, remember, “Our ability to adapt is amazing. Our ability to change isn't quite as spectacular.“ Change hurts, it entails changing processes, hence feeling uncomfortable, out of place, but like natural selection, this is a race of the fittest, and only the true innovators will push forward. Tackle change head-on, but start by setting small goals, and work your way up. Try testing out a consolidation of your company’s information into one place. Then discover insights into what your customers are saying without saying it by tracking their behavior. Test your team by building ML models without the need to code, a job anyone with simple SQL knowledge can perform. But start somewhere.