I recently had the opportunity to speak on the topic of data monetization at the 2020 MIT Chief Data Officer and Information Quality Symposium (MIT CDOIQ). This summit, now in its 14th year, has long been a place for leaders in data science and analytics to share their insights regarding new technologies and trends at every scale and across every industry.
Data monetization has been a hot topic in the world of CDOs this year. The global pandemic has forced many companies to alter their business models. Customers refrain from visiting stores in person, supply chains shift erratically due to closures and changes in demand, and this means that companies have a more difficult time selling traditional products and services. Data isn’t affected by quarantines or lockdowns—so how can you use it to improve top and/or bottom line of the company?
Two Ways to Monetize Data
Companies can use their data to monetize either directly or indirectly.
Indirect monetization is when a company utilizes its own data assets in a strategic way to either improve sales or reduce costs. An example of improving sales and revenue is to analyze consumer spending patterns and understand which customers are primed to buy more of your product. Data driven cross-sell and up-sell are most common examples of Indirect monetization resulting in increase in revenue. Another way companies use indirect monetization is through reduction in costs. Optimizing processes and resources based on insights from data can lead to gaining more productivity and operational efficiency which can reduce the costs and improve the bottom line.
Direct monetization is about creating a new revenue stream. Direct data monetization, in which you either sell your first-party data, sell the analytics related to that data, or create a new product informed by your data, has enormous potential for revenue growth, and it may be transformative for your organization. Research from MIT Center for Information Systems Research (MIT CISR) shows that top-performing companies can generate up to 55% of their revenues from data alone.
Why is Direct Data Monetization So Powerful?
MIT CISR broke down companies into four categories, each based on a different data monetization strategy: operational optimization, customer focus, data business, and future ready. The former two strategies, operational optimization and customer focus, are essentially the indirect monetization strategies we’ve already covered. Data business strategy is all about direct monetization while future ready is strategy that includes both direct and indirect monetization.
Source: MIT CISR
As you can see above, the top performing companies in the data business and future ready categories have monetization outcomes that are head and shoulders above those using indirect monetization. What’s more, nearly every organization—regardless of their industry, can pursue a data business or a future ready strategy to some extent.
With that said, creating a data business requires scale, expertise, and creativity. Companies that succeed in this arena aggressively link their data monetization to their sales efforts. They also make leadership show their work, creating KPIs that can attribute revenue to data monetization efforts. Additionally, companies in this arena are intensely competitive. Rivals will copy analytics techniques if they can figure them out, so there’s a huge importance attached to finding an original approach. Lastly, successful data businesses know that market needs change quickly and dramatically, so they need to be poised to change their approach on relatively short notice.
How to Become a Successful Data Business
With all those challenges to becoming a successful data business, how does any company succeed?
Here at HYLA, we’re proud to have a successful data business, and so we’d like to use our success as a model for other organizations. Our Device IQ platform is the industry leading data/analytics solution that is used by leading wireless carriers, OEMs and retailers alike to gain insights into the mobile device ecosystem. Our productization of Device IQ platform was carefully done in a series of steps. Below are some generalized steps that you can take to productize your data.
First, start with solid data foundation. Having mature and trusted data is the key to any successful application of data. It is not only about data but everything around data including and not limited to Data Governance and Master Data Management (MDM). There are numerous Data Maturity Models (DMM) available to gauge your organization’s data maturity before embarking on any data monetization journey. This assessment will help you understand your organization's data capabilities and address any shortfalls and vulnerabilities.
Next, you understand the data and analytics needs that you can address with your data. One thing to watch for here is losing competitive advantage while building data products. You obviously do not want to include those data elements in your data and analytics solutions. As you build products (Data as product, Analytics as product), always start with internal users but with a very disciplined approach to product management. You need to build a constant feedback loop with internal users and watch their usage pattern. Any enhancements that comes out of that exercise is then fed back to your product roadmap.
Once the product has been used internally for a significant amount of time, you start preparing for an external launch. External product launch is a lot more difficult. It starts with defining sales strategy including sales channels, prices, packages, bundling with other products, etc. Also, extremely important is having a good legal review of the product and getting all key documents like data agreements, licensing agreements, data ownership agreements, etc. ready. Equally important is data security. Ensuring that your customers can access your data in a secure way is a key for successful data productization.
Keeping up with customers’ needs and continuous evaluation of changing industry will go a long way in keeping the product relevant for your customers. Sharing with and getting feedback from customers on the product roadmap will ensure that they stay connected with product and always know what is coming. Also, remember that Data Productization and Monetization is not a one-time exercise. It is a mindset and culture of the organization that always keeps thinking of new ways that data can be strategized for customer usage.
HYLA’s Device IQ has established itself as the industry leader in providing data and analytics in the mobile device reverse logistics domain. It has been a journey that has taught us so many valuable lessons on Data Monetization. But one key thing that has never changed is our customer centric focus on building and enhancing Device IQ. The abilities to find the value of data, secure a niche, show your work, and read the market are all critical for a data-driven business, but the rewards, as borne out by MIT research, are more than worth it. If you’re interested in learning more about Device IQ and how it can help your business or if you have any questions on Data Monetization, contact us today.