The digital revolution compelled every firm to reinvent it, or at the very least reassess how it does business. Most big corporations have made significant investments in what is commonly referred to as “digital transformation.” While those investments are expected to exceed $6.8 trillion by 2023, they are frequently undertaken without apparent advantages or ROI. Although there are several explanations for these failures, they are typically the consequence of underestimating the different processes or stages necessary to properly execute a transformation agenda.
Common blunders include the naive belief that just purchasing technology — or investing in any of the fancy tools or bright new products of the expanding tech sector — will improve enterprises. Even the finest technology, however, will be rendered ineffective if the necessary procedures, culture, and people are not in place. According to Stanford’s Erik Brynjolfsson, one of the key reasons for the lack of productivity increases from new technology, including AI, is a failure to invest in skills. Particularly reskilling and upskilling once people are in your company. I once persuaded my granddad to get a smartphone; he never even took it out of the package. Persuading experienced staff or senior managers to install new technology tools is a comparable process for many firms.
It’s difficult when businesses decide to begin on a digital transformation program without a clear definition. Also much alone a vision, of what that entails. Although each organization is unique. There are significant differences between different types of businesses, industries, and cultures. The fundamental meaning of transformation is not about replacing old technologies with new ones. Nor capturing large amounts of data, hiring an army of data scientists, or attempting to replicate some of what Google or Amazon do.
In reality, the objective of digital transformation is to become a data-driven organization, with critical choices, actions, and processes heavily affected by data-driven insights rather than human intuition. In other words, you will only be transformed once you have changed how people act and how things are done in your business.
As seen in the diagram below, five components are required to carry out an organization’s digital transformation:
- People
Digital transformation begins with people, which serves as a great reminder that whenever we discuss data — especially meaningful data — humans are at the end of it. Most firms define the people side of change as their access to customers, clients, and workers. Historically, these connections resulted in inadequate or fragmented recordkeeping.
Consider an analog and informal small business, such as a stand-in a Turkish bazaar: the salesmen have extensive access to and knowledge about their customers and clients, but it’s all “stuck” in their heads. Similarly, a London taxi driver or a Parisian cafe waiter may have intimate knowledge of their clientele. What they want, or a small business founder may know the 20 individuals that make up her staff pretty well, without requiring much technology or data. But what happens when a company is too huge or complex to know its consumers or employees on a personal level?
- Data
You need data – conveniently accessible and retrievable records of experiences with customers, employees, and clients. If you want to expand your understanding of customers and workers and replicate it across a huge company and in far more sophisticated and unexpected scenarios. In the process of collecting or making digital recordings of persons, here is where the technology may make the biggest difference. The process of datafying human behavior and transforming it into standardized signals is known as “digitization” (0s and 1s). It’s vital to remember this since the genuine benefits of technology are “soft” (i.e., less costly systems or infrastructure), not “hard” (i.e., less expensive systems or infrastructure) (i.e., capturing valuable data).
- Insights
Although data has been dubbed the “new oil,” its worth is defined, like oil, by our ability to filter, cleanse, and power anything important. Any data, such as 0s and 1s, will be useless in the absence of a model, a system, a framework, or credible data science. With the correct skills and tools, data can be transformed into insights. Analytics, the science that helps us make sense of data, is emerging from technology at this time. We will be able to test this model through prediction to the extent that we have significant insights, a story, a sense of what may be going on and why, or a model. It’s not about being right here; it’s about finding better ways to be incorrect. To some extent, all models are incorrect, although some are more useful than others.
- Action
Getting to the insights stage, however, is not enough. In reality, without a concrete strategy to put them into action, even the most intriguing, compelling, and surprising discoveries would go to waste. Even with the finest AI, data science, and analytics, as Ajay Agrawal and colleagues argue, it is up to us humans to figure out what to do with a forecast.
Assume your findings indicate that a particular sort of leader is more prone to derail – how will you alter your internal recruiting and development process? What if it informs you that buyers detest a certain product? How will this impact your product development and marketing strategy? And imagine you can forecast which clients are likely to go to your competition; what would you do? AI can make predictions. Data can provide insights, but the “so what” element necessitates action. These actions necessitate the necessary skills, procedures, and change management. This is why talent is so important in unlocking (or, conversely, impeding) your digital transformation.
- Results
You can analyze outcomes or influence at the end of the procedure. However, this is not the final step; after evaluating the findings, you must return to the data. The results form part of the new, richer dataset, which will be enhanced and improved with the process’s discoveries. This iterative process or retroactive feedback loop allows your insights to become more predictive, relevant, and useful. Which in turn increases the value of the data. And in the process, you improve and build the people skills required to create a powerful synergy between humans and technology.
In summary, the keyword in digital transformation is “transformation,” not “digital”. Our world has evolved tremendously in the last two decades, and adjusting your company to these changes will not happen immediately. Nor will it be accomplished merely by purchasing new technology or gathering more data. What is required is a transformation in thinking, culture, and talent, as well as upskilling and reskilling your team to ensure future readiness. That being said, one thing hasn’t changed. All of this is merely a new version of old work or a problem that every leader has always faced throughout human history. During preparing their teams and organizations for the future and creating a better future.
Nobody can claim to be a genuine leader if they are in charge and the status is maintained. The name we assign to today’s bridge is not an exception to the digital transition norm. It is the vital job of leaders to construct a bridge between the past and the future. Leadership is always a war with the past, with tradition.
