Unlocking the value of data is a key focus for business leaders, especially the CIO. While in its simplest form, data can lead to better insights and decision-making, companies are pursuing an entirely different and more advanced agenda: the holy grail of data monetization.
This concept involves aggregating a variety of both structured and unstructured data types from various sources and then creating new value-added services and products from this data. While it is no surprise that industries like media and financial services are at the forefront of these efforts, companies in other industries are also pursuing data monetization strategies to better serve their customers.
The advent and availability of advanced artificial intelligence tools are driving these new data-driven products and services, while other parallel processing technologies are equipping companies with a ready-made capability to analyze and create value from massive quantities of data. Natural language processing and chatbots are probably the most common examples of this capability, but new developments (including digital twins and advanced predictive analytics) are also leveraging structured and unstructured data, along with sophisticated algorithms, to increase forecast accuracy and business insight to previously unseen levels.
There is no doubt that data monetization is a worthy objective, and it is increasingly rare to find a company not pursuing this capability in some form. However, this pursuit can also be filled with pitfalls as regulators, private citizens, and politicians become increasingly focused on data privacy and how data is used. Even questions about who owns and controls data are becoming important.
Even more challenging, many people don’t fully comprehend this topic and how advanced it has become, resulting in a great deal of misunderstanding and misinformation. This confusion, as well as fear of the unknown, creates barriers to developing truly valuable data-driven benefits. Such advantages include lofty goals like safer roads and life-saving drugs, as well as more basic benefits like an improved customer experience or the perfect Friday night movie recommendation.
For those already involved in executing a data monetization strategy (or those just starting out), there are some lessons worth sharing from our experience working with clients on this complex topic.
Here are five considerations when embarking on a data monetization strategy:
1. Align with overall business objectives: Whatever your monetization strategy, aligning with overall strategy and business objectives is crucial. This can be challenging, as data monetization by definition can lead to new products, value-added services, or entirely new lines of business – all of which can impact current strategy.
In every case, it is important to spend time understanding the business case for data monetization and how it supports overall business objectives. Will it make existing products and services more valuable, or is the goal to create entirely new lines of business that are adjacent to the existing business? Maybe the goal is to do both.
Clearly understanding this aspect and aligning across the various functional areas ensures consistency around what is being pursued, clarifies potential return on investment, and helps determine the true level of risk. Teams want to avoid taking “bet the whole company”-level risk for a limited return.
2. Have proper metrics and KPIs in place to evaluate success (which implies success is clearly defined): Hand in hand with strategic alignment is an understanding of how success will be measured. Are the right KPIs in place to fully understand the data monetization strategy and corresponding value created? While traditional metrics around return on investment and capital spend are always top of mind, there are other operational metrics that are just as important. Companies should prioritize, for example, mapping out the required cloud compute overhead in the monetization strategy, as well as the potential risks created in the areas of data privacy and security.
A holistic approach to KPIs is one area in which moving beyond pure financial metrics is wise. As with the development of anything related to new AI technologies, it can be a struggle to fully understand the return on investment and value proposition. Creating new products and services around data is complex, and the set of returns may not be easily captured. There is also great uncertainty around the capital required to fully meet the technological challenges – and even what the end state looks like.
Limiting uncertainty is a goal for any new project. Teams should be creative and holistic, attempting to capture every aspect of the plan with a set of complete metrics.
3. Understand the various regulatory schemes and rules, and how compliance must be achieved: Compliance is a potential minefield, as the rules and regulations are ever-changing; what is acceptable today may not be in the future. Often companies only pay cursory attention to these risks, while others become so focused on them that they struggle to make progress. Striking the right balance between caution and compliance is key.
One approach that we have found to be successful is treating data monetization in the same manner as any research and development effort, with clear stage gates from conceptual idea to minimum viable product to a fully finished new product or line of business. This method allows a control environment to be constructed around the data monetization strategy, with an eye to the various markets and channels in which future products and services might be offered. This approach also allows a set of guiding principles to be established, which clearly delineate certain areas of data monetization to be viewed as off limits, based on either current or future laws or the potential reputational risk that come from these efforts.
4. Understand the non-regulatory aspect of public perception, reputational risk, and general risk that can result from data monetization gone wrong: Along with the actual regulations, the risk associated with perception should not be overlooked. While various regulatory schemes may permit some data monetization approaches, public perception, and reputational risk play by other rules. Although it’s a bit of a trope, it is worth asking whether a certain product or service could be explained to a TV news crew from your front lawn.
In reality, some data-based services may be highly valued and appreciated by customers and the general public. Perhaps data monetization is driving new life-saving drugs or surgical techniques that come from monetizing aggregate patient data.
On the other hand, efforts might be viewed negatively. A pharmaceutical sales strategy, for example, that monetizes patient data to sell more types of a certain drug may be frowned upon due to serious side effects. Or an auto maker trying to leverage performance data for customers might be viewed as being needlessly intrusive.
The possibilities for data monetization may be endless, but in the realm of public opinion, there are boundaries to what’s acceptable. At a minimum, this reputational risk should be understood in detail for each part of a data monetization effort.
5. Understand how technology enablers are changing and what this means when planning for the future: It is important to appreciate that we are still very much in the early days of digital technology, with a time frame that is moving much quicker than the computing age we have now left behind. Companies, therefore, need a strong vision for how enabling technology will impact future products and services. There are still rapid changes in both capability and performance: advances in parallel processing, machine learning, and artificial intelligence will all play a role, as will advances in cloud computing and in-memory processing. Newer technologies like quantum computing might also someday become a factor.
It took almost four decades to move from room-sized mainframes in the 1940s to the personal computer on every desk in the 1980s. But now, in an equal amount of time, the computing power and ubiquitous nature of this capability have created new possibilities that were unimaginable just a short time ago. The speed at which new technologies are developed has changed dramatically almost overnight, and the results can be seen in rapid changes to elements like file sharing, social media, and digital advertising. Advances in artificial intelligence, natural language models, and various algorithms are also happening with increased speed.
Therefore, an open mind and critical eye to what the future brings are necessary to avoid building solutions that meet the needs of the past.
We are living in incredible times, and the promise of data monetization is real. Entrepreneurs and leading companies are creating valuable new products, with innovation limited only by imagination as technology improves at an ever-increasing rate. Organizations that are already on the data monetization journey should evaluate how the landscape is changing and whether their existing strategy remains effective. Those who have not yet explored this new world should not delay for too long – valuable opportunities may be missed.