What drives low BI Adoption in Pharma companies and what can they do?
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BI investments in global healthcare are expected to reach around 10 BN by 2025, but companies are still struggling with low adoption.
In the past few years, pharmaceutical organizations have been investing heavily on enterprise level BI solutions and technologies, to improve efficiencies, save costs and generate incremental value for business.
According to a report by Zion Market Research, BI investments in global healthcare are expected to reach around 10 Bn by 2025, with a CAGR of around 13% since 2019.
With the exorbitant amounts of investments targeted to BI implementations, the companies are still failing to realize the optimal returns. The adoption rates for BI technologies have remained abysmally low at around 30%. While modern, agile, and self-service have managed to increase the adoption and drive value for business, the real and tangible role remains elusive.
Challenges
Working with several pharma clients over the years, we have seen some challenges that are pervasive across the organizations. And the first step is to understand the root-cause.
Solution Approach
Considering the challenges pharma companies are facing, we outline some of ways to enhance the adoption of BI solutions among business users.
User Centric Approach
Pharma companies need to shift their focus from building a single platform for multiple user groups. Mass adoption of analytics will depend largely on delivering analytical solutions, designed for custom user personas, and focused on solving specific business problems.
Adapting ‘Design Thinking’ methodologies to understand users, challenge assumptions and redefine problems is an effective means to develop products with increased value for business.
Leadership Buy In
A strong buy in from the leadership is imperative to fuel Business Intelligence adoption. Business function leaders should be brought on-board the BI journey and enable them to see the value it brings, prior to commencement of the transition.
We recommend joint workshops with IT and business teams to understand the problem areas, present Proof of Concept solutions and rapid prototypes.
This not only helps gain leadership buy-in on the capability of the tool, but also showcase tool agility and flexibility.
Promote BI Success stories
A very adept way to promote BI adoption is to identify champions and power users from the business and collaborate with them to propagate success stories.
It is essential to identify the right set of power users who have successfully adopted the BI solution to become advocates and share their experiences.
We recommend doing interviews with power users on how they use BI solutions to gain critical insights, demonstrate best practices and drive an internal marketing campaign.
This not only helps in improved adoption amongst the non-data-savvy users, but also establishes a continuous channel for product feedback and improvement areas.
Continuous Evolution v/s Revolution
Rather than striving for a utopian solution and delay the deployment of solution, the companies need to focus on delivering continuous incremental value to users. BI based solutions need to be treated like a product, one that is consistently enhanced and improved upon. Setting up defined process to gather continuous feedback from business can help understand new user stories and unmet needs of the different user personas. Periodic release of new product features not only helps retain end user engagement, but also scales up the solution to new business needs.
BI on BI
In an effort to optimize BI engagement, audit data from the tools play a critical role. It not only helps provide baseline adoption rates, but also helps analyze usage patterns. Log data from product usage can help identify views that are being used the most, who the power users are and what assets are they leveraging. It is also important to rationalize the solutions periodically to avoid information overload that the users need to wade their way out of.
Conclusion
While the adoption of BI depends on several other factors such as technological maturity of the company, user base, scope of operations, data density and quantity, embracing some of these best practices can help the companies witness the kind of adoption rate they need to grow revenue, optimize cost, and take the company ahead on the path of next generation Analytics and BI.
