With buzzwords like machine learning and artificial intelligence (AI) barraging the supply chain industry, leaders face the challenge of making informed and timely decisions around incorporating new technologies. A core tenet in seeing results from these technologies is the use of data. Yet, bad data is an all too common industry pain point and can be a major barrier for digitizing your supply chain.
Given the rise of innovative technologies, fueled by the increasing customer demands of the ‘Amazon era,’ it is all the more important to determine how to best use data to empower your organization. In this four-part blog series, Blume will be providing a guide to the ins and outs of implementing data-driven supply chain solutions. For the first blog, we’ll be discussing the most commonly faced challenges that arise from working with data and provide insight on how to solve them.
Utilizing the Right Type of Data
Within the supply chain, there is a massive amount of data everywhere you look. However, the wrong data may end up being more harmful than useful. To enable machine learning and AI, supply chain organizations need high volumes of both accurate and relevant data. Without the right types of data, these solutions will not be able to develop predictive models and instead miss opportunities for optimization.
To address this problem, organizations need to determine which data is most relevant for the types of insights they’d like to garner and problems they want to address. Supply chain organizations should consider using a combination of customer, external live and direct transportation data.
Reducing Latency in the Data
Though it may be possible to acquire the right data, it may be rendered useless, if not received on-time. Supply chain organizations often face difficulties in accessing timely data for their customers due to unpredictable factors and various carriers and companies involved in an end-to-end movement. Yet, receiving an update on a delivery in real time versus three hours can make all the difference in ensuring customer satisfaction and ongoing business.
In order to ensure the data in your supply chain is timely, seek out a platform that will give you access to real-time data. By using real-time data, your organization will have shorter lead times, gain the ability to get your product to the market faster and make more strategic business decisions.
Ensuring Data Connectivity
In addition, data in the supply chain often comes from multiple sources and even across multiple organizations, making it difficult to integrate and gain insight from. Some common sources of data used within the supply chain industry include: APIs, electronic data interchange (EDI), transportation management systems (TMS) and IoT devices. Even within these sources the type of data varies in its accuracy, creating a further obstacle to driving solutions with data.
Data connectivity is at the heart of any good logistics network which works to ensure efficient flows through the supply chain. To best ensure data connectivity, invest in a platform which brings data together from multiple sources. By correlating all of this data, your organization will be able to drive predictive capabilities in demand, real-time visibility into inventory, collaboration and real-time status of orders.
Finding Skilled People to Interpret the Data
Another data-specific challenge is a lack of skilled people to record and analyze the data within supply chain organizations. In order to ensure the data recorded within your organization is accurate, workers need to correctly input the data into a system, as most incorrect data is a result of human error. Similarly, without trained people to interpret the data, there is no way to derive meaningful insights to attain benefits from these technologies.
Investing in a workforce trained in data management and analysis will be a key difference in unlocking the potential that data-enabled technology has to transform your digital supply chain operations. With skilled employees, it will also be easier to ensure accurate and timely data.
Data-Powered Supply Chain Solutions
By following these best practices, your supply chain organization will be able to utilize data to enable solutions which drive growth and value for your customers. Additionally, all of these tips will empower your organization to make smart predictions and recommendations, saving you time and money.
To learn more about how data can pave the way to the future for a smart supply chain organization, follow along for our next post about the 4 V’s of data.