- Over 80 percent of current warehouses operate without any automation, meaning supply chains and their data are left unoptimized.
- Increasing data transparency will display any constraints allowing you to develop suitable solutions.
- With over 80 percent of supply chain disruptions caused by human error, employing intelligent software to take over monotonous daily tasks will ensure they are finished faster and without mistakes.
by Sunil Kardam
It is fair to say that the global logistics network has been having a rough time over the past few years, and the supply chain crisis is expected to continue well into 2023. However, it is not all doom and gloom, as there are ways that logistics companies can stay ahead of the curve.
While every company aims to work at full capacity, over 80 percent of current warehouses operate without any automation, meaning supply chains and their data are left unoptimized. Poor supply chain data quality poses a challenge for most organizations, compromising operational effectiveness, regulatory risk compliance, and stifling logistical agility. The effects of insufficient and undeveloped data can have far-reaching and long-term consequences for an organization, from inadequate fleet management to poor financial health.
An effective data strategy is an enterprise framework that helps reduce the unpredictability of supply chains that originate from various external and internal sources. Here are some ways your company can leverage modern technology and benefit from an effective supply chain data strategy:
Discover Your Company’s Pain Points
Implementing a data strategy sounds like a simple fix for all your logistical problems, but knowing where to start can be tricky. One recommendation is to begin with a Data Maturity Assessment (DMA).
A DMA analyzes how an organization utilizes the data they produce and evaluates various factors that affect the quality of analytical data and, consequently, data-driven decisions. It assesses the current level of data maturity within the supply chain that can serve as a baseline for improvements.
Once this baseline is noted, companies can integrate Supply Chain Management (SCM) applications that use advanced analytics to predict issues before they occur instead of locating and addressing them afterward. The software can help synthesize data, reduce supplier risks, identify single points of failure and bottlenecks, build resilience, and sync manufacturing processes and demand planning with supply.
Analyze Your Operations For Some Quick Wins
Once you have extracted your company’s data through an SCM application, a data strategy roadmap is a next step. This usually consists of a data strategy business case, effort, cost and times estimates, and an agile schedule of each phase with the overall timeline.
The map analyzes the priorities of your supply chain and identifies quick wins to ensure management can start seeing value quickly. Increasing data transparency will display any constraints allowing you to develop suitable solutions. This all contributes to building a data-driven supply chain. Creating a roadmap can be completed in-house with the help of an external toolkit and often takes between four and seven weeks to complete. This will create positive momentum for your data overhaul.
Employ the Power of AI
Most modern SCM applications push forward effective supply chain strategies using artificial intelligence (AI). An article by McKinsey reported that early adopters of AI-enabled supply chain management improved their costs by 15 percent, inventory levels by 35 percent, and service levels by 65 percent when compared to slower-moving competitors.
By extracting all the untapped data your business has accumulated, AI and machine learning can make accurate forecasts and decisions for the future. Technology helps optimize and increase transparency in areas including logistics and distribution, planning, production, and procurement. Additionally, with over 80 percent of supply chain disruptions caused by human error, employing intelligent software to take over monotonous daily tasks will ensure they are finished faster and without mistakes.
There are many supply chain data and AI solutions on the market designed for differing needs and business areas – picking the correct one for your company may seem daunting. However, implementing modern innovations into processes can increase overall productivity, reduce costs, and secure investments by providing a data-driven business case.
In a recent survey from Ivalua, 84 percent of manufacturing executives stated that modernizing supply chain operations is a strategic priority. Do not get left behind — with so many logistical advantages, it is time to implement your supply chain data strategy.
Sunil Kardam is the Analytics Head of Supply Chain & Logistics at Gramener.