3 Challenges Leaders Face in a Big Data World

Without data science, leaders find themselves floating in a sea of data they can’t make sense of. But what exactly is this new discipline and why can’t lenders just implement it and move on?

We wrote about this at length in a new White Paper that is available at no cost on our website. But to put it succinctly: 

Data science is the field that uses scientific methods, algorithms, processes, and systems to extract knowledge and insights from structured and unstructured data. It combines various disciplines like statistics, computer science, and domain-specific knowledge to analyze large amounts of data and create models that can predict outcomes and uncover patterns.

In a word: data scientists mine BI for insight. So, why doesn’t ever lender just hire some of these professionals?

CHALLENGE 1: The cost of staffing a data science department is high.

These are the people who make sense of big data. But with the average annual salary of these professionals over $125,000 and almost certain to grow in the future, companies are already looking for ways to analyze more data with fewer people.

AI was an easy answer. Its ability to process and analyze vast amounts of data has made it a highly prized tool. However, the models are still under development. 

CHALLENGE 2: AI alone does not offer reliable insight for decision-making.

AI predictions are not always based on fact. The systems are prone to hallucinate and come up with their own data if not carefully monitored. AI summaries condense data and can hide real insights by crushing them into an easy answer.

Finally, because data science and AI are still emerging disciplines, most companies are still learning to wire everything up correctly to deliver actionable results.

CHALLENGE 3: Getting analysts and statisticians to think like executives.

The data itself presents challenges and companies are not staffed with professionals trained to sort it all out. While data handling tools have evolved rapidly, in most cases, the professionals haven't. The result is that the data science team works through the weekend and then presents the CEO with a spreadsheet on Monday morning that makes no sense to the executive and does not suggest the next steps.

Data workers don’t have the experience to know what information will be meaningful to executives working in the C-suite so either they guess or just give them everything and overload persists.

The problem seems to be circular. Because data scientists and their software systems are expensive we need AI, but since AI is unreliable on its own we need more data scientists. Until a solution is found, leaders will continue to be crushed under the weight of their own information.

Business leaders need the insight that comes from a good analysis of big data. They want to overcome the challenges standing between them and stronger businesses. What they need is a better solution.

Fortunately, such a solution is available now. You can read about it in our White Paper or reach out to us with questions at info@rbiplaybook.com