How to build a data-driven procurement approach? | EuroIndustriel
Big data helps procurement teams address the multiple challenges. By combining real-time information with historical data and customer insights, procurement team can become pro-active. They can optimise the supply chain and improve profits with data-backed decision making.
The buzz word right now is Big Data. But, less than 25% of corporates have long-term strategies to leverage the power of data. Can you believe that over 2.5 quin-tillion bytes of data are created every day? And, over 90% of existing data was created in the last two years.
With so much data to handle, it’s understandable that procurement teams are finding it challenging to keep up to speed. This rapid proliferation of data has forced organisations to rethink their decision making. They no longer can rely on gut instincts or historical data. Instead, organisations have to learn how to leverage real-time data for the best results.
Here are the top five ways for procurement teams can get started with the data analytics game, to streamline the buying process.
1. Procure More Value from Non-Traditional Data Sources
Generally, most organisations analyse only spend data. If you’re looking to leverage more value from your data, then you have to look beyond traditional data sources. For example, text analytics can help you gather insight about a supplier via social media. Social media data is an unexploited data source that can provide you with timely insights.
Nearly 80% of the data in an organisation is unstructured. Unstructured data includes everything from emails, text files, social media and more. Unstructured data is an untapped goldmine. Start by structuring and organising this data. Keep in mind that real-time data plays a crucial role in helping you monitor real-time strategies as well as tweak implementations in real-time to increase the chances of success.
2. Feel the Pulse of Changing Customer Demands
Data analysis is a great tool to identify, track and predict changing customer requirements in real time. Additionally, it helps to improve customer service by making logistics more efficient, and eliminating costly errors.
3. Procure the Best Quality Products at the Best Prices
This is one of the biggest tangible benefits of leveraging data analytics for procurement. In today’s highly competitive environment, supply chains face the constant pressure to be agile and more cost-effective. Data analytics can compare pricing and availability from suppliers in real-time, while also considering other ancillary factors like logistics costs and other variables. This helps procurement teams source the best quality products at the best prices in real time.
4. Identify Data Points that offer True Value
One of the biggest challenges facing procurement departments is that they are overwhelmed by the sheer volume and diversity of data available. They struggle to make sense of data, making it impossible to leverage it. Big data is a big opportunity for procurement. Don’t make it a challenge. Start by structuring data and identifying data points that offer true value.
5. Include all Three Pillars of Supply Chain Management in Data Analytics
Planning, design and execution are the three pillars of supply chain management. Data analytics is not just the forte of the procurement department. Get all departments involved starting from finance to sales. Every department should work on addressing the challenge, “how do I make the supply chain more efficient?” This is a must for a data-driven procurement approach.
The Future of Procurement is Data-Driven
Earlier, procurement was primarily seen as a process-drive approach. Today, it has emerged to be a data-driven activity. All procurement activities – sourcing, contracts, making purchase – have become data-driven. By having access to the right data insights, companies can take better decisions boosting the bottom line.
The future of procurement is data driven. The sooner your company moves to a data-backed approach, the better and more efficient is the entire process.
