Context

Today the world generates more data than ever before. In 2013, the total amount of data created, captured, copied, and consumed worldwide was reported to be around 9 zettabytes. According to some estimates by the end of 2020 the number has increased by 6.5 times to 59 zettabytes.

Here at Eshia Analytics we consider data as the “new oil” and in our experience we have seen that the data driven companies that use integrated and advanced analytics outperform their competitors in every sector.

Supply chain happens to not only be an indispensable part of a business but also a very sensitive one. A slight mismanagement in one particular segment of it can have an overwhelming domino effect on other operations and processes. It can lead to heavy expenditure and other undesirable nuisances.

But data science combined with AI is helping businesses to circumnavigate these issues, cutting costs and making processes more reliable and accurate.

According to grandviewresearch.com, the global supply chain analytics market size was USD 3,460.1 million in 2018 and is expected to reach USD 9,875.2 million by 2025 at a CAGR exceeding 16.4% from 2019 to 2025

Here are 6 key ways that Data Science is transforming supply chain:

1) Demand forecasting

The ability to generate large volumes of high dimensional data related to demand creation has contributed significantly in the development of sophisticated algorithms that can forecast demand in much more accurate terms.

With the help of data science and ML advanced techniques for forecasting and bringing improvements in finding optimal aggregation levels and forecasting horizons are getting built and implemented.

It’s very important for the companies to correctly evaluate the influences of not only their own marketing activities but also factors like the promotional activities of the competitors and customers on demand generation. At the same time, attributes like product innovation, social trends and government policies need to be considered to modify the product portfolio to align with the market demand.

Descriptive, predictive and prescriptive analytics is making it much more feasible to quantify and understand these attributes better; predict the outcomes more accurately and prescribe robust marketing strategies and portfolio modifications.

With several aspects of demand forecasting getting predicted accurately and automated, production scheduling and inventory management is becoming easier every day.

2) Inventory planning

Inventory planning is very crucial for having a good supply chain. Nothing can be worse than the delay or obstruction in the supply of a product when its demand is really high. On the other hand storing a product in excess when its demand is not that high can lead to undesirable expenditure.

So, one primary area of concern for businesses is to make sure that the inventory facilities and the manufacturing amenities are all properly connected.

Data science and AI can help analyse manufacturing units and warehouse alignment and predict how that can influence the supply chain with a changing demand.

Additionally, it finds the best flow paths to fulfil customer demands at optimal cost

3) Dynamic pricing

With the latest techniques in data science the factors influencing pricing can be calculated accurately and prices can be set in real-time that will play a huge role in controlling the demand according to the capacity of the supply chain and the best revenue stream.

Data analytics can help companies gain market growth by deciphering market behaviour in quantified terms and understanding the customer demand curve.

4) Efficiency and transparency in transportation

The recent upsurge in IoT devices has given the business owners a scope to have more clarity and control on the transportation processes. Vehicles carrying the goods can be tracked and data can be logged in real time. Big data analytics can use that data in multiple areas like minimizing fuel consumption, prevention of delays, improving driving efficiency and building navigation systems to avoid bottle necks.

It can also help businesses choose the right transport modes, like delivery by train or a truck, thus cutting expenses and carbon emission.

5) Improving customer support

Data Science and AI techniques can render functionalities like chatbots and voice assistants that will ease up the process of customer support to suppliers, consumers, wholesalers and sales forces.
Chatbots and AI voice assistants can help solve queries better and faster with more accurate information.

Additionally, AI combined with some latest technologies like blockchain is helping businesses deal more efficiently with warranty and procurement frauds, scams and compliance issues.

6) Sourcing and procurement

This particular function already has data in abundance at its disposal. But there are still many teams that wrangle data in the traditional way. That involves laborious tasks of compilation, organisation and dissemination processes that can extend for months. But big data analytics is making all of that much faster, efficient and stream lined.

Data analytics and AI can be used to automate and improve the processes constituting the selection of suppliers and evaluation of opportunities. This will pace up product development cycles, lowering of expenditure by increasing production efficiency and improving product quality.

How can Eshia analytics help you?

Do you want to make your supply chain more transparent and reliable?

Do your delivery processes often experience bottlenecks? Are your customers complaining about damaged products or delayed deliveries?

Or, do you want to explore demands more accurately and opt for better inventory management?

Well, then allow Eshia Analytics to partner with you.

Here at Eshia Analytics, we have a team of data scientists and engineers experienced in delivering data driven solutions for the big and complex supply chains.

With a deep understanding and hands on experience in implementing the latest techniques in analytics and the state-of-the-art AI functionalities we can help you extract the value out of your data and deliver end-to-end solutions that can save an enormous amount of money and time by automating manual/tedious tasks, predicting outcomes and prescribing data driven strategies.