The 5 systemic challenges firms must overcome to derive value from data
It would be safe to say that organizations today have more data than ever before. But deriving actionable insights from the data and converting the insights into value can prove to be a daunting task for most companies. Often, it is not the lack of technology that causes the problem, it’s the culture and inertia carried over from the industrial age that does the damage.
Uber uses real-time demand and supply data to arrive at surge pricing to optimize its revenue. With many million active users, Twitter has made a business model out of breaking news and live trends. Spotify offers music on-demand to more than 75 million users using real-time personalized data. These digital-born organizations are built with data right at the centre of their model. Industrial organizations, on the other hand, struggle with data. There are five systematic challenges, called the 5As of data, that these organizations must overcome to derive value from data. The 5As are Availability, Access, Accuracy, Analytics and Agility.
Availability:“Forty million shoppers buy our products in a year, but we do not know who these shoppers are.” This is one of the classic woes you might hear at an organization that faces the availability challenge. The crux of the challenge is that the organization has incomplete internal and external data sources. An example of internal data that may not be easily available is the health record of employees. An example of external data could be the biometric data of all customers in a retail bank. Decisions in these organizations tend to be made based on limited data or the personal experiences of decisionmakers.
Access:You know that you are witnessing the access challenge if you hear something like this from an organization: “We have identifiable data of all our 10 million customers, but the commercial bank division cannot access the data from the retail bank database.” The access challenge happens when not everyone in the organization has access to the data. This could be part of a design to control access to sensitive data. In many cases, however, the sheer complexity of data systems prevents employees of one business unit from accessing the data from another. These organizations experience frustration because duplicate systems emerge over time, costs escalate, and a lot of time is wasted on just tossing data around from one system to the other.
Accuracy:When an organization faces the accuracy challenge, you might hear something like this from it: “We have 10 different data systems within our organization that capture customer data, each speaking its own version of the truth.
