(USA and Canada) The statement, ‘All companies are data companies’, has never been truer as businesses, big and small, sit on a wealth of data. Our ﬁrst article in the data monetization series discussed the need for companies to start thinking about value creation and acceleration through data monetization. Irrespective of how mature an organization’s data and analytics strategy is, prudent data monetization will support businesses to leverage opportunities that can increase revenue, bring in more clients, and advance the organization’s growth prospects. However, concerns related to consumer data privacy are more prevalent with respect to delays in commercializing eﬀorts.
In this article, we share how businesses can mitigate such risks associated with data monetization with an informed framework.
Imagine this: ﬁve-year-old Sarah sits quietly and plays in a sandbox. She is building an intricate castle, using her small palms to shape the moistened sand into towers. The playground is a fenced, safe space for her to fully explore her imagination and learn and play in a tactile environment. Studies have repeatedly shown that consistent and predictable boundaries build trust and reduce uncertainty and anxiety. Research reiterates that boundaries improve children's creativity, allowing them to engage in learning and development by providing a structure to work in and solve problems.
What does this mean in the business context for data monetization, you may wonder. A similar framework approach to data would, on average, be more cost-eﬀective, as liabilities tend to compound in contexts sans boundaries as opposed to within deﬁned spaces. Organizations that are familiar with the legal, business, and ethical boundaries of data monetization rely on such boundaries to help them navigate and access accelerated growth. Boundaries are often seen are prohibitive but clear boundaries are not just important for safe exploration but also result in creative growth, new opportunities and innovation at the edge.
Therefore, in this brave new data world, it is prudent for businesses—those that seek to internally monetize data as well as those that intend to build business models around data monetization for other businesses—to look more closely at their frameworks.
Deﬁning a Framework 101
Now that you know why, here is how your business can deﬁne a framework that truly capitalizes on your company’s data monetization eﬀorts:
Strong internal processes
Establish a foundation by encouraging teams to track, understand, and adopt industry best practices for data monetization. This means you must have transparent and vocal leadership that advocates for regular information sharing and audits across the data, technology, policy, and business teams, which naturally creates a resilient framework.
Policy and Contractual awareness
While a full-ﬂedged Compliance and Legal team is crucial for companies at the advanced stage of data monetization, smaller businesses can set the ball rolling with basic awareness sessions with external experts and consultants to educate at least a core team. These would help create a preliminary but relevant understanding of data privacy and security policies. The next step would then be to supplement the initial sessions with regular workshops or training programs to "instill a continued state of policy awareness and norms"
An ethical approach
The organization’s leadership should champion ethics that place user rights and privacy at the center of data monetization priorities. Instilling renewed principles of corporate governance to user equity would help businesses preempt risks and remind employees of the necessary boundaries we spoke about earlier. An inherent ethical approach by business would sustain innovation with controls and data monetization with privacy.
Data Monetization: Suggested Framework
Having found the right approach, it is time to invest in building a data monetization framework for your company. Our ﬁve-pronged strategy guides businesses to execute their data monetization plans -
Businesses should establish baseline protocols that are based on internal expert recommendations and external best practices. These include legal, ethical, and technical checks for handling data. Say, your business is working with an EU client. It makes business sense to be preemptive and invest in tools to align with provisions of the General Data Protection Regulation (GDPR).
An ongoing process to analyze the eﬀect of existing and proposed regulation on data monetization eﬀorts would equip businesses for impact. Analysis on user trust and experience can be valuable.
Analytics without groundwork is like having seeds and being unable to plant them. It is essential for teams to venture beyond analyses and into quantifying the impact of monetization policies. This is where you should create an unobstructed view of the ﬁnancial, legal, ethical and detrimental impact, if any, on the business goodwill or market trust.
Once you have quantiﬁed the impact, the next crucial step is to respond to it by either iterating data monetization practices or plans based on the assessment, or by instituting new measures (for instance, improved systems for storing personal data, cybersecurity, accreditation for data handling) to mitigate liability.
Data auditing is often misunderstood as a complex process by companies. Businesses should focus on implementing basic auditing controls, with the guiding principle of ‘trust but verify.’ For instance, even the leadership asking the right questions at opportune times can be an eﬀective data auditing tool. Businesses can then build on this by adopting a mechanism that works by instituting ongoing legal and technical controls which, in conjunction with the associated control logs, enhance auditability. Simply put, once clear guidelines have been established, audit is a natural next step to verify their implementation.
In this article, we propose a framework for data monetization policies, encouraging periodic review, probing, and iteration. Businesses should foster huddles of people with complementary strengths, bringing together eclectic teams of executives, data scientists, and risk mitigators to ask the right questions and enhance monetization opportunities.
While the beneﬁts of data monetization are quite clear for business, we should not overlook the value of these activities for our clients and consumers. It optimizes costs, increases outreach, and contributes towards better and improved user experience. As businesses march into the inevitable path towards data monetization, it is preparation and a vision to invest in the right frameworks that will ensure success in the long run.
Implementation of this framework will allow for companies to use data for personalization and outcome improvements while respecting privacy, being transparent, and pushing the boundaries allowing for innovation at the edge. We will explore innovation at the edge in our next article.
About the authors:
Thiag Loganathan is the CEO and Co-Founder of Cardinality.ai. He is a serial entrepreneur and brings deep expertise in data/AI solutions and data-driven frameworks. He previously led DMI’s Big Data Insights Division. Thiag also founded Kalvin Consulting in 2007, a Data Analytics solution provider, and an SAP Partner, which was acquired by DMI in May 2013.
Dennis Kettler, Global Head of Data Science and Data Products at Worldpay. He has 15+ years of experience in data analytics, having worked as the senior manager in the analytics team at Vantiv, Kroger Personal Finance, and Macy’s. Dennis‘ expertise includes, big data analytics, pricing, business intelligence, and data strategy for customer and retail insights.
Akshara Baru is a lawyer working at the intersection of governance, technology, and policy. She has a Master's in Public Administration from SIPA, Columbia University. She helped with research and brought this article to life.