Digital transformation is one of the most used but rarely understood terms in businesses. A common mistake is to think that digital transformation is a fast and revolutionary process for automation. In fact, digital transformation is a long process that has been going on for decades. Operational functions such as imprecise procurement laid the foundation for digital transformation, and they quickly caught up and gradually matured. This Tech Town article describes the digital transformation of shopping and 7 ways that data and analytics has driven it.

Digital transformation in shopping

Digital transformation in procurement involves new applications and automation of procurement processes to increase efficiency, compliance and value of functionality. 

Algorithms, artificial intelligence (AI), robotic process automation (RPA), and machine learning (ML) are all emerging tools for improving procurement applications and processes. 

But it’s not just new tools, diverse types of data that are driving digital shopping. Any business transformation starts with human expertise. According to the Accenture report, other diverse factors include a shift in skills and talent required, improvements in intuitive user experiences on enterprise software, and the way policies and processes guide the operating model. 

Together, these trends are rejuvenating shopping. Due to the great need for analytics and expense management, many solutions have emerged to meet different needs and levels of demand. As the procurement software landscape evolves, procurement is provided with access to better tools for collaboration, integration, and innovation.

The evolution of shopping analytics

This is an area where procurement technology has evolved through clear stages. We have observed the digital transformation taking place across different generations of shopping analytics:

  •     Generation 1 (1990 -): Analysis performed in Microsoft Excel by business consultants or analysts, mainly focusing on past spending analysis.
  •     Generation 2 (2000 -): Desktop spend analysis software purchased under license with data stored on-premises or in the enterprise firewall.
  •     Generation 3 (2010 -): A browser-based spend analytics dashboard that provides enterprise-grade usability and visualization, licensed or purchased as a SaaS. These SaaS dashboards provide granular visibility to gain more insight into the data.
  •     Generation 4 (2015 -): Automated, AI-powered shopping analytics solutions that combine multiple data sources, encrypted and stored in the cloud, and purchased as SaaS. These solutions provide detailed notifications, alerts, and solutions that improve procurement responsiveness and vigilance.

Different generations of procurement analytics solutions coexist to meet the needs of different business sectors. Some businesses keep their Excel reports, while others may continue to use self-built or preconfigured business intelligence solutions into the new decade. Some businesses may skip generations in the digitization process entirely if management has a clear direction to realize data-driven transformation.

From insights to action

In the early days of procurement analytics, the best leaders could hope for were annual (or semi-annual) performance reviews as part of the broader sourcing strategy process. than. They simply don’t have the digital maturity to connect, clean, and harmonize data fast enough for frequent and extensive analysis. As digital capabilities and capabilities improve, we can change our perspective from the past to the present – and even the future.


Analytics has enabled procurement to shift the focus from expense approvals and reporting to forward-looking forecasts that can affect business spending.


Procurement Analytics today is not only a new set of tools for cost management, it also unleashes value in procurement data, provides strategic insights for the business, and enables purchasing. contribute to setting direction. Procurement can use Analytics to describe, predict, or improve business performance. Analytics approaches all operations – from strategic sourcing to category management and the purchasing process.


At a broad level, the data analyzed can be divided into four categories:

  •     Description: What happened in the past?
  •     Diagnosis: Why did something happen in the past?
  •     Predictions: What trends and patterns will play out?
  •     Indication: What procurement decisions should be made?


Traditionally, procurement analytics focused on understanding past procurement spending and supplier performance, but it’s now turning towards AI-driven decision-making. This reflects the evolution from “descriptive” to “sound” analysis.

7 shopping apps converted by analytics

Analytics is a great example of digital transformation. Specific examples of work and tasks being transformed can be easily identified. Analytics itself is just a support tool, but when in the hands of professionals, it becomes a powerful tool for improvement. 

Software advancements have made procurement so data-intensive, and there are many opportunities that analytics provides in this area. Here are seven common uses of analytics in shopping:

  •     Analytics in portfolio management: Procurement analytics enables portfolio managers to identify savings opportunities, segment and prioritize suppliers, address risk, and facilitate innovation. Systematic exploration of opportunities and risks can only be successful when the previous data sets are analyzed together.
  •     Analysis in sourcing strategy: In sourcing strategy, analytics helps determine the best times and areas to run sourcing events and requirements. It can identify which suppliers to include in a project and provides rich information about the supplier’s quality and risk position.
  •     Analysis in contract management: Analysis of the value provided through contract lifecycle management (CLM). It can warn when contracts need to be renegotiated or provide data for negotiations with suppliers. Analytics can identify maverick spend to help with compliance and improve contract coverage. It can help exploit the benefits of scale and scope.
  •     Financial analysis in procurement: Procurement analytics can also provide a lot of value in the transactional and financial aspects of procurement. With analytics, businesses can measure order cycles and improve payment terms. Can assess payment accuracy, uncover discount opportunities, benefit from currency fluctuations, identify mistaken payments, and reduce fraud. Businesses can also forecast and implement situations of changes in commodity prices.
  •     Analysis of sustainability and CSR: Analysis can assist in assessing sustainability and corporate social responsibility (CSR) in the supply chain and procurement. Analytics can uncover the environmental or social impact of procurement decisions and identify opportunities for more sustainable alternatives and improvements.
  •     Analytics in Risk Management: Analytics can assist in identifying and mitigating risks in supply chains and procurement. It can unravel the complex relationships between supply, price, environment, CSR initiatives, and risk, and identify opportunities for mitigation.
  •     Analysis in performance measurement: Procurement analysis is used primarily to determine the savings realized, which are directly related to the financial statement of profit and loss (P&L).

The next stage in transformation: Shopping data centers

Now is a good time to be a procurement leader driving digital transformation. Through decades of development, we have more data and software solutions than ever before. As the pace of development is accelerating, one area that comes to mind in analytics is the concept of a shopping data center.


In the past, procurement analysts were limited in their ability to use data from outside the enterprise’s IT department. For many people, combining data from different ERP systems or transaction source systems is challenging enough. Cloud-based procurement analytics software and APIs enable more automated and flexible use of data coming from both internal and external systems. Businesses can view all of this from the point of view of a shopping data center where information can flow naturally. 

Today’s analytics software can safely orchestrate this flow of data in real time. What remains is for leaders to decide on the most valuable data flows for data to flow based on their organization’s goals. 

There was a time when spending analysis and supplier risk assessment occurred at different stages in a long process, but advances in digital transformation have allowed us to accelerate growth. really high.


Remember, digital transformation is a journey and not the end goal. Data and analytics enthusiasts have seen digital procurement move from opportunity to a vision of interconnected data centers. Now, join the transformation movement and enjoy the value it brings! 

Hopefully the information Tech Town brings above will be useful for businesses. If you are planning to implement digital transformation but don’t know where to start, Tech Town is here to help. 

Tech Town is a technology company from Vietnam, with representative offices in the United States, Japan, Canada, the Netherlands, … As a reputable digital transformation consultant, specializing in implementing projects custom software development with the application of the most modern technology techniques such as AI, Machine Learning, Blockchain… For more than 4 years of operation, Tech Town has become a trusted digital transformation consulting partner. by startups and enterprises from many countries around the world such as the US, Canada, the Netherlands, Japan, the UK and other developed countries. 

Contact us if your business has any technological challenges!



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