Data-driven business practices permeate industries and departments and have become one of the biggest competitive advantages today. The level of knowledge businesses can extract from their own internal and external operations makes it possible to make informed decisions that will boost growth on multiple levels.
The situation is no different when it comes to supply chain management. This business area produces massive amounts of data coming from customers, suppliers, inventory, and more, and it can greatly benefit from a data-driven approach.
But how do you get started and what is the best way to go about it?
In this guide, we will provide you with 5 data-driven ways in which you can improve your supply chain performance and ensure enhanced productivity and growth.
Let’s dive in!
1. Use a mix of internal and external data sources
In many business areas but especially in the supply chain, internal data is equally as valuable as external one as the mix of the two provides the 360-view that decision-makers need to optimize every relevant aspect of supply chain performance. Some of the most common external and internal data sources used for supply chain optimization include:
- Production: this data enables businesses to analyze multiple things such as production capacity or any production errors and fix them to avoid product returns.
- Warehousing: this data can help spot inventory shortages as well as any other issues to ensure orders arrive on time and with the expected quality.
- Transportation: this data can enable organizations to look at the routes they take to deliver packages, the amount of fuel being used, the volume of products being delivered, and much more.
- Sales and marketing: data on customer reviews, historical sales on specific products, and much more can help in forecasting product demand and optimizing product design and development based on specific customer needs.
2. Track and monitor the right KPIs
As we mentioned in the previous point, there are multiple sources from which organizations extract knowledge for supply chain optimization. After that data is collected, it is turned into interactive KPIs (key performance indicators) that are later visualized in a report.
Now, a common mistake that organizations make is to measure dozens of KPIs to inform their strategies. Using too many performance indicators can mislead your analysis as data that is not necessary can be considered within the analysis. To avoid this from happening, experts suggest picking around 5-6 KPIs per business goal.
The criteria to pick these indicators are they should be directly tied to your goals, be attainable and realistic, and be measurable over time, among other things. datapine wrote an insightful guide on the top 25 supply chain KPIs to guide you in the process.
3. Automate report generation with real-time insights
Reports are a fundamental piece of a successful data-driven decision-making process as they provide an organized and centralized location for businesses to monitor their performance.
That said, manual report generation is a tedious and time-consuming task that doesn’t work in the fast-paced nature of a supply chain environment. For that reason, we recommend you look into automated reporting as a key tool for the success of your analytical efforts.
Automated reporting enables organizations to generate interactive reports within minutes, leaving all the extra time that was previously dedicated to report generation free for more important tasks.
Plus, these reports provide real-time data that enables decision-makers to spot any inefficiencies or opportunities as soon as they occur. Something that proves to be especially valuable in the supply chain where each stage affects the following one.
Fortunately, platforms, like Power BI, that generate real-time analytics are widely available nowadays. Additionally, it’s also easy to find Power BI course on the internet to learn how to utilize the tool to its fullest.
4. Benefit from advanced analytics technologies
As mentioned before, supply chain management is a complex process that involves a lot of departments and areas. That’s why another important recommendation is to rely on advanced analytical technologies to make the process more efficient for less effort and money. In that sense, technologies such as predictive analytics prove to be especially useful.
Essentially, predictive analytics algorithms take historical and current data and analyze it to find trends and patterns and predict future events. Supply chain managers use this technology to predict product demand and avoid overstocking products that are not going to sell.
That said, it is important to consider market conditions when generating forecasts. For instance, some products might sell better during a specific holiday or season. Therefore, it is important to revisit forecasts based on current conditions as well.
5. Involve every relevant player in the process
Any data-driven approach will fail if the right people are not involved in it. In order for your data-driven supply chain to be successful you need to make sure every department and relevant stakeholder is informed and uses the right tools and data for their decision-making process.
This way, you make sure everyone is connected through the use of data and no standalone decisions are made. While this might sound like a less valuable point compared to the others, it is of utmost importance and should not be overlooked.
As you’ve learned throughout this post, data is the secret to successful supply chain management. While many elements go into a successful data-driven approach, the points that we’ve presented here should serve as the perfect starting point to dive into the analytical world.