Most enterprise leaders understand the value of using data to improve their businesses—at least in theory. The problem is that not enough companies put that understanding into practice, relying instead on trial and error rather than objective, fact-based decision-making.
That’s ironic because, as private citizens, we use data all the time. Whether looking for the best airfare across multiple websites or deciding which restaurant to visit based on other diners’ experiences, data-based decision-making is an integral part of our everyday lives.
The Importance of Data
To go one step further, we at Genpact believe that data and technology, along with human ingenuity, hold the key to solving the world’s most pressing challenges. But to achieve this goal, we could and should democratize data access across organizations, allowing everyone to harness it, analyze it, and then extract insights from the treasure troves of data at our fingertips. However, instead, we often leave data analysis to just a few people, limiting ourselves from achieving the most value for customers, employees, and other stakeholders.
To solve this challenge, consider a project we recently launched using Genome, a platform that provides multi-modal learning opportunities to our 100,000 employees. We named this project DataBridge, a data literacy initiative that allows participants to become data proficient by learning data science techniques.
Working virtually in teams, employees have access to the knowledge they’ll need in a world that requires constant education and reskilling to keep up with the technology revolution. Equipped with this information, our employees generate insights to solve real-world problems.
A Case Study
Using Genome, for example, we help those enrolled in the program – more than 68,000 people – understand and visualize data and then use those facts to help guide decision-making for our clients and our business. For those employees that complete this intensive program, we grant them certifications and select them for future career advancement.
Initially, we launched DataBridge with no incentives for employees to join — their primary motivation was to become more comfortable with data skills. Our goal was to expose 30,000 people to the learning curriculum in the first year, giving them a base understanding of analytical skills. To our surprise, the enthusiasm for this type of training was overwhelming, with more than twice as many individuals initially indicating that they wanted to participate in the program. As of the end of 2021, we have already trained more than 52,000 employees.
To put their learning into action, these employees had to select a project from one of our clients and apply the concepts they learned to solve a particular challenge.
For example, one group worked on how a client could process invoices more efficiently. Under the previous system, company employees would make their best guess as to which general ledger an invoice should be assigned. Often, that involved a time-intensive series of emails and phone calls asking others for help.
To speed up the process, our team wrote an algorithm that looks for data patterns in invoices and then assigns those findings to what it believes is the correct general ledger. The system works with 90 percent accuracy, freeing employees’ time for other tasks and speeding up the payments process.
Another team, working with a workers’ compensation insurance company, tasked itself with figuring out how to reduce the number of claims payouts. Often, dissatisfied claimants may have initiated costly lawsuits if they felt that the offered amount on a claim was less than they deserved.
To reduce the likelihood of litigation, the DataBridge team created an algorithm that looked at historical claims data and identified key elements that could predict the probability of a lawsuit. Claims that met those criteria were then flagged to be fast-tracked and handled by more experienced agents, avoiding potential legal issues.
Equally important, by upskilling all employees in data and analytics, we increased team visibility and communication, shifting employees away from transactional projects and into insight-generating roles.
DataBridge is only one example of preparing our workforce for the future. And it’s all for a good reason. By the year 2030, the World Economic Forum estimates that more than 1 billion people – nearly one-third of the jobs worldwide – will need reskilling to keep pace with digital disruption.
Conclusion
As leaders, we know that employees are our greatest asset, and we see value in offering them the skills they need to succeed in today’s dynamic marketplace. For us, the mission is to help organizations build a similar data-driven culture that empowers and inspires employees to become stakeholders who reinvent how organizations operate today and into the future.
