Exponential data growth is a fundamental problem that is continuing to overwhelm most businesses.
EY’s report, “Digital supply chain: It’s all about that data,” explains that new digital business models are increasingly more complex, including an entire ecosystems of data.
“The bloom is off the rose when it comes to the ‘store everything’ standpoint. People are starting to realize that keeping too much data is a liability, not just an asset,” explained Paul Brody EY Americas Strategy Leader Technology Sector.
Here are a few key points from the report :
Managing the data growth dilemma: The growing tsunami of data is both a boon and bane to businesses in the digital age. Limitless oceans of data, often reflecting customer experience as it happens, have the potential to remake supply chains and business models. These models can and should be more efficient, productive, flexible and responsive. But right now, data is a mess. The current period of hyper data growth leaves most companies in a position where their ability to uncover business insights is effectively hidden within an increasingly complex and often unfathomable amount of data.
Unprecedented data growth: Winners and losers in the big data era will be those best able to rapidly cull relevant insights out of enormously complex and fast-growing datasets. But rising data complexity presents an existential challenge for supply chains.
Supply chain, disrupted: Out-of-control data growth can obscure, rather than reveal, business insights needed to drive digital-age supply chains — but a growing consensus shows how to avoid that trap and manage growing data.
Supply chain, advanced: Machine learning can significantly accelerate “time to insight,” but it is no substitute for the hard work of enterprise data management strategy development and data simplification.
Supply chain, horizon: IoT and blockchain technologies promise benefits potentially greater than the cloud-mobile-social-big data technologies that supply chains are grappling with today.
The report concludes that companies must act quickly to take control of data growth, complexity and chaos. That includes focusing, simplifying and standardizing data analysis through an enterprise data management strategy, and exploring the range of possibilities afforded by machine learning, IoT and blockchain.
"Unmanaged, that complexity becomes a barrier to innovation and inhibits our ability to derive meaningful insights and, in fact, becomes a barrier to achieving the automation and efficiency we desire,” said Dave Padmos EY Global Technology Sector Leader Advisory Services. “ To seize the full potential of digital, companies must develop data strategies, and better information and data management discipline, and start asking better questions.”
