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. It takes 15 days to produce a comprehensive business dashboard.” Accuracy challenge happens when the data is available and accessible, but is of poor quality. This could happen because of a variety of reasons: improper training of data entry staff, incoherent data coming in from different channels, inaccurate machine data making its way into the organization without any data processing. Without accurate data, it is pointless to talk about the next challenge, analytics. Essentially, bad data will result in bad decisions, no matter how sophisticated the analytics process is.
Analytics: When an organization faces the analytics challenge, you might hear this from a leader: “We have invested in acquiring the latest technologies for data analytics, but we don’t have the right data analytics capabilities to leverage them for achieving results.” Organizations are spending a lot of money in acquiring software tools for data analytics but the capability of employees in converting data to insight is still falling short.
Agility: At the highest level, data-savvy organizations perform analytics on-demand, in a real-time fashion. You might hear this from an organization that faces the agility challenge: “We have the right data systems, but we are unable to make use of the data on a real-time basis to maximize outcomes.” The root cause of the agility challenge lies in the way work gets done in the organization.
Without a single view of the customer, organizations cannot really do justice to customer experience in the omnichannel-driven digital age. Leaders may want to design their businesses in a way that data flow between different units is seamless. They will benefit from investing in building data capabilities in their teams. It is important that in addition to creating new value from data, leaders must also be mindful of safeguarding existing value through strong data protection and ethical practices around data usage. Leaders can enable their businesses to maximize opportunities and reduce risks by embracing agility in their decision-making process. Leaders will amplify impact by leading the charge when it comes to shaking off the inertia of using heuristics instead of an evidence-based decision-making process inside organizations.
While there are many technology tools to help with the 5As of data, ultimately the challenge lies in the capabilities, culture and mindsets of the people of the organization. These will hold the key to determining whether organizations can derive value from data and stay ahead in the digital race.
This article is the last in the series on leadership in the digital era. Rajiv Jayaraman is the founder and CEO of KNOLSKAPE, an end-to-end learning and assessments platform.