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Three levels of data alignment: making data assets work for you

Authored by Nathan Olson

It should come as no surprise that the data an organization uses and owns is one of its most crucial resources. Whether the organization is selling their data as a product or leveraging it as a source of revenue – they’re monetizing the data and that data plays a central role in how the organization operates. Despite the importance of data, many businesses don’t value it as a proper asset and often don’t have the same standards that they do for their physical assets. If companies begin treating data as an asset, they’d enhance their business value for their clients.

If you can’t measure it, you can’t manage it

To properly maintain and utilize data assets, it’s necessary to know what there is to manage. The default practice at most organizations is that every department owns their own data, which is rarely shared, across the company. However, many companies are moving towards utilizing a data catalog to inventory what assets exist.  

By cataloging data, an organization can identify areas of redundant data, work to fill data gaps, and increase their efficiency. If the quality of the data is important to the organization, then having a catalog of data assets will give the organization the infrastructure to implement data quality practices across the organization.

Data cataloging can also improve security and compliance standards. Both security and compliance practices are often set at the company level, but left up to each department to implement. With a data catalog, “companies can establish enterprise-wide security privileges and governance rules from a single control point closer to the point of business data consumption and directly linked to data delivery.”1 This allows for the implementation of governance standards and the ability to leverage metadata to demonstrate the value.  

Levels of alignment maturity

From and IT or data perspective, improving quality, security, and compliance are likely already priorities. The operations side may see the value in these things but feel the need to prioritize them against other business projects and goals. However, the management of the data is not a competing priority to other projects, but the main enabler to improve the success of those projects. Every organization has a different level of maturity in terms of the alignment between IT and operations, the maturity of this alignment can be grouped into three levels:

Level 1

At level 1, IT and operations are seen as separate departments, often with competing priorities. This could be called Level 0, because at this stage of maturity, there is practically no coordination between IT and operations. There is often conflict between these two, which detracts from what either team would be able to accomplish on their own, let alone working together. For example, an organization within this maturity had overwhelmed their IT department with requests, causing the relationship between operational department heads and IT to be unreceptive. Many department heads spun off their reporting leads to only handle their own team’s data management, resulting in no company-wide data communication or standards. This put an invariable limit on what the organization was able to accomplish.

Level 2

At this level of alignment maturity, operations and IT are still treated as separate, autonomous departments, but they work well together. Operations makes formal requests, which are considered and prioritized by IT. However, the planning and budget cycles between the two don’t sync up, and ultimately each team is focused on fulfilling their own role.

This level of maturity often forces teams to be reactive, instead of proactive. An example of this level of maturity comes from a company that decided to supply customers with progress reports of how well they were utilizing the company’s software. The operations team would often communicate sudden changes, while the development team and the data team would be scrambling to implement those changes. This resulted in a lot of rework when deliverables didn’t meet the operations team’s expectations. The lack of coordinated planning led to miscommunication between the development and data teams, which then led to data gaps and inconsistencies.

Level 3

At Level 3 alignment maturity, IT and operations function as two roles on the same team, even if they are technically different departments. IT has a good understanding of the direction that operations is going, and operations understands the available data assets, capabilities, and constraints of the IT team. This level is what all organizations should aspire for; however, it requires both cultural buy-in and practical process steps to enable:

  • Unified planning – IT and operations need to function on the same schedules, in terms of planning and budget. There needs to be a recognition that IT enables the business, and both teams need to respect the others’ roles.
  • IT cost is proportional to business value – An organization needs to make a critical assessment of their data catalog. They need to justify that they’re putting their resources into the data assets that are providing the most business value.
  • Operations values data as an asset – Respect goes both ways when IT and operations are aligned, and that requires operations to understand their data assets. These assets need appropriate resources to manage quality and governance or they will become useless.
  • Operations brings IT into vision discussions – If an organization wants to leverage its data assets to accomplish its business goals, it must involve IT in those discussions on goals. This means bringing IT into the discussion at a high level.

What level of alignment are you at?

An organization’s data assets are arguably the most valuable resource it has, so they need to be treated with the same standard as their physical assets. This starts with having a culture where IT is managed with a high degree of quality and standards that is focused on the business’ goals, and in turn, operations invests in the maintenance of their data assets. A mature, data-driven organization must have a culture of aligning business goals to data assets and take practical steps to enable this at all stages of planning and execution.

For more information on this topic or to learn how Baker Tilly specialists can help, contact our team.

1. Flores, Wes. Take an Inventory of Your Data Assets

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