Are you overwhelmed with the changes happening in your organization? As a supply chain manager in this digital era, chances are you are using at least some new systems, technological tools or software. And that's likely a good thing. Digitalizing the supply chain has a wide range of benefits - from quicker production workflow to increased accuracy and efficiency. But just because the digital advancements and automatic processes available to us today are helpful, that doesn't mean they can't also be a challenge.
One of the biggest effects of this proliferation of digital devices and enhanced connectivity that seems to be plaguing supply chain leaders today is the robust amount of data and information is it presenting us with.
A report published by EY revealed that as business models are becoming more digital-based, they are growing more complex and the explosion of data is becoming a source of stress for companies, Material Handling and Logistics reported. Furthermore, the source explained, while most people understand that access to more data and information than ever before can be beneficial in some ways, at a certain point it becomes less of an asset and more of a liability.
The problem with too much data
As the saying goes, "Too much of something is never a good thing." And this may be the case when it comes to supply chain data - at least the kind that is unstructured and difficult to analyze. Organizations are not wrong in assuming that data and analytics are supposed to help improve and optimize the supply chain - and they certainly can. However, given the rapid rate at which the data growth is accelerating, it is becoming increasingly difficult for businesses to keep up with it and handle it in a way that leads to any valuable insight.
Obviously, collecting robust amounts of big data is irrelevant without being able to properly organize and interpret it. And this is where machine learning and enterprise data management come into play. As Material Handling & Logistics pointed out, the supply chain leaders who uncover solutions for data standardization and analysis - and do so as quickly as possible - will be the ones to gain a competitive advantage and benefit from their digital supply chains.
By adopting a strategic approach to data management, companies will be able to obtain more valuable business insights and start asking the right kind of questions that fuel organizational success and performance. So what can you do to make that happen within your own supply chain?
Finding order in chaos
When trying to make sense out of supply chain data, the place to start is determining which problem you are looking to resolve - or what question you are looking to have answered. Spend Matters explained that focusing on data collection by breaking it down into specific segments to work toward a single objective at a time can act as a guide.
In an SAP article, Richard Howells recently offered a number of additional tips for making sense of supply chain data, including:
- Understanding where both structured and unstructured data is coming from.
- Making supply chain data accessible from any device at any time.
- Putting data in relevant and correct business context, customizing it for the particular audience it's intended for.
- Utilizing data scientists and those with similar skill sets and expertise who can help collect, manage and analyze supply chain data.
The incredible amount of data and information that is available to you can either be a blessing or a burden - depending, in large part, on the tools and processes you leverage to help manage it.