Products built by aerospace and defense companies are highly engineered and sophisticated, which means they’re often complex. That’s not a bad thing. But they’re also complex in ways that are undesirable. Products and their constituent parts are tracked in dozens of systems –from design to manufacturing to maintenance — which can result in an average of 26 different reference numbers for each part.
The drive to digital transformation is helping A&D companies recognize that situations like this, which arise from a lack of governance and the absence of an enterprise-wide data strategy, have created substantial costs and risks that have to be addressed to realize the full benefits of digital transformation.
That’s especially true for companies that want to establish a “digital thread” for products and parts throughout their systems. The ability to follow any part throughout the A&D value chain (design, manufacture, service) by following a single digital ID will help A&D companies recognize tremendous cost savings. A digital thread also provides a glass pane for status, reduces rework and errors, improves security, and helps manage compliance and regulatory issues with greater efficiency.
That sounds great. But the key question for many companies remains: How do you get started with an endeavor like that? Many organizations fail to prioritize defining a data strategy on the grounds that it’s either a case of “boiling the ocean” or else an “infinity project” that will deliver little value.
A few key points can help your company move toward a data strategy that allows you to pursue the rest of your digital transformation agenda.
1. Make an affirmative decision to manage your data.
All companies make decisions about how they engage with, operate on and leverage their data — whether at an enterprise or project level. Even if a company has no formal data management policy, that in itself is a decision, albeit one that leads to the situation many companies find themselves in today. On the other hand, companies that form a holistic point of view in adopting an enterprise-grade data strategy are well positioned to optimize their technology investments and lower their costs.
2. Establish executive sponsorship and governance.
Sustaining a successful data strategy requires alignment with corporate objectives and enforced adherence. As corporate objectives evolve, so should the data strategy — keeping up not only with how the business is operating, but also with how supporting technologies and related innovations are maturing. This means including representatives from all the domains that are involved. It also means assigning someone with the authority to resolve conflicts between groups. This is a key element to helping federate data across silos and moving to a data hub approach, thus eliminating the need to maintain 26 different part numbers for a single item.
Sustaining a data strategy also means making a specific investment in personnel. Companies that embrace the constructs of a data strategy often define dedicated roles to own these strategies and policies. This ranges from augmenting executive and IT staff with roles such as chief data officer and chief data strategist, respectively, to expanding the responsibilities of traditional enterprise data architects.
3. Get started by instituting good data management practices in smaller programs.
Success demonstrate the value that data management can deliver at a small scale and what it could potentially deliver at the enterprise level. Applying an Agile methodology, which continually demonstrates short bursts of success, will help gain momentum (like a snowball rolling down a hill) and organizational acceptance.
As with any business or technical process, a data strategy has its own lifecycle of continual evolution, maturity, change and scale. But the benefits it makes possible—for example, the ability to construct a digital thread for products and parts—will far outweigh the investment that’s required.
For a thorough view of the process that’s involved in setting digital strategy, read the whitepaper Defining a data strategy by my colleagues, Aleksey Gurevich and Srijani Dey. It offers a concise view of the components of a winning data strategy as well as the steps needed to implement, maintain and evolve it.
