Data analytics and the future of supply chain

For those who are following in latest in supply chain news there seems no end to the reports on the importance of advanced supply chain analytics. A large majority of progressive’s CEOs agrees with these reports and put issues concerning supply chains among the top issues on their agenda. Despite this we are reminded of the lack of preparedness from company and supply chain leaders. According to an article from the Hacket Group, 94% of supply chain leaders say that digital transformation will change supply chain on a fundamental level in the coming years, but only 44% have a strategy ready.

Some companies might believe they are prepared for these impending changes as they have poured money on digital technologies. This doesn’t mean that they can sit easy as investing in digital technologies is nothing unusual. 85% of companies are investing heavily in digital technology but at the same time only a few of these companies are succeeding in achieving the expected growth value. What we can see here is a gap between the needs of the companies and what is done to meet those needs. There also seems like there is a lack of direct correlation between investments into digital technologies and actual growth and results. Or at least an inefficiency.

There are a few reasons for this inefficiency that we can point out.

• Lack of understanding of available technologies.

The lack of understanding of technologies, how to use them and their uses complicates decision making and creates uncertainty whenever a decision is to be made.

• Difficulties adapting to new technologies and new ways of working.

Many companies have a hard time adapting to new technologies and new ways of working during, and after, digitalization. Rigid thinking and working are major roadblocks for value creation.

• Unfocused transformation.

Digital transformation of the supply chain is strategically a company-wide issue and the CEO carries a fundamental role in this endeavor. The top management of the corporation need to be the frontrunners of new technology for the rest of the company to follow suit. This means that management needs to actively inform and educate themselves in new technology.

Connectivity and analytics

Companies spend a lot of time and money on technology as the enabler of connecting supply chain and this technology will most likely play an important role in creating efficient digitalization long-term. Yet a faster way given current system environments, preconditions and challenges is through a scalable and flexible technical platform, enabling efficient and fast connection of trading partners. An interconnected supply chain and the use of analytical data means faster, better informed and more adaptive decision making.

A connected supply chain leads to better collaboration and cooperation. With effective connectivity, up and down the information chain, the different actors within the chain can share everything from on-demand-data, status signals, deviations, problems and even solutions between each other. Connectivity allows companies to gather and access data along the entire end-to-end flow.

Connectivity in turn allows us to use one of the important technologies for supply chain companies today; data analytics. The huge amount of data that can be shared along the supply chain opens up the possibility to measure, analyze and finally predict data. For example, the possibility to measure performance in the data flow opens possibilities to discuss the cause and effects of problems and successes. Which in turn leads to improved capabilities for improvement and change. Data analytics can provide not only descriptive analysis such as shown above, but also predictive analysis and prescriptive analysis. I.e. knowing what to expect and knowing how to act respectively.

The future of advanced supply chain

The Hacket study shows that 100% of the asked supply chain leaders thought advanced supply chain analytics important and 66% of them deemed it to be of critical importance. Though the study shows many supply chain analytics case opportunities that supply chain leaders deems important remain unutilized.

The most important use cases of advanced data analytics in the following years we can draw from the study are optimization of production and sourcing to reduce total landed cost. As well as inventory level optimization to balance working capital investments with service levels. Other important opportunities include cases such as;

• Measuring and analyze transportation performance.
• Identify and resolve quality defects trends and root causes.
• Analyze product cost variances.

To be able to take advantage of these opportunities companies will require a large amount of accurate data from not only the entire supply chain, but also external sources. Which in turn requires a higher degree of connectivity within and outside the supply chain.

It seems that a majority of companies are to expect many challenges when it comes to their supply chain and their technological and analytical maturity. Supply chain operations and performance will improve as processes and workflows are implemented to improve data quality, consistency and systems that can deliver end-to-end supply chain analytics visibility. A move towards predictive analytics and external data integration are a natural small but important step for companies as supply networks grow quickly globally.