{"id":52045,"date":"2023-11-28T06:10:31","date_gmt":"2023-11-28T06:10:31","guid":{"rendered":"https:\/\/syndigo.com\/?p=52045"},"modified":"2024-01-06T00:34:07","modified_gmt":"2024-01-06T00:34:07","slug":"data-ownership-it-or-business","status":"publish","type":"post","link":"https:\/\/syndigo.com\/fr\/blog\/data-ownership-it-or-business\/","title":{"rendered":"The Battle to Own Data: IT or the Business Owner?"},"content":{"rendered":"\n
Striking the right balance of data ownership between IT and business decision-makers is essential for organizations to fully capitalize on data. Is this a challenge in your organization?<\/p>\n\n\n\n
As companies increasingly rely on data for key initiatives like business intelligence, predictive analytics, digital transformation, and improving customer experience, a crucial question arises – who should own this data?<\/p>\n\n\n\n
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Many organizations have defaulted to IT ownership since IT teams have traditionally owned the systems where data reside. But the new reality is that with data playing a bigger strategic role, business leaders need more involvement in data strategy and governance with IT from the start.<\/p>\n<\/div>\n\n\n\n
Who Owns What? Here\u2019s What the Experts Say<\/strong><\/h2>\n\n\n\n
We invited data consulting experts from our alliance partner Object Edge to share their thoughts and first-hand experiences with data ownership challenges. A digital consultancy, Object Edge has implementation expertise with master data management, syndication, business intelligence, and analytics.<\/p>\n\n\n\n
They have seen first-hand that there is still confusion in many organizations over who should mandate and govern data initiatives. Legacy companies tend to default to IT ownership, while digital native companies often empower business units more. As a result, many companies find themselves without the infrastructure necessary to achieve business measurements and are now struggling to figure out how to create it.<\/p>\n\n\n\n<\/figure>\n\n\n\t\t
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Case Study<\/strong><\/h4>\t\t\t<\/div>\n\t\t\t\t\t\t
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Object Edge worked with an industrial manufacturer that didn’t fully know how to articulate its data strategy. In working together, they quickly recognized it was critical to understand who would own key data assets and what those assets were.<\/p>\n
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As part of an ERP consolidation project led by IT, they tackled this question head-on. While an IT-driven project, their executive leadership focused on involving business stakeholders from the start and getting their input on decisions.<\/p>\n
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Object Edge\u2019s approach was to create and document processes for data ownership and decision-making. This meant that IT and business both bought into the process. As a result, when they later launched larger data initiatives like a master data program, they already had solid processes for data ownership and governance in place involving both IT and business.<\/p>\n\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\n\n\n
The Downsides of Exclusive Data Ownership<\/strong><\/h2>\n\n\n\n
Exclusive IT ownership of data can hamper businesses\u2019 ability to leverage data for strategic business objectives beyond keeping core systems running. When IT fully owns data programs, there is often less accountability to the business side, which means less agility for business owners to respond to time-sensitive business issues. This also leads to something informally referred to as \u201cbeg and borrow,\u201d meaning that business decision-makers are begging and borrowing data from other teams because the data they want is difficult to access.<\/p>\n\n\n\n
On the flip side, exclusive business ownership of data causes problems too. There can be ambiguity in how IT systems and infrastructure will enable the data needs of the business. A hybrid shared model between business and IT works much better.<\/p>\n\n\n\n<\/figure>\n\n\n\n
Tips for Shifting to a Business-Friendly Data Ownership Model<\/strong><\/h2>\n\n\n\n
Here are some starting points to move in the direction of a more business-focused data-ownership approach. <\/ins><\/p>\n\n\n\n
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Improve data literacy across your organization. This enables more effective use of data by business decision-makers.<\/li>\n\n\n\n
Win executive sponsorship to address pain points. This is a key driver of change for data ownership transitions. A top-down strategic vision combined with bottom-up recognition of need gets initiatives moving.<\/li>\n\n\n\n
Designate data leaders such as a Chief Data Officer to help structure and own these conversations. This works best when there is already enough data inventory and vision in place to leverage it. They can drive literacy and connect objectives to data improvements.<\/li>\n<\/ul>\n\n\n\n<\/figure>\n\n\n\n
What We Learned<\/strong><\/h2>\n\n\n\n
The key takeaway from this discussion is that neither IT nor business should own organizational data in isolation. Instead, companies need to construct a shared data governance model that balances both IT and business involvement.<\/p>\n\n\n\n
On the IT side, technology teams play a crucial role as data custodians. They manage the underlying data infrastructure and systems, ensuring smooth and secure technical operations. However, IT cannot be handed full control over data strategy and priorities.<\/p>\n\n\n\n
On the business side, business units need to drive the data strategy by defining objectives, pain points, and use cases. However, the business side lacks the expertise to fully oversee technical data management.<\/p>\n\n\n\n
This is What Success Looks Like<\/strong><\/h2>\n\n\n\n
The companies that succeed with data are those that reject “one-size-fits-all” data ownership in favor of tailored partnerships between IT and business.<\/p>\n\n\n\n
By dividing and conquering responsibilities, with IT focusing on custodianship, and the business side focusing on strategy and ownership, companies can break down these silos for a more collaborative process. This enables agile data sharing and governance across the organization.<\/p>\n\n\n\n
This balanced model is essential for data to flow seamlessly between systems and teams. It provides accountability on both sides to keep data initiatives tied to business KPIs. It also allows organizations to fully leverage data as a dynamic asset capable of driving competitive advantage, not just a fixed byproduct of IT systems.<\/p>\n\n\n\n
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