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Data fabric
Transplant connective tissue into your supply chain for greater agility .
By Mark Holmes
Adapting fast to events and trends such as energy-price shocks , production shortages , or sudden changes in consumer demand , has become a critical capability for supply chain organizations . Our world is far more volatile , and organizational success requires greater levels of agility than ever before .
It is about more than minimizing disruption – it is about the ability to adapt faster than the competition to optimize the supply chain more intelligently and consistently to maintain resilience and increase revenues .
The problem for most large organizations now is they have increasingly complex supply chains . Many organizations have 20 or 30 applications covering the management of transportation , orders , warehouse operations , and yard movements at manufacturing plants or depots . Increased agility requires the ability to connect enterprise applications and gain a single source of truth from their disparate data , which is very difficult without a purpose-designed connective tissue to harmonize it all and make it fit for analytics .
Supply chain digital maturity
The reality for most organizations is that a faster , more dynamic supply chain requires a certain level of digital maturity that is much farther on from where they are .
If the first level is about foundational architecture and connectivity , the second level of maturity is where an organization has achieved end-to-end visibility , automation , and smart asset management . The third level is where greatest agility is achieved through access to predictive capabilities and the introduction of automation into decision-making . It enables greater collaboration and integrated planning and adaptive orchestration , preferably through a control tower .
Fully optimizing a supply chain at this level , with near-real-time predictive and prescriptive insights demands AI and machine learning ( ML ). This is how organizations accelerate the speed and quality of decision-making at critical moments . Analysts at Gartner expect that by 2026 , 50 percent of supply chain organizations will use ML to augment decision-making .
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