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Technology
All Hands on Deck

The journey to becoming truly data-driven requires a concerted effort by everyone within an organization.
  • Pat Saporito
  • October 2019
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Big data, artificial intelligence and digital disruption have created incredible competition in every industry. In some cases, digital startups are the competition. In others, they have become partners in building out more robust capabilities. Data and analytics are not just the fuel but also the engine of today's business environment.

Organizations are facing challenges in wide-scale use and adoption of analytics. Often the HiPPO (highest paid person's opinion) syndrome prevails.

Almost every senior executive I've met is frustrated with this issue. Data-driven has become an empty buzzword. As in the Wizard of Oz, there's not much behind the curtain. We have analytic islands instead of an enterprise approach. You cannot be a data-driven organization without understanding what one is and what it takes to become and sustain being one.

Lack of use and adoption stem from three key areas: Culture, lack of trust in the data and ease of use.

Ease of use includes not only having the right tools but also having an easy-to-use search catalog of your standard analytics, with core corporate and operational ones clearly identified. The catalog should include metadata, or data about the data such as its source or last update. Metadata should be accompanied by a data dictionary with data element definitions, calculations and aliases, along with ease of use and a business or semantic view of the data by function.

The catalog and dictionary reinforce user understanding. However, the most important part of user trust is a data governance program. A process is needed to validate and correct questionable data. Data stewards need to be appointed as “go-to” data people. Governance needs to be rightsized depending on the use of the data. Governance that is too heavy discourages data use and reinforces personal data silos.

Ease of use and data trust are table stakes, but culture is just as important. Managers need to clearly demonstrate that they make data-based decisions starting at the top with executive management and down through operations. New employee onboarding should include a data analytics orientation and a review of key data sources, tools and standard reports.

Communities of interest for different types of users, including managers, analysts and data scientists, need to be created. Ongoing training and development for data analytics and data security should exist. Employees should participate on projects to apply and reinforce learning.

Analytics adoption and business value are goals of an analytics program supported by continuous funding and managed through a Business Analytics Competency Center or COE leader working with a senior business executive champion or chief data analytics officer.

Analytics need to be part of a company's annual planning process. Corporate initiatives should include goals, objectives, measures and actions. These initiatives then trickle down and become part of the objectives set by each department and employee. They also become part of the annual data analytics planning to include new data analytics needed to support the initiatives.

Becoming truly data-driven is a journey. It requires all levels of the organization and an organization infrastructure comprised of people, processes, data and technology to drive business value and user adoption from data and analytics.


Best’s Review columnist Pat Saporito is a partner at Digital Business Creations LLC and author of Applied Insurance Analytics: A Framework for Driving More Value From Data Assets, Technologies and Tools. She can be reached at pat.saporito@gmail.com.


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