Future of Operations
Use data-driven operations
to improve decision-making
The Future of Operations
Today, operations tends to be hierarchical and highly dependent on local expertise, rigid processes, and reactive decision making that is undermined by errors in the chain of communications. Operations constantly makes trade-offs between different objectives, including efficiency, productivity, quality, safety, reliability, and sustainability.
Guided by a digital-first strategy, organizations will become flatter, with a single source of truth as they leverage operational data to optimize and drive better, more timely decision-making, which can be defined as data-driven operations (DDO). With better, more contextualized data that is widely accessible, organizations will gain more visibility and predictability of operations, empowering employees to make decisions rapidly and confidently with less oversight.
Improving Decision-Making Through Data-Driven Operations
With better, more contextualized data, organizations will gain more visibility and predictability of operations, empowering employees to make decisions rapidly and confidently with less oversight.
Cloud usage has become a key indicator of how effectively organizations leverage operational data to drive decisions. IDC survey data shows a clear connection between putting operational data in the cloud and improved decision making. A scalable technology management approach that is capable of managing multicloud, hybrid deployments while addressing the need to vet application updates and technology changes made in operations – on both a technology and organizational level – will set enterprises up for success in the Future of Operations.
Effective operational data management is essential to achieving operational excellence. Modern operational data management strategies enable organizations to realize the full value of advanced data analysis tools, helping draw out new insights while fostering collaboration. Organizations that commit the necessary resources to enhancing their operational data management processes will position themselves for success well into the future.
The promise of artificial intelligence (AI) and machine language (ML) initiatives has led many organizations to simply throw all data into repositories while assuming it can be effectively and efficiently analyzed without adding context and meaning. But as IDC’s survey data reveals, most of these undertakings have fallen short.
OT has historically been the driving force for improvements in operations. Now, as traditional approaches to data and analytics reach their limits, there is a growing expectation that AI will deliver the next round of performance improvements. And,as the pressure to adopt AI within operations continues to gain momentum – driven by broader hype around AI’s successes in the B2C world – technology providers are launching AI-driven solutions to support a growing number of AI-based projects.
Future success will require approaches that recognize the unique challenges of deploying AI in an operations context. Technology-driven organizations with operational data management mastery will be well positioned to leverage AI as it matures to a point where it consistently enables more successful deployments.