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April 1, 2021

AI-Powered Analytics Provides a Single Source of Truth

Bijal Karande
Bijal Karande
AI-Powered Analytics Provides a Single Source of Truth

Is Your Life Sciences Company Blinded By Big Data?

Imagine that a group of pharmaceutical executives is meeting to discuss major issues faced by their fast-growing company. As their conversation progresses, they begin to realize that their baseline numbers all differ. By the end of the meeting, no one can form a consensus about the next steps. That’s because everyone’s baseline numbers are the foundation of their assumptions about what needs work. Without a shared set of key metrics from a single source of truth, decision-makers find it impossible to collectively decide on business priorities. For decades now, a single source of truth has been the holy grail for business intelligence (BI). Despite the clear dysfunction that results from multiple versions of the truth (MVOT) and fragmented views of BI, life sciences companies continue to struggle with multiple data silos and competing versions of key metrics. It’s a problem that’s only gotten worse in recent years due to the explosion of big data across the enterprise. How can businesses in life sciences get a single source of truth? Here’s what’s holding them back from data truth and why AI-powered analytics can help.

What is a Single Source of Truth?

A single source of truth (SSOT) is about integrating, synchronizing, and managing disparate data across various systems. Without a single source of the truth, a company’s decision-makers don’t speak the same data language—because they’re all working on different versions of half-truths. As a result, they can’t monitor business performance, and so they end up working on the wrong activities which fail to move the needle.

Harnessing Big Data is Complex for the Life Sciences Sector

Data is multiplying across departments in the enterprise through myriad platforms. What used to be hundreds of millions of records are now tens of billions of records. For the life sciences sector, data is also being generated by devices outside the business—from wearable consumer health devices to doctor tablets and manufacturer data lakes. Historically, however, life sciences haven’t been able to harness this data to create a single version of the truth. Why?

  • There’s too much data. Petabytes of data slow down standard BI systems. Reports built from extremely large datasets can take weeks to create. Business users can’t wait this long.
  • Business users don’t have the expertise to use analytics solutions effectively. Overly complex ad hoc reporting tools cause users to rely on quick and easy shortcuts, like downloading data into Excel.

As a result, users generate the same data from different platforms at different times, and misinformation grows rampant. Multiple versions of the truth lead to confusion, paralysis, and bad decision-making. Inconsistent, contradictory data erodes trust in the numbers and impedes the ability of an organization to understand its current performance or forecast the future with confidence.

Creating a Single Source of Truth for Life Sciences

Thanks to advancements in AI-powered analytics, departmental teams, executives, and senior leadership can all access a single source of truth. And real-time business intelligence can inform every decision. Here’s how WhizAI solves the issue of SSOT:

  • There’s no limit to its data scalability. WhizAI can scale to tens of billions of records. Despite enormous datasets, our AI-powered analytics engine can provide split-second responses to complex analytical questions.
  • Business users don’t need any expertise to get answers instantly. When users need BI, they don't have to download data or ask IT to build them a new report. Getting real-time BI is as easy as asking ad hoc questions with embedded analytics tools. WhizAI instantly delivers answers in user-friendly charts and graphs.

How a SSOT Transformed Operations for a Pharmaceutical Manufacturer

At one global pharmaceutical manufacturer, commercial sales are organized into four therapeutic areas. Within every therapeutic area, there are billions of records. Its diabetes product line alone has 1.2 billion sales records. To speed up BI reporting, the company’s IT team divided sales data into multiple silos by therapeutic area and territory. Over time, however, conflicting numbers and concerning data discrepancies became a major challenge. As a result, the leadership team turned to WhizAI to create a single source of truth to align various strategic initiatives across the company. WhizAI combined data from every therapeutic area and territory into a single analytics model. Now, the company’s sales teams, executives, and senior leadership teamwork from a single source of truth. With business insights at everyone’s fingertips, productivity has improved by 5x. There’s also been a 60 percent reduction in dependency on IT because WhizAI creates charts, graphs, and reports on demand.

Speak the Same Data Language Across Your Organization

When life sciences companies have multiple data platforms that collect a wealth of data, it’s easy for them to feel data-driven. But they’re not data-driven. Establishing a single source of truth is the first step toward aligning your entire company on key performance metrics. Once everyone is speaking the same data language, your company can have truly data-driven conversations and make faster decisions. WhizAI has solved the problem of big data for the life sciences sector. Our AI-powered analytics brings together data across every therapeutic area into a ‘one truth’ single-source data model. It also brings in big data from other healthcare applications and devices. The result is a truly single version of the truth.

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