Value of data analytics

Extracting Value From Your Data Analytics Investments

Matt Pedone
Director, Enterprise Strategy
Jan 22, 2024

If you’ve invested millions in your data and analytics capabilities but can’t articulate the return on your investment, you might be crazy. While doing the same thing year after year expecting different results is essentially the definition of insanity, don’t worry, you’re not actually crazy. At least, not because you’ve been doing this. 

The History of Data and Analytics 

The Early Days of Data and Analytics

The data and analytics space is wildly complex and ever changing. Today, it is almost impossible to discuss any topic without acknowledging the profound influence of data and analytics. The importance of data is evident in various fields, including technology, finance, health, environment, and social science.

Data collection dates back to as early as 3000 BC when ancient civilizations relied on rudimentary methods to gather data. The Egyptians used papyrus to track information about sales transactions and their inventory, while ancient Greeks employed the method to gather demographic data of soldiers. Such historical use of data indicates its significance even in ancient societies, helping leaders make informed decisions.

The Shift

data analytics

However, it was the 20th century that changed the dynamics and amplified the potential of data like never before. With the advent of computers in the 1940s and 50s, electronic data processing came into existence, opening a gateway to endless possibilities. 1965 witnessed the creation of the first database management system, and by the 1970s and 80s, the emergence of spreadsheets transformed the face of data manipulation and storage, making data easily accessible and usable.

The evolution of data reached an unprecedented speed at the dawn of the 21st century. With the internet boom and increasing digitalization, vast volumes of data started being created and processed every day, marking the dawn of Big Data.

Today, we stand at the cusp of another seismic shift in the world of data and analytics. Concepts like Artificial Intelligence and Machine Learning have become integral parts of data analysis, delivering powerful insights at rapid rates. Meanwhile, privacy regulations and ethics around data have become equally essential.

The Complexity of Data Analytics Today

data analytics challenges

Looking back, the journey of data and analytics from being a tool of basic record-keeping in ancient societies to becoming a sophisticated, omnipresent part of modern civilization is indeed captivating. In this digitized world where data is the new oil, our understanding and use of data have shaped and will continue to shape our lives.

On top of the expectations from your boards and executive leadership teams to be innovative and drive growth, you also have departments and cross-functional teams eagerly seeking out the latest technologies they believe will help them reach their strategic objectives. Companies of all sizes and across various industries are investing heavily in these 'digital transformations', with projected spending exceeding $3 trillion by 2025.

Why might this be? There are a lot of reasons. Some of these factors are more intricate than others, but one consistent observation we have made in our extensive work with Fortune 100 companies facing this issue is that it is simpler to quantify outputs rather than outcomes.

It is rewarding for a team, department, or leader to proudly showcase their accomplishments. However, often these achievements do not necessarily reflect their true value, but rather signify the completion of a project. Don’t get me wrong, celebrating successes is good, but you have to know those efforts are going to pay off for the organization, ideally in the form of direct ROI.

In the past year, the data and analytics market reached a staggering $175B. This proves that companies are investing massive amounts of money each year in pursuit of the competitive edge promised by their data. However, when they pause to reflect on what they’ve gotten for those investments, they find themselves frustrated with the results. They discover they don’t have the right data, question its quality, struggle to gain valuable insights, and fail to democratize the data in a manner that encourages informed decision making.

Most executives are left asking themselves, “How do I know that all of these data and analytics investments are making a difference for our organization’s bottom line?” 

Defining Economic Value of Data Analytics 

Despite all of the challenges your organization has faced in the past, you can find some comfort in the fact that there is a solution. Thanks in part to the amazing work of Bill Schmarzo, who is a recognized global innovator, educator, and practitioner of Big Data, Data Science and Design Thinking, organizations around the world have been able to define the economic value of their data and analytics assets. Bill has taken a series of well known economic concepts and developed a series of data and analytics focused theorems. 

At Further, we not only help our clients define meaningful measures of economic value by connecting their data and analytics assets to their strategic business outcomes. Additionally, we provide support in developing an agile, test and learn framework to optimize their business based on these value indicators. 

Armed with a meaningful set of value-oriented performance measures, decision makers can truly make data informed decisions that allow them to optimize for value – replacing outputs with outcomes. Using an agile, test and learn framework enables quicker, more value oriented decisions and removes unnecessary bias.  

test and learn data analytics

Evaluating The Value of Data and Analytics at a Global Pharmaceutical Company

We worked with a global pharmaceutical company to evaluate their data and analytics investments, we were able to define the existing use cases associated with their first and third party data, which allowed us to assign an economic value to those data sources. 

We were then able to derive the incremental value that could be created as new use cases were addressed with the same, or adjacent, data sets and analytics assets. This provided a clear roadmap for incremental value creation for a nominal, if any, additional investment. 

As a result, not only were they able to justify the investments they had made thus far but were able to secure additional funding to acquire new data sets and invest in additional analytics infrastructure and associated data products. 

They saw positive impact to key success measures, like we see with other health and life science organizations we work with. Typically we see anywhere from a 15-25% increase in sales funnel progression, a 50-60% decrease in prospect acquisition cost and a 40-50% prescriber / provider growth. 


There has been a significant increase in investment in data and analytics. This trend is expected to continue in the future. In an environment of more expensive credit, increased inflation and waning consumer confidence, now more than ever, there is a growing need for measurable ROI from these investments. 

data driven decisions

Now is the time to recognize the value of your data and analytics assets, understand how they are being used, and find ways to enhance their effectiveness for creating value. Contact Further to learn how we can help.

Matt Pedone
Director, Enterprise Strategy

For almost two decades, Matt Pedone has been helping Fortune 500 organizations realize the full potential of their data to accelerate growth and create value within their respective organizations. As a Sr. Principal at Further, Matt leads the development of robust data strategies for our clients and ensures our client teams are bringing the right data, cloud, and AI solutions to the table to enable them to achieve their goals. All of Matt's free time is spent with his wife and three kids, traveling the globe, coaching rookie baseball games, bringing art projects to life, or making sure his toddler isn't letting their puppy out the front door. 


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