Leveraging Data Analytics in eSourcing for Better Decision-Making


Discover the power of data analytics in eSourcing for informed decision-making. Elevate procurement strategies through leveraging analytics to make smarter, data-driven eSourcing decisions. 

Data is everywhere. Some are useful, some less so. There are places where data is everything. One of those places is in business and one of the places it has the most value is the supply chain. The trick is how you use it and in today’s world, analytics holds the key to unlock big data. 

But what is big data? How can big data management improve eSourcing practices, and how does big data analytics lend itself to better decision-making to drive your business forward?

In this article we’re going to get a better understanding of big data and analytics, how they can be managed, and leveraged to enhance eSourcing and the entire supply chain.

What is big data?

Big data refers to enormous amounts of unstructured data from several sources that must be properly arranged and analysed before it can be used to its full extent. There is so much data that current data processing software simply can’t cope. You need larger platforms with greater automation to optimise the data and use it to discover patterns and trends in things like spending, risk management, and supplier performance.

It’s advisable to choose your eSourcing platform wisely because the volume of data isn’t the only thing to consider. Information comes flooding in like a tsunami – big, relentless, and faster than you think. You need a platform that can manage tonnes of data from different sources simultaneously.

Types of analytics

1) Descriptive analytics

Descriptive analytics is all about historical data, which can be very useful. For example, various reports, including sourcing, sales, and revenue, demonstrate the business’s financial health. It’s possible to see patterns of behaviour that cost the business money and areas where opportunities are ripe for leverage.

2) Predictive analytics

Predictive analytics is where it starts to get complicated with statistical modelling and probabilities, etc. AI and Machine Learning technology combine things like data mining, historical data, and ML guesswork to identify possible future results. For example, trend A in eSourcing presents opportunities for growth, but trend B is risky.

3) Prescriptive analytics

Prescriptive analytics is like the Ghost of Christmas Future, it shows you what could be. It even recommends certain courses of action based on the likelihood of success. This kind of advanced analytics is very complicated. Not only does it use very advanced mathematics, computer science, and statistical methods, but it’s also best interpreted by a big data engineer. 

Big data management

The point of big data and big data management is to provide invaluable insights into the efficiency of current eSourcing strategies and how the strategies must evolve to ensure a successful future. The number of businesses, especially small businesses, that are moving over to big data services is growing rapidly.

Consider: In 2022, the global big data analytics market stood at $271,83 billion. It’s expected to hit $307,52 billion in 2023. Another study found that businesses that use big data saw their profits go up by 8% – 10%.

Furthermore, investing in big data analytics needn’t break the bank. Many small businesses start off with approximately $10,000 annually. 

The new data-centric approach to essential business processes, especially eSourcing, eProcurement, and supply chain management, enables owners to respond proactively to changes in the current market while optimising the functionality of business operations.

Benefits of big data analytics for eSourcing

Big data analytics has many advantages for eSourcing. One of the most useful is data in real-time. Information comes in, is processed, analysed, and is immediately available. Constantly updated data allows you to see how your suppliers are performing. Data-fed forecasting points to potential risks which you and your supplier can address to avoid the problem completely.

Real-time market data provides information up and down the supply chain. Data regarding customer satisfaction can also point to supplier problems, like poor quality material and shoddy workmanship. You can take this up with your supplier or rely on reports generated by automated eSourcing software to choose a new supplier.

Additional benefits to be leveraged include:

1) Advanced Artificial Intelligence (AI) or Machine Learning (ML) technology has enabled the tech to mimic human thought, reason, and learning – only much, much faster. This is handy when there is a lot of data coming in and you simply don’t have the time or resources to sort through all of it, let alone analyse and optimise it. AI technology can do all of that and deliver the data to you virtually immediately.

2) Regulatory compliance is assured. The accuracy and consistency with which data is captured and stored are standardised to ensure that all documents, reports, and eSourcing business practices don’t just meet legal regulations but also pass quality standards.

3) ESourcing data analytics software ensures important information is transparent and easily accessible. You have access to data at all links in the supply chain. There is literally nowhere to hide. All data is visible, which means that buyers can spot when the manufacturer is about to drop the ball, and take steps to resolve the matter before it becomes a problem.

4) Risk management is easier because you have volumes of data on all your suppliers. You could know how many reviews they have on social media – and whether those reviews are good or bad. You could have access to professional ratings and get insight into their service delivery; do they deliver on time, do they consistently overspend, do they always use genuine materials and not counterfeit? 

Big data technology gives you the means, and even the methods, to reduce risk to the barest minimum.

Big Data Analytics Tools

As we’ve seen, big data analytics is complicated, so it stands to reason that it needs special tools to get the most out of it. Some of the most used tools include:

ESourcing software. These analytics tools are designed to manage all aspects of the eSourcing process, from identifying, evaluating, and selecting suppliers to payment tracking. The tools simplify the eSourcing management process, making it more efficient and leveraging the resulting cost savings to include a more diverse set of suppliers on an international level.

Data platforms. ESourcing software includes a single platform through which data can be managed. When you’re dealing with big data, however, you sometimes need a data analytics platform large enough to cope with all the information without hiccups or downtime. These big data tools capture, store, and analyse huge amounts of vendor or supplier data, which can be instantly processed and delivered to eSourcing experts who will use it to make informed decisions quickly and incisively.

Financial management. Financial analytics tools play a significant role in eSourcing. Spend, invoice, and purchase order analytics provide essential insight into the financial management and well-being of the eSourcing link in the supply chain. They keep track of all spending not directly related to procurement and provide invoice data that analyses payment cycles – and identify patterns of late or nonpayment.

Purchase order and payment analytics round out the financial tools, creating a comprehensive view of eSourcing’s financial status in the supply chain.  

The final word on eSourcing big data analytics?

There is no final word. Big data gets bigger by the hour and the tools that analyse and make sense of all the data become more sophisticated and automated by the day. There is still plenty of untapped data languishing below what we’ve already discovered and leveraged to make eSourcing (and consequently all parts of the supply chain) more efficient and more accurate so that decision-making is always improving – improving the bottom line.

At the beginning of the article, we undertook to better understand big data and its role in eSourcing. We’ve looked at what it is and how it can be used to enhance eSourcing by streamlining the processes and keeping a close eye on suppliers and spending.

We’ve also looked at some (of very many) tools available that deliver business data analytics in a usable format for people to understand.

If you want to investigate further, contact Delta eSourcing for a free demonstration of how an eSourcing platform can benefit your business.

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