A business-contextualized data approach is crucial for boosting supply chain visibility, especially during downturns. With increasingly complicated and globally integrated supply chains, a lack of appropriate information may cause poor management and, as a result, bankruptcy.
One of the most prevalent causes of this is a lack of visibility, which can lead to incorrect forecasts, troublesome decisions, delayed products reception, and other supply chain hazards.
According to a report, just 21% of purchasing executives grasp the difficulties of lack of visibility in the supply chain, which becomes even more crucial when the entire chain is struggling to ensure output and satisfy input demand.
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What to know before building a data strategy
Businesses were obliged to expedite their digital transformation efforts and adopt digital initiatives at a never-before-seen pace in a year of unforeseen setbacks.
However, before generating the desired insights, a data strategy that maps business objectives and addresses the requirements of the business must be developed. This requires knowing precisely what details should be collected and trusting the sources of this data.
It is important to answer the following questions: What is the goal of developing a data strategy? What are the company’s goals? What are the expected insights? What data is required, and who has access to it? Which tools should we use?
The first stage in developing a data strategy is to respond to these questions; the second is to understand what the Purchasing sector hopes to solve with these insights, and finally to achieve the needed visibility in the supply chain.
Benefits of data-driven supply chain
One of the goals of a data strategy in the purchasing sector is to improve chain visibility. After all, having access to a mountain of data is useless if the data analysis does not accurately detail the flows throughout the supply chain.
A data-driven supply chain is one whose management is focused on gathering and examining data at various points throughout the chain. The analysis of this data enables businesses to acquire a true view of all their processes and the performance of their supply chain.
Based on this information, the business can identify procedures and sections of its supply chain that need to be improved, whether in terms of quality, compliance, or efficiency, and gain important insights into future demand trends.
Furthermore, a data-driven supply chain management system is required for calculating costs associated with rework, production failures, product quality issues, or noncompliance.
A data strategy centered on the supply chain, when implemented effectively, provides all professionals working in the production process with access to the essential information to solve issues related to supply, delivery, or manufacturing delays in time in order to prevent an operational disruption.
Data strategy can increase competitive advantage
In the past few years, data collecting and analysis tools have been progressively used to develop more efficient company strategies. Why not employ technology for supply chain management if a data strategy can enhance sales?
The data strategy is only the first but crucial step in boosting visibility across the whole supply chain, and with better visibility comes the ability to:
- Take proactive steps to avoid difficulties
- Adapt production to accommodate potential material delivery delays
- Maintain a sufficient inventory to meet unforeseen demands
- Identify possibilities to improve process efficiency
Data should assist businesses in overcoming any disruptions and being ready to deal with everything from logistical issues to changes in consumer behavior. Real-time data is critical for gaining an edge over competitors and promptly responding to unexpected situations.
As a result, businesses must be ready to modernize their data strategy in order to satisfy the new needs of a shifting supply chain and current market conditions.
Please contact us if you have any questions about logistics or supply chain.