Ever since digitalization advanced to a new way of servicing consumers, enterprises have constantly grown investments to enable continuous transformation in the:
- Fast adaptation to new innovations
- Full understanding of customers to design personalized products and features
- Evolving governance processes to manage business and legal risks
- Development of advanced technology solutions to stay ahead of competition
For this reason, we hear from all the business leaders on their efforts in digital transformation, big data transformation, and becoming data-driven organizations.
As a fellow consumer, and from our interactions with various business leaders, we have seen and experienced the advancements in digital and big data transformations within the last decade. Nowadays, everything is done digitally. A businesses ability to digitalize in a short period of time would not have been possible without all the foundational efforts that have happened in the last two decades (e.g., how fast businesses make their products and services available online during the ongoing COVID-19 pandemic).
However, one area businesses are not where they want to be is in becoming a data-driven organization. Not only do organizations know where the gaps in their business are, their customers also experience those gaps in the products and services they receive from the business. As a consumer, how many times have you received inconsistent messaging from a business through direct mail, email, phone, or even the business representatives themselves?
Based on personal experience and information gathered from our clients and network, we see two key reasons that are slowing organizations down from becoming fully data driven:
- Origin of Insights – Where and how the insights are generated.
- Spread of Insights – How the insights are spread across the enterprise.
Origin of Insights: Reliance on people’s (employees) experience or limited data science resources
Businesses have all the data, advanced data science techniques, cost effective computing, and storage solutions available to them to generate insights from everything and anything. However, not all businesses can hire data scientists to apply advanced analytical techniques and generate insights. These businesses rely on the institutional knowledge and experiences to design new products and customer treatment strategies.
Companies who can afford data scientists are doing a pretty good job of generating hidden insights. This is the reason we, as consumers, wonder many times, “Wow, how do they know I am going to travel?” or “How do they know I’m interested in these shoes?” The challenge here is that organizations are still depending on their data scientists, which even in big corporations are few. In the age of big data, there is so much information available that it is nearly impossible for data scientists to analyze all the data at hand to garner the most accurate possible insights in a reasonable amount of time.
Even if a company somehow managed to have an unlimited number of data scientists working 24/7, human error innately means that they are going to miss something or focus on externalities within the data that seem like trends but really are not. The overload of data not only makes it impossible for data scientists to make insights that truly encapsulate the data, but also increases the likelihood that they waste time and resources focusing on data that does not matter.
Spread of Insights: Companies can only become a truly data-driven organization when every associate in the business is fully knowledgeable about the business, products, and their customers
Even when data insights are synthesized, the spread of that analysis is curtailed by an inefficient system. In most organizations, data scientists are associated with individual business units (e.g., marketing, risk, customer management) or with a centralized analytical team. Both structures rely on these data scientists to spread the knowledge across the enterprise. Usually, the information needs to go up in many organization layers before reaching leaders with an enterprise view, and then is cascaded down to the rest of the organization.
During each step of the process, the data insights inevitably lose their purity to human error. With each new person that the data moves up to, there is a risk of misunderstanding the information, emphasizing certain parts of the insights based on limited awareness of enterprise knowledge, and there being conflicting knowledge coming from different sources.
Path to becoming a truly data-driven organization
Businesses can become data-driven organizations only when:
- Insights are generated from everything in as real-time as possible.
- The insights are directly democratized across the organization, making all associates citizen data scientists.
This requires investing in augmented analytics capabilities that leverage artificial intelligence to generate business insights in every aspect of the organization and for everybody in the organization.
OneDATA.Plus is an enterprise marketplace solution that is designed to enable organizations small to large in managing their data, analytics, customer, technology, and governance in one solution. With OneDATA.Plus, a non-technical person with little data knowledge can manage enterprise data, a non-engineer can generate 360 and 3D views to understand their customers better, and non-data scientists can get business insights without knowing data science.