Big Data on Supply Chain

Over the years, supply chain management has evolved from traditional methods of handling activities within business operations to more advanced approaches. Technological advancement has enabled the growth of the supply chain today. 

With the aid of technology, we can deliver more products and services to customers in good time. Increase information flow within the supply chain for efficient decision-making and positive business outcomes. One such advancement is big data. 

What is big data?

Big data refers to a large amount of data in a structured, semi-structured, and unstructured form gathered by an organization. The data is often collected from different sources to enable managers to identify patterns and trends in human behaviour to increase customer engagement. 

Organizations that leverage big data gain a competitive advantage over others that do not, based on the quality of information they have to make decisions. Big data gives valuable insights into business operations, resulting in strategic decisions that impact the bottom line. It is characterized by what is called the five Vs of big data. Now, let’s look at each of them in detail. 

The five V’s of big data

Volume

The first criteria to consider data as big data are volume and size. The volume describes the amount of data that exists. This depends on the organization. For some organizations, it can be tens of terabytes of data. While for others, it may be hundreds of petabytes.

Velocity

Velocity describes data speed- how fast data is generated and moved. It refers to the continuous flow of information. Data is generated through different sources every minute. There are various ways to collect real-time data. 

For example, Every order, invoice, or comment made on Facebook or every like on Instagram generates data. Velocity also describes how quickly this data is turned into information that improves an organization’s decision.

Variety

Data are collected from different sources, and they exist in various forms. Data can be structured, semi-structured, and unstructured. Unstructured data are data that are not ordered; they can be in the form of videos, photos, and audio. 

Semi-structured data are not fully organized; they include emails, zipped files, and webpages, while structured data are organized data with a definite format and can be easily understood; examples are names, credit cards, and addresses on a spreadsheet.

Veracity

Veracity refers to the quality of data. The credibility of data is essential to a business as the main reason for gathering data is to help make informed decisions. 

Since data is collected from different sources and in various forms at high speed, it increases the tendency of errors, inconsistencies, and uncertainties. However, data used by organizations should still maintain high accuracy.

Value

The essence of data is the value the user can derive from it. Data that cannot give insights are useless. Proper data analytics should be conducted to extract value from big data. Data becomes valuable in the correct format, and quantity, and available at the right time. The higher the insights extracted from big data, the higher the value.

What are the benefits of big data?

Improves inventory management

Having visibility over inventory can help mitigate supply chain challenges. Real-time tracking can help a business minimize the risk of getting out of stock. If a retailer goes out of stock of a product, the customer might source that product from another vendor, which means the retailer can lose the customer. Big data can also provide inventory information, helping businesses predict reorder time. Therefore, ensuring products are replenished at the right time to fulfil customer demand. 

Selling on multiple channels is an advantage for today’s businesses to increase profitability. A business needs to synchronize those channels to gain visibility to be efficient. This will help to avoid overselling as you will get real-time information on your stock. 

It can also improve business order fulfilment speed. For example, when a customer makes an order, the order will be assigned to the warehouse closest to the customer. This can help to cut transportation costs and increase speed. 

Demand forecasting 

Demand forecasting helps businesses to predict the demand to be expected in the future based on past and present consumer behaviour. This allows manufacturers to produce what consumers need and helps them plan production accordingly. It also helps the finance team to prepare the finance required for procurement and operations. Primarily, demand forecasting omits disruptions and makes production smooth.

The sales team can predict marketable products at different seasons with big data. Enabling them to launch product promotions and develop sales strategies. Forecasts can also help businesses identify consumers’ spending patterns to help them create tailored marketing strategies.

Predictive maintenance

Big data can help manufacturers predict the ideal maintenance time for their equipment to avoid breakdowns. Manufacturers can analyze patterns and trends by constantly monitoring equipment and collecting data from various sources to know when maintenance is necessary. 

Insights derived from big data can also be used to create maintenance schedules and ensure that tasks are performed at the right time for smooth production processes. This would enable plant managers to improve efficiency, reduce the cost of repairs, and increase the lifespan of equipment. 

Improves transportation and logistics

For a company to reduce the cost of logistics, it must identify ways to optimize routes. Real-time data collected from GPS, weather data, and road conditions can be used to predict the best path for vehicles. With data, organizations can track and monitor the conditions of their products right from the warehouse till they get to the consumer. 

For example, perishable products need to be delivered quickly to consumers because if these products are not preserved at ideal temperature or quality when delivered, customer dissatisfaction could increase return rates. 

In a nutshell, data is ever-present, and it exists in various forms. This is why businesses must recognise its importance and take data management seriously. The more data a company can access, the more it can make better decisions by improving its inventory management, reducing the cost of logistics, and increasing its profitability through forecasting and predictive maintenance. There are many ways to make the most of big data.  

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