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A Guide to Data Monetization, Part II: How to Craft an Indirect Data Monetization Strategy

By: Robert Wood


In the first installment of this three-part series on data monetization, I explored three common benefits that companies achieve by leveraging data monetization strategies: enhanced existing goods and services, optimized sales and marketing efforts, and reduced costs and improved decision-making.

All three of these benefits stem from indirect data monetization efforts — efforts that are comprised of internally focused strategic initiatives. (I will cover direct data monetization in the third installment of this series.) Because formulating an indirect data monetization strategy requires taking stock of a company’s specific strengths and weaknesses, there is no one-size-fits-all roadmap for indirect data monetization.

That said, every indirect data monetization strategy must be built within a coordinated, company-wide framework if it is to establish or cement a company’s competitive advantage(s). Effective indirect data monetization does not depend on one person, one system, or one “Eureka!” moment — it is a result of the combination of focused strategy with company-wide investment and commitment.

To ensure this combination produces the desired results, a company should take the following four steps when crafting its indirect data monetization strategy:

1. Determine core competencies and use them as competitive advantages.

First and foremost, make data-informed creativity a priority. Do you have strong, creative product owners? Will giving them access to new data help them augment existing products? Is there data they wish they had that would help them augment existing products or design new products? Using data to facilitate product enhancements can drive increased sales, revenues, and profitability.

It is also important to think holistically about your data-driven insights. Do you have the ability to build a suite of advanced analytics? Are you relying on outdated business intelligence and reports? How accurate are your demand forecasts? Are you using the most accurate algorithms, models, and tools? Implementing accurate analytics across your company’s processes can reduce production, storage, and labor costs.

Finally, be sure to pick low-hanging fruit first. Once you determine your company’s core competencies, identify specific opportunities for positioning these competencies as competitive advantages.

2. Identify strong leaders capable of facilitating organizational change.

Nearly every data monetization effort will cause some degree of disruption, not least because successfully executing a data monetization strategy must be a company-wide endeavor. As such, it is important to identify strong leaders within your organization who are capable of facilitating the necessary changes both within distinct departments and across your company at large.

This typically requires a concerted effort to create an atmosphere of organizational change management. Your leaders must dare to achieve greatly, even if doing so involves spurring significant cultural change at the most fundamental levels of your company.

3. Put the right data and tools in important employees’ hands.

Individuals who directly interact with customers serve as a vital feedback loop. They understand your customer’s use of your product, the value the product delivers, and the areas in which the customer believes the product falls short of expectations. It is essential to put these employees in a position to not only assess, but address customers’ needs. Among other things, this means giving your customer-facing employees the data and tools they need to identify problems, escalate them to higher levels as needed, and resolve them efficiently.

It is equally important to get the right data and tools into the hands of those responsible for production processes. By utilizing better forecasting methods, business intelligence, and cost data, these employees can optimize production processes, reduce costs, and increase throughputs.

While data security is of the utmost importance — and, to be clear, you should not feel obliged to make all your data available to every employee at all times — data that is kept entirely inaccessible ends up adding no value to your company.

4. Plan for the future — in terms of both technologies and people.

The most successful indirect data monetization strategies are those that consider long-term opportunities in addition to short-term opportunities. To that end, be sure to identify the requisite systems and technologies for meeting your strategic objectives both now and down the line as early as possible.

Additionally, invest in finding, recruiting, and deploying team members who are capable of cleaning, structuring, analyzing, and incorporating data and analytics in a way that scales up your capabilities. Note that, due to longstanding labor market imbalances, hiring data specialists often places stress on recruitment teams, so it is critical to plan accordingly.

5. The Case for Indirect Data Monetization

Despite the fact that indirect data monetization is often an excellent way for companies to begin realizing increased value from their existing datasets, many companies continue to significantly underestimate the financial value of these types of strategic efforts.

Granted, the extent of this value will depend on the limits a company faces in terms of its technology, its data science talent, and the quality and accessibility of its data, but by following the four steps outlined above when crafting its indirect data monetization strategy, any company has the potential to drive increased value across its operations.

This is part two of a three-part series on data monetization. Read part one and part three.

Robert Wood


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