Thiag Loganathan & By Dennis Kettler
Dec 9, 2020
By now we have all heard the ubiquitous and somewhat misleading new phrase “Data is the new oil”. Oil derives its value based upon the many useful and critical products created through its refinement. However, in our experience, it is not universally true that data is being leveraged effectively to create value for companies. Thus, data is the “new oil” only for select companies that have been able to appropriately define, refine and monetize. For those that aspire to drive value on their data, how and where should one begin?
To continue the analogy, similar to oil, data can be refined in many ways to deliver meaningful insights, decisions and, ultimately, value to a business’ top and bottom line. This process involves science, art, and experience to successfully monetize data. In this series, we demystify and layout a framework to understand and extract value from your data asset.
Data Monetization is a fancy way of saying, “making money from your data.” Whether your organization is a data producer, data aggregator or data consumer, you have the potential to generate new revenue streams through data monetization. This value can be achieved across a broad spectrum of analytical activities from descriptive through preemptive. Additionally, data can be leveraged across disparate disciplines: new data-driven products and services, client lifecycle management, internal cost optimization, sales funnel optimization and cross-sell/next best product to name a few. The most successful companies will monetize data in a great range and variety of activities.
Irrespective of a company’s level of data and analytical maturity or the maturity of their broader industry, there is opportunity to drive immeditiate value through data monetization. In early stages, this may come via new product offerings, product features or data-driven targeted marketing or, in later stages, via compression circumvention strategies, automation and cost mitigation strategies or disruptive services leading to new business. More specifically, we believe:
1. Leader, Strategy and Goals:
2. People, Process & Technology: We have heard this a lot, “I have old tech, the data is not all in one place, the data is not clean”. Yes, it is a challenge, and it is almost always the case when you start. But the right people and process will allow you to get started quickly while dealing with the tech and data quality constraints. So, invest in the right people with light processes before implementing hard processes and technology.
3. Risk, Consent, Privacy & Security [future article]:
Adherence to ethical, legal and compliance policies - Data protection laws, PII, PCI, HIPAA, and other regulatory compliances. In the next article, we will address this in more detail.
4. Extracting Value [future article]:
Understand your data and gaps, overlay possible value streams with restrictions and constraints to create a business plan that extracts value leveraging your data assets.
5. Getting Started and Roadmap [future article]:
This is the most difficult step; it is important, while getting started, to focus on value instead of technology. The roadmap should have incremental business and technology milestones that are achievable while setting you up for long-term success.
6. Business models and monetization [future article]:
Companies that succeed in data monetization will have multiple programs using different business models, stakeholders with varying degree of success. It is important to use MVPs and small scale pilots to prove out business models and adoption before a large scale roll-out that can become an ongoing value stream for the company.
With data privacy and security being a key factor especially with the newer consumer privacy policies such as GDPR and CCPA in place, leaders need to be cognizant of various processes and controls required to ensure compliance. In the next article we will dive into the details of the risk, consent, privacy, and security as they relate to Data Monetization.
A serial entrepreneur and expert in data/AI solutions, Thiag Loganathan uses data-driven frameworks to capture, measure and improve abstract socio-business problems to deliver incremental results fast. He is a proven leader in leveraging technology to improve business outcomes, and a trusted advisor with a career of building culture and environment for high performing teams that deliver solutions using Digital, Cloud, Data and AI with a focus on CRM & IoT.
Thiag helps government workers and U.S. constituents with modern experiences using Cardinality.ai for health and human services agencies. He also leads strategy and products for Goldfinch, a data cloud platform company, focusing on supporting businesses to use data and tech to execute updated strategies and make granular data-driven decisions in the post COVID-19 reality.
Prior to his current roles, he led DMI’s Big Data Insights Division, helping organizations turn data into profit through mobility, big data and data science, with a focus on Customer Experience and IoT.
In 2007, Thiag started Kalvin Consulting Inc., a business intelligence solution provider, and an SAP Partner, which got acquired by DMI in May 2013. During his time at Kalvin, he was named the Executive of the Year for 2011 by the Ohio North East Chamber of Commerce, for his long-term commitment to bettering the community. Thiag holds a bachelor’s degree in electrical engineering. He lives with his wife and three children in Potomac, Maryland. Whenever possible, he enjoys playing golf and tennis to keep some social engagement going.
He brings deep expertise in utilizing “enterprise data asset” to monetize, drive measurable value and differentiate. He is an accomplished leader with knowhow of “data and analytics” solution lifecycle and leveraging it to improving business outcomes.
Demonstrated experience in developing and rolling out end-to-end data driven platforms and business solutions including pricing optimization & elasticity, financial modeling, portfolio insights, loyalty programs, marketing mix, customer analytics and segmentation.
Dennis is currently the Global Head of Data Sciences, Governance and Business Development for FIS. Throughout his career, he has established Data Science as a core competency enabling transformative capabilities such as advanced data visualization, predictive analytics, and ML/AI. Ultimately, Dennis has played a key leadership role in activating data-driven decisions that have established competitive advantages in market.
In his current role, Dennis continues to lead both data sciences and data product development. He also is responsible for driving governance strategy, capital investment, and business development as a senior leader of the FIS Data Solutions Group and the Ethos ecosystem of data solutions. He brings a wealth of experience supporting many of the world’s largest retailers, corporations and payments brands for more than 10 years.
Dennis and his team are focused on driving disruption and innovation on multiple fronts, including the payment lifecycle through intelligent real-time decisions (fraud, authorization, cost and dispute), advanced consumer analytics and operational analytics.
Dennis currently holds four patents related to payments, attribution and consumer consent. The four patents held by Dennis are: