Sustainability has become a hot-button issue for every business. Supply chain firms play a critical role in enhancing the sustainability of products and in delivering insights that customers demand these days.
Thanks to the immense amount of data that virtually every company now collects and has access to, supply chain firms can use advanced analytics to enhance their processes and reduce waste. On the other hand, transitioning to an analytics-driven organization is challenging, especially given the manual nature of legacy supply chain workflows.
Here are five tasks that supply chain firms must execute to build a sustainable organization that is data-driven.
Examine the Past and Present
Many organizations have been collecting vast troves of data for years without knowing it. One of the hurdles that legacy data presents is that it’s largely disorganized and stored in diverse, often unstructured formats.
Collecting these data together and analyzing them for patterns that can drive sustainability might be a tough task, but it’s a worthwhile one.
If your organization has already begun using analytics to increase efficiency, examine the data you’re collecting for their relevance towards your sustainability goals. Examine your historical data and identify the variables that are relevant for your goals today. Conducting a review of your analytics workflow is also a good idea.
How integrated are your workflows? Are all data sources connected to analytics dashboards, and are they generating relevant threshold alerts? Create easy to understand processes that back these data up, and you’ll find it easy to monitor your progress towards enhanced sustainability.
Model the Future
Modern analytics packages give you the power to model future scenarios and conduct deep what-if analysis. Supply chains are vulnerable to political, environmental, and social factors that affect transportation routes and logistics. Analytics is the key to solving these issues.
An increasing number of supply chain firms are adopting predictive analytics packages that are easily integrated with custom machine learning algorithms. These systems go beyond merely calculating the shortest and least wasteful delivery route. They also take local regulations and political events into account and reduce the time spent in transit.
For example, many healthcare and food products require sensitive temperature and other condition monitoring systems to ensure they arrive fresh at their destination. Monitoring this information with analytics solutions allows companies to make sure goods arrive safely without risk of spoilage or encountering regulation-related delays.
Incorporate Non-Traditional Data
Typical sustainability metrics include factors such as energy use, water use and raw material consumption. While these variables are important, they provide a narrow view of your organization’s sustainability efforts.
Thanks to the massive technological leaps that analytics packages have made, it’s now possible to dissect non-traditional data.
Variables such as employee headcount, time spent on tasks, sales volume, inventory efficiency and hours of operation aren’t what you would think of as driving sustainability at first. However, when you recognize that all of them point to the efficiency of your overall organization, you’ll make a massive difference to your sustainability efforts.
Use analytics packages to model different scenarios using these variables. For example, do your workflows take longer on certain days? Are they more efficient at certain times? What would delivery processes look like if you changed workflows? Modeling everything is the key. Spend time getting to know how your analytics package can help you.
Act on Insights
The best analytics are useless without action taken to act on them. Many organizations, unfortunately, think that sustainability ends with simply tracking data. One reason for this happening is the difficulty in reorienting company culture towards analytics-driven decisions.
Focus on reeducating and repurposing your employees’ skills to match the new environment you’re looking to install. There’s no doubt that analytics and data are the way forward so installing the right training programs and workflows that generate employee buy-in is critical.
Alienating your employees or making them feel as if the human touch is unreliable or inefficient is the wrong way to go about it.
Instead, highlight how analytics helps them gain deeper insights into their jobs and allows them to spend less time on clerical tasks. Focus on how they can use analytics to zero-in on the most critical parts of their job and can spend more of their time solving issues instead of simply keeping up with them or following up on manual processes.
Refine and Improve
Conduct a thorough review of your analytics workflows and processes. Seek employee feedback constantly. After all, they’re the ones involved in the day to day operations and will have better insight into granular issues.
While the tiny details are important, the big picture matters as well. The business environment is changing, and customer demands are changing with it.
These days, customers demand instant insight into their problems and expect their suppliers to keep up. Sustainability is challenging to maintain due to ever-changing fuel costs and political environments. Pandemic lockdowns forcing people to work remotely, to stop flying to conferences and killing commutes can make a big difference too.
In short, everything is in flux. The only way to keep up with these changes is to conduct iterative reviews of your processes at every level.
Dynamic Workflows for Enhanced Sustainability
The age of the static sustainability program is dead. These days, organizations need to react quickly to changes in their environment. Using analytics and embracing them as a point of company culture is the best way to handle dynamic environments.
