Pharma Commercial Teams: Building an Analytics Culture as a Driver of Competitive Advantage

By David Kreutter, PhD

This is the second in a two-post series on driving transformation and competitive advantage through analytics for life sciences commercial teams.

In my previous post, I discussed how to scale analytics across life sciences commercial teams and outlined seven crucial areas that drive competitive advantage. In this post, I discuss the challenges of creating an effective analytics culture and why a unified strategy and unified culture are essential to realizing the value of your data by informing decisions that impact your business.

A recent industry survey from New Vantage revealed that executives in organizations of all types -financial, healthcare, life sciences and others – recognize the importance of data and analytics, with 92 percent of surveyed executives reporting that their organizations are increasing their pace of investment in big data and AI[1]. However, senior executive leadership and financial support of data and technology have not been sufficient to transform organizational culture to be more data and analytics driven. The same survey revealed that only 31 percent of executives have created a data-driven organization and a scant 28.3 percent have forged a data culture[1].

Other reports highlight that 60-85% of analytics projects fail to progress from proof of progress into production[2,3], and 57 percent of business intelligence use cases are considered ad hoc analyses[4]. If the majority of analytics projects fail and more than half are being conducted on ad hoc basis, then by definition you don’t have a strategy for data analytics, and the absence of a strategy, means you cannot create a culture.

The overwhelming majority of executives surveyed cited people and processes, not technology as the key challenges to establishing an analytics culture[1]. So how do you build a data and analytics culture that transforms your business and drives competitive advantage?

Key challenges to building an analytics culture

There is little doubt that the advances in analytics technology and the increasing volume and variety of data provide the fertile soil necessary to support a robust analytics strategy, but organizations are still struggling to realize the full potential of these improvements.

So, if the technology and data are readily available, where is the disconnect? I believe the broken link is that most organizations are approaching the problem from a tool perspective while ignoring the people perspective.

Disrupting the status quo is hard. It’s challenging to get people to accept results that are counter to what they believe. I can’t tell you the number of times in my career that I have been told by colleagues point blank that I was wrong, my data was wrong, my analysis was wrong, and my results were wrong. The reason for the pushback? Because I was presenting something that was inconsistent with their experience and with the strategy that they believed was best.

Creating a transformative analytics culture

There is little doubt that the advances in analytics technology and the increasing volume and variety of data provide the fertile soil necessary to support a robust analytics strategy, but organizations are still struggling to realize the full potential of these improvements.

Align your analytics strategy with the business strategy: If you are going to create a data culture, you need to focus on problems that are significant to the business client. Analyses have to be relevant to important business problems and deliver results that are material and visible to the commercial organization.

Translate statistical findings into language that is meaningful to the business stakeholders: Marketers and sales teams don’t typically speak the language of analytics. Analysts have different expertise – no more or less valuable than the internal customers they are serving. When you start to view analytics as a collaborative process with a common purpose, where everyone is working on the problem together bringing different but equally valid areas of expertise, you create the foundation for a data and analytics culture.

Approach problems with a sense of empathy: We sometimes forget that our internal clients are people with strong feelings of purpose and pride in their work. If you want your clients to engage with you, and act on your insights, you need to start treating them just like you would treat external customers. You need to look at things from their perspective –what you can do to meet their needs. Develop empathy for your clients.

Engage and create in a collaborative process: The analytics process should not be one where you meet with your internal client, discuss a problem, go away, analyze the issue in isolation and come back with your insights. Analytics has to become a process of co-creation with your client to develop a shared understanding of the critical issues and the approach to solving them. In the end, you’ll be developing the insights together with your clients and reducing the likelihood of disconnect. As I mentioned in my previous post, once you move toward a more collaborative approach to analytics, you enable everyone to explore the same data from different perspectives. This collaborative exploration develops the analytics literacy of the consumers of analytics, enabling them to ask better questions, promoting the discovery and sharing of novel insights. Leverage an analytics tool that is transparent and easy to use, enabling everyone, regardless of technical experience, to explore data and derive insights independently.

Be open to new processes, data and technology. Learning is a cornerstone of an analytics culture: Be open to the new – new processes, new sources of data, new types of analytics and new tools and technologies that help us uncover unique insights quicker. For example, machine learning has garnered much interest, but broad adoption has lagged. An open-minded, experimental approach will lead to a more collaborative environment that will knock down silos and lead to innovative breakthroughs and yes, a competitive edge.

Communication is central to collaboration

I like to think about analytics as a bookshelf with the books being the technical analytics skills related to acquiring, staging, cleansing and analyzing data. The bookends that support the books are strong communication skills– not just talking but listening and probing for understanding. The bookend on the left is the consulting skills that allow you to probe and understand what the real business problem is and frame it as a problem that can be analyzed. The bookend on the right side is the ability to translate those statistical findings into something that’s meaningful to the business. In order to create a data-driven culture you’ve got to rethink how analytics is provided throughout the organization.

A true data and analytics-driven culture must embrace collaboration and exploration of different points of view that align around insights that solve business problems. Such a culture will increase the speed from insights to action and drive competitive advantage for your organization.

To learn how IHD Analytics can help you scale your analytics capabilities and increase speed to insights, request demo at


David Kreutter, PhD, Senior Lecturer, Columbia University School of Professional Studies, former VP Global Business Analytics and Insights, Pfizer

[1] Big Data and AI Executive Survey 2019, New Vantage Partners, 2019

[2] 85% of big data projects fail, but your developers can help you succeed, by Matt Asay, TechRepublic, 2017

[3] Failure rates for analytics, AI, and big data projects = 85% – yikes!, by Brian O’Neill in Designing for Analytics, 2019

[4] 30 Business Intelligence Statistics for Data-Driven Companies, by Devin Pickell, Learning Hub, May 24, 2019.