Big data benefits for supply chains

Big data offers invaluable insight for supply chain management that can boost efficiency and cut costs to offer a powerful competitive advantage.

On April 23, 2019

Supply chains generate big data, or massive volumes of information collected from many different sources. When it is processed and analyzed correctly, it can boost efficiency to offer a powerful competitive advantage.

Invaluable insight for supply chain management

Big data offers invaluable insight for supply chain managers, mainly to improve network planning, optimize delivery, enhance risk management and implement demand-based management.

“Big data can significantly improve supply chain operations, but it is not a magic solution. It requires companies to transition the way they do things, and it must be adopted as a company-wide culture to add real value. Data strategy has to be a top-level priority among business objectives to enable investment,” says Osman Bahadir Demirdis, Supply Chain Project Manager at FM Logistic.

Building a big data solution

To take advantage of the data opportunity, a brainstorming session with representatives from across the company should be the starting point to set priorities and get full cooperation.

Osman Bahadir Demirdis explains: “Collective input should guide the data strategy and make sure the end result successfully responds to the specific needs of the business. Goals, rules, processes, sources and any other key components should be clearly defined in the beginning.” Creating a partnership with an external expert for support can help during this phase.

Data integrity is fundamental

Data integrity is fundamental, and all sources must provide clean, consistent and timely. To achieve this, close contact with operations is needed. If data is being generated by external sources, by customers or partners for example, then powerful data quality modules can be a solution. “Technology-generated data minimizes error risk, but humans are indispensable for validating the final result and finding ways to improve the system,” highlights Osman Bahadir Demirdis.

Careful consideration has to be given to the creation of a data architecture model to analyze, use and share the information. “Big data is not a traditional data base. It has to be customized according to the strategy. Once you have quality data, the key is to convert the information into actionable insights to drive efficiency throughout the supply chain,” notes Osman Bahadir Demirdis. Technologies are available to help with this step, such as Google Cloud Platform (GCP) modules.

Data science and a global vision

Integrating data into business demands a range of skills, involving both operational and technical expertise. Supply chain managers need to adopt a data science way of thinking to gain a global vision of what might be possible with big data analytics.

Current business processes also need to be evolved to best implement big data as well as navigate any issues. Osman Bahadir Demirdis says: “To ensure the security and efficient use of sensitive data, access needs to be restricted according to specific user profiles, which can be a challenge to manage.”

He adds that privacy laws, such as the European regulation of data protection (RGPD), which limit the amount of time information can be stored, can be another barrier to overcome. When the architecture is designed, it is important to register these regulations as key measures.

data science

Putting data into action

FM Logistic is using big data to improve supply chain performance and develop innovative service solutions. “A pilot project is underway to optimize transportation operations, using big data to centralize multiple loading points, systems and operators. Pre-process improvements are suggested based on analytics, and a Super User dispatches the best solutions, which are then implemented by individual operators for cost savings and reliability,” says Osman Bahadir Demirdis.

Two other projects are also being tested. The first is a dynamic client service pooling solution that optimizes fulfillment rates, cuts costs and reduces carbon emissions. The second is an interface that monitors warehouse performance on a daily basis by gathering information from multiple sources to generate savings.

Improving decisions across the supply chain

Businesses are expecting more and more from supply chains. The ever-growing volumes of information presents endless possibilities to improve decision making for all activities across the supply chain. In fact, the global supply chain analytics market is expected to hit a value of $403 billion in 2023, marking growth of nearly 41% from $52 billion in 2018.

Industry leaders who want to build the best supply chains know now is the time to take advantage of big data analytics to cut operational costs and increase flexibility in the future, ensuring they remain innovative to stay ahead of competitors.

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