The global pace of business and the rapidly changing risk environment are forcing companies to find new competitive advantages—one of those being data. Because of this, there’s a vital need to leverage different types of data for different purposes. But with all valuable things in life, there’s a challenge to overcome. The problem with using historical data for supply chain risk management is the loss of context around the data. Not good. So what can you do with historical data? And what about real-time (RT) data?
Historical Data enables changes to your static SC network based on data collected over time.
Getting trend analysis:
These algorithms, coupled with real-time data, can enable more advanced statistics on value at risk, along with the potential revenue impact of events.
Real-time Data enables you to collect relevant information related to risk using “sensors” throughout your supply chain.
Rapid detection and how it works:
To move quickly, your team needs to know the context around a problem (e.g., forecasts, inventory, orders) and what options are available. In today’s fast-paced world, new decision assistant technologies are leveraging real-time data to provide a complete view of the problem and available solutions.
Some advice on using RT data:
To utilize RT information, you MUST have a new operating model. Disruptions are going to happen, and you need to be able to respond faster than your competition. In supply chain, slow and steady does not win the race. Collecting data is only step 1; step 2 is to make sense of it fast enough so that it’s useful in assessing risk. But that’s not all; step 3 is having a team that can act on the information FAST to resolve the problem FAST. Your team’s communication channels should allow them to react rapidly, while exercising authority to resolve problems quickly. Part of this strategy requires technology, but it also requires creating agility and empowerment of your team.
The Takeaway: Statistical analyses based on historical data may look pretty and seem nice to have, but are almost always inaccurate. To keep up in tomorrow’s supply chain world, take another approach—use real-time data to make important decisions based on what is happening now.
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