If we look at the world of finance, it’s normal to be upfront about the fact that poor data quality has a direct, negative impact on performance. As a result, traceability and validation processes are a top priority, to ensure optimal data quality.
In the world of IT, though, shouldering responsibility for ensuring good quality data is a hot potato. It’s seen as an intimidating task, which people can be keen to avoid facing head-on. Yet each time an organization introduces a new technology or tool, a new data source is created. One that needs to be governed with a clear, watertight framework and data model.
Introducing these new technologies and tools will be central to the process of transforming your IT organization, as will the data developments they bring with them. Below, we’ll take a look at how to ensure data plays the right role as you transform your enterprise IT.
Data in digital transformation: Quality is always the top priority
A truly data-driven organization needs multiple roles in place to ensure good data quality. Handily, there’s no need to reinvent the wheel here. At DXC ServiceNow Strategic Business Group, for example, we leverage the IT4IT™ framework. It offers a proven process for shaping strong and mature data model foundations, especially when used in combination with ServiceNow. In addition, organizations are able to cherry-pick with which IT4IT and ServiceNow capabilities they want to start their digital transformation, adapting its potential to their readiness and budget. This offers organizations a ready-made, traceable framework for constructing their data foundation. One that’s still flexible enough, though, to cater to their specific requirements.
If we look to DevOps as an alternative, the value of this traceability becomes clear. With DevOps specialists bringing their own toolsets to their work, it’s tough to keep track of what data each new tool is storing, and where — particularly for support teams responsible for IT Service Management. Are there data overlaps or gaps? Potential risks? Do we still have a proper overview of all the changes made to an application? If an incident or business outage occurs, this traceable knowledge becomes especially crucial. As a result, no matter the cutting-edge nature of the technology, the performance it might offer, or its appealing capabilities, tracking precisely how it’s using data needs to stay your organization’s top priority.
Choose your data wisely: Utility is key
To generate maximum value as rapidly as possible, the role of data in digital transformation comes down to thinking in use cases. Far too often, organizations bring in experts to clean up their data, ensuring it’s secure and usable. After significant time and expense, though, nobody within the organization touches the data — it’s simply not what they need to deliver their work. To avoid this, we always take a use-case-driven approach to our clients’ data usage. Utility drives the entire process, leading to pragmatic dashboards that deliver what employees need to know.
This approach also maintains clarity regarding the business rules and metrics you introduce. For useful data-driven output, less is more. Setting up a Common Data Service Model with ServiceNow, for example, might aim to include 15 - 20 data objects. Yet we’d begin with just 1 - 3, creating a value-delivering data backbone. Given we implement traceability for hosting costs from this first stage, your development team retains clarity and control. From there, you’d be primed to build up your data foundation utilizing IT4IT’s ready-made, adaptable model.
Data and digital transformation: Align data strategy with organizational context
Managing, securing, and using data to optimize business decisions through digital transformation isn’t just about bringing in a solid data model. It starts with analyzing which data sources your organization currently has, as well as the tools it’s using.
The data sets at play also need to be clearly defined within your organizational context. What do your teams and departments mean when they discuss each data point? The IT4IT framework delivers on this. It takes care of the busywork of data definitions while seamlessly catering to your organizational context, building this out on the enterprise architecture level. The result? A single definition source to refer to as you populate new data objects, prioritizing clarity and organizational alignment.
Build in governance from the start
Especially when it comes to big data in digital transformation, governance is vital. Appointing data owners and stewards enables you to create processes in your organization to maintain data transparency and traceability.
At DXC ServiceNow Strategic Business Group, after implementing a new capability, creating new key data sources, and handing over ownership, we also support clients to create these governance roles and processes. We deliver workshops and training material for clients’ data owners and stewards on managing the nuances of their organization’s data objects. With ServiceNow’s self-service functionality, they can then easily update data objects as required, responding to requests related to governance, traceability, and security from across business units.
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