CIO tips for maximizing the value of data:
  • Avoid data paralysis by focusing on action and considering deleting, archiving, or auditing unnecessary data.
  • Clean up data and eliminate input errors, synchronization issues and outdated information.
  • Create a data catalog for data governance
  • Build a culture-driven, data-driven organization by enabling reasonable risk-taking and learning from failure.

Most successful companies share one trait: the ability to make key decisions in a timely manner, which is only possible with the help of data. Data has become the most valuable asset as it contains a wealth of information about an organization’s customers, their behavior, and industry trends that can be leveraged.

According to a PwC study, data-driven organizations can outperform competitors by 6% in profitability and 5% in productivity. But that’s only possible if organizations can use the value of data to analyze numbers, evaluate patterns, gain insights, and make trusted judgments faster. Organizations today have a data strategy and tools in place. As industries evolve due to rapid change, CIOs combine historical data with statistical modeling, data mining techniques, and machine learning to make decisions that improve outcomes.

However, are CIOs taking full advantage of their data-driven organization?

According to Amit Sharma, Chief Information Officer (CIO) and Head of Partnerships at Cytecare Cancer Hospitals, less than 50% of CIO and business decisions are based on data.

“In any industry, at least in my experience, less than 50% of decision-making is data-driven, which shows us there’s tons to do in this space. Industries need metrics development because a data-driven decision will yield the best possible return.”Amit Sharma, Chief Information Officer (CIO) and Head of Partnerships at Cytecare Cancer Hospitals

So what are the bottlenecks for this?

Nikhil Goel, Vice President and Head of Information Technology and Projects at Aetna India, says that with the high volume of data produced every second through multiple channels, it becomes difficult for organizations to streamline information.

Giving an example, he explains that for the healthcare business, data is generated in the background through various channels such as patients, pharmacies, offices and hospital information systems. Petabytes of data are a challenge, which reduces the decision-making process because they do not know the right place for the use of the data, as well as the purpose of the information derived from the collected data.

Even with the existing tools, it is difficult to use them with the best data pointers available because using them without even understanding the purpose makes the decision process more difficult. For example, according to the Dimensional Research survey, nearly nine out of ten companies say they are unable to get real-time information from their legacy ERP systems to make effective business decisions.

Traditional ERP (enterprise resource planning) systems, such as SAP and Oracle databases, are widely used in the Fortune 500 to hold important operational data. Even though these systems are common in businesses, only a few can leverage the data from these systems for decision making. Thus, this makes it important for leaders to identify data placements and benefits from their outcome requirements.

Ninad Raje, Director and CIO, HealthAssure says, “There are tools available, but how do we interpret these analyzes and trends, based on which decisions need to be made. So that’s the challenge, and the solution is to think before you act.

80/20% data-driven decision making

However, whether you’re a seasoned gamer or a data-savvy newbie, too much data can quickly become the same decision-making obstacle it’s designed to eliminate, and turn data into analysis paralysis.

Adding to this, Gaurav Kataria, Chief Digital and Information Officer (CDIO), Sai Life Sciences Ltd. states that 80% of decisions can be made with 50% of data because it is easier to make, however, 20% of decisions are critical and can lead to analysis paralysis.

“When you get data on business leaders or individuals, it may not lead to any end point of the analysis. They would swim through different slides, mentioning that the data didn’t look good or suggest we add another analyze and look at the viewer differently. At the end of the day, there will be tons of meaningful and insightful data, but you will stifle the speed of decision-making as the analysis becomes paralyzing. That shouldn’t happen.Gaurav Kataria, Chief Digital and Information Officer (CDIO), Sai Life Sciences Ltd.

So whether it is a structured or unstructured insight tool, the goal is to work on data collection. Consumption must be kept in mind, which involves training. So while organizations have all the analytics tools, they also have a dozen, hundreds, or thousands of data points to mine.

Revolution of mentalities

To avoid analysis paralysis and streamline data decision-making, there is a need to humanize data, which also helps increase positive instinct and quick decision-making. Here, data visualization can help data analysts connect effectively with decision makers who need to understand analytics and its ramifications. They will not change their behavior and adopt an analytical approach. This has required organizations to train their staff and resources to work with data.

Data literacy has grown in the organization, but Jagmohan Singh Rishi, Global Head – Learning & Development, Wockhardt Limited, believes that the mindset and culture of the organization has put CIOs and businesses waiting to increase data-driven decision-making.

Rapid digitization has raised awareness among senior executives of the importance of data, which has resulted in greater adaptability of the digital strategy and increased IT budgets for the organization. But Rishi says the hope is far-fetched as they are limited to traditional tools and strategies despite building infrastructure.

“After COVID, the CEO mindset changes. As a result, we are left with no other option but digitization. But I find many industry leaders talking about tools for technology adaptation but are still working on an option, for example, if an organization has invested in visualization tools, but upper management or middle management still want to use only excel sheet reports, so the top level needs to instill a mentorship program reversed through data scientists to get used to their data points,” Rishi added.

Therefore, to become an effective data-driven organization, companies need an enterprise data catalog combined with comprehensive data governance capabilities to provide scalable access to trusted data and build a culture. knowledge of data. Organizations must make strategic decisions and produce substantial business benefits by creating a data-driven decision-making culture.

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