There’s been a big change in the way software decisions are made. Today more than ever, various departments, divisions, and even teams are choosing what software to use without the involvement of IT. And in companies where IT departments continue to be the single point of sourcing for software and technology, innovation is focused on finding the right solution at the right time to meet the goals of the business. Regardless of who clicks accept, signs the contract, or shakes hands, there is an undeniable trend — organizations are seeking an increasingly diverse software portfolio to run their operations, reporting, compliance, and other areas of business. As a result, setting and enforcing the policies of data is a unique and increasingly difficult challenge.
ENSURING EFFECTIVE TRANSFORMATION
Organizations bring in new software for a variety of reasons — to automate processes, provide insight, decrease costs, increase profit, ensure compliance, or achieve some other goal that drives the business forward. And the success of any new software product depends on the data that software uses. At its essence, new software is a form of digital transformation — and data transformation is needed to get the right data into the new system and ensure the data is business ready. This involves not only moving data from one data store or database to another vendor, but also transforming the data to unlock the benefits of the desired transformation.
Let’s take an example from the world of Human Capital Management (HCM). Many organizations use a subscription to a cloud-based HCM software platform as the compelling event to reorganize corporate structure. This type of reorganization is a business problem that’s led by technology and supported by data. As business goals, technology, and data come together, these organizations transform themselves to operate in a digital economy. Without an effective data transformation that aligns with technology and goals, the promised transformation will fall short of expectations.
COORDINATING DATA ACROSS SYSTEMS
As a new software and data landscape starts to take shape, the techniques used to govern and steward the data across that landscape must evolve. Those pieces of data that have significant cross-cutting concerns and impact will need to be managed and governed centrally, while other types of data that are shared among a limited number of systems and processes must be governed in a way that impacts only those systems. However, no matter how many systems a piece of data touches, that data has the opportunity to be shared and used in systems that drive insight, engagement, and design.
In order to maximize the business value of the data stored and shared between these systems, the data needs to be governed and stewarded in a way that promotes an overall set of business goals and initiatives. The traditional techniques of master data management and ad-hoc stewardship will often be insufficient to manage data in this type of environment. To ensure that the right policy is enforced at the right time, businesses will instead need strategies that drive data governance as a business-focused and business-enabling corporate function tied directly to data-level stewardship activities.
SETTING AND ENFORCING POLICIES
My family and I recently went on a road trip from our home in Atlanta to Massachusetts. We drove through nine states in just a couple of days. In order to reach our destination as quickly and as safely as possible, we adopted two policies that governed our trip: observing the speed limit and passing on the left. Each state we drove through enforced its traffic policies differently — using police cars, planes, and speed-monitoring cameras — depending on what made sense for the budget, topography, and resources of that state. However, what allowed us to arrive quickly and safely was each state’s close link between its traffic policies and the enforcement of those policies.
Much in the same way, a close link between the establishment and enforcement of data policies in a landscape that combines new terrestrial and cloud-based systems is crucial to achieving an organization’s business goals. Each company must set policies with these goals in mind, and must implement an enforcement technique that’s based on location, budget, and resource availability. As more systems are brought into a landscape, these decisions become more varied and complex — and the organization needs an agile strategy that’s focused on the business and supported by forward-thinking data governance and stewardship tools and techniques. It’s essential to engage the business early and often as they own the data, support the innovation that Move to Cloud brings, and ensure that data can be protected, valued, and leveraged for competitive advantage.
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