How data and analytics fuel digital transformation in procurement
What is digital transformation in procurement?
Digital transformation is the automation of procurement processes through the collection and analysis of data.
Artificial intelligence (AI), algorithms, and machine learning (ML) are all enablers that are helping businesses to improve digital transformation in their procurement operations.
Employing automation increases efficiency, compliance, and the value that good procurement brings to the business.
Types of procurement analysis
1. Descriptive Analytics - Analysis of the data to describe what happened in the past.
2. Diagnostic Analytics – Interpretation of the data to explain/understand why a situation happened in the past.
3. Predictive Analytics - Looks at trends and data to forecast future procurement performance and the likelihood a situation will occur again.
4. Prescriptive Analytics - Improves decision making by suggesting actions through predictive modelling.
What are the 8 procurement processes?
- Needs Recognition
- Purchase Requisition
- Requisition review
- Solicitation process
- Evaluation and contract
- Order management
- Invoice approvals and disputes
- Record Keeping
How can procurement analytics improve procurement processes in your business?
Analytics by itself is only an enabler but used within procurement it can help improve processes and outputs within many business areas. Here are some examples:
1. Analytics in category management:
It allows category managers to identify saving opportunities, manage risk, manage suppliers, and assists innovation. Not only that but it also facilitates the identification of opportunities and risks by analyzing data silos (collections of raw data accessible by one group but cut off from the rest of the organization) together with the new available data.
2. Analytics in strategic sourcing:
It helps to identify the optimum times and areas to run sourcing events and request for proposal. Likewise, it provides information about suppliers’ risk and quality. Consequently, this information helps identify which suppliers to include in sourcing projects.
3. Analytics in contract management:
Here, analytics yields value across contract lifecycle management (CLM), as well as data insights regarding when a contract needs to be renegotiated. Furthermore, analytics helps to manage contracts and optimize discount levels and forecast the liabilities in financial terms. In addition, it provides data for supplier negotiations.
4. Analytics in procure-to-pay:
Here analytics provides insight into the financial and transactional side of procurement. Purchase order cycles and demand volume can be measured and improve payment terms. Moreover, it helps evaluate payment accuracy, discover rebate opportunities, identify currency fluctuations (and benefit from them), find mistaken payments, and reduce fraud. It can also forecast commodity price changes.
5. Analytics in sustainability and CSR:
In this domain, analytics helps supply chain and procurement via assessment of sustainability and corporate social responsibility (CSR) information. By analyzing the social and/or environmental impact of procurement decisions, analytics helps to lessen negative impact through identifying opportunities for improved sustainable alternatives.
6. Analytics in risk management:
This helps to reduce risk in supply chain and procurement. Through analytics, it is easier to decode the complex relationship between supply, price, environment, CSR initiatives, and risk to identify opportunities for improvement. Furthermore, it can help evaluate vendor delivery timelines, product quality, and time usage to resolve any problems.
7. Analytics in performance measurement:
Here, the focus is on bettering the bottom line, through analyzing profit and loss (P&L) reports. Procurement analytics are used to produce and examine multiple datasets to identify savings and cost reduction opportunities.
As you can see, data and analytics in procurement can be used to improve overall business performance. Nowadays, there are different software tools to help businesses adapt to the ongoing digital transformation in procurement. Certa digitizes the lifecycle of your third party suppliers and caters to the entire Third Party Risk Management process. Through utilizing procurement data to build better relationships with suppliers, Certa streamlines the digital transformation within your business, permitting cost savings and giving you more time to focus on other critical areas of procurement.
How data and analytics fuel digital transformation in procurement
What is digital transformation in procurement?
Digital transformation is the automation of procurement processes through the collection and analysis of data.
Artificial intelligence (AI), algorithms, and machine learning (ML) are all enablers that are helping businesses to improve digital transformation in their procurement operations.
Employing automation increases efficiency, compliance, and the value that good procurement brings to the business.
Types of procurement analysis
1. Descriptive Analytics - Analysis of the data to describe what happened in the past.
2. Diagnostic Analytics – Interpretation of the data to explain/understand why a situation happened in the past.
3. Predictive Analytics - Looks at trends and data to forecast future procurement performance and the likelihood a situation will occur again.
4. Prescriptive Analytics - Improves decision making by suggesting actions through predictive modelling.
What are the 8 procurement processes?
- Needs Recognition
- Purchase Requisition
- Requisition review
- Solicitation process
- Evaluation and contract
- Order management
- Invoice approvals and disputes
- Record Keeping
How can procurement analytics improve procurement processes in your business?
Analytics by itself is only an enabler but used within procurement it can help improve processes and outputs within many business areas. Here are some examples:
1. Analytics in category management:
It allows category managers to identify saving opportunities, manage risk, manage suppliers, and assists innovation. Not only that but it also facilitates the identification of opportunities and risks by analyzing data silos (collections of raw data accessible by one group but cut off from the rest of the organization) together with the new available data.
2. Analytics in strategic sourcing:
It helps to identify the optimum times and areas to run sourcing events and request for proposal. Likewise, it provides information about suppliers’ risk and quality. Consequently, this information helps identify which suppliers to include in sourcing projects.
3. Analytics in contract management:
Here, analytics yields value across contract lifecycle management (CLM), as well as data insights regarding when a contract needs to be renegotiated. Furthermore, analytics helps to manage contracts and optimize discount levels and forecast the liabilities in financial terms. In addition, it provides data for supplier negotiations.
4. Analytics in procure-to-pay:
Here analytics provides insight into the financial and transactional side of procurement. Purchase order cycles and demand volume can be measured and improve payment terms. Moreover, it helps evaluate payment accuracy, discover rebate opportunities, identify currency fluctuations (and benefit from them), find mistaken payments, and reduce fraud. It can also forecast commodity price changes.
5. Analytics in sustainability and CSR:
In this domain, analytics helps supply chain and procurement via assessment of sustainability and corporate social responsibility (CSR) information. By analyzing the social and/or environmental impact of procurement decisions, analytics helps to lessen negative impact through identifying opportunities for improved sustainable alternatives.
6. Analytics in risk management:
This helps to reduce risk in supply chain and procurement. Through analytics, it is easier to decode the complex relationship between supply, price, environment, CSR initiatives, and risk to identify opportunities for improvement. Furthermore, it can help evaluate vendor delivery timelines, product quality, and time usage to resolve any problems.
7. Analytics in performance measurement:
Here, the focus is on bettering the bottom line, through analyzing profit and loss (P&L) reports. Procurement analytics are used to produce and examine multiple datasets to identify savings and cost reduction opportunities.
As you can see, data and analytics in procurement can be used to improve overall business performance. Nowadays, there are different software tools to help businesses adapt to the ongoing digital transformation in procurement. Certa digitizes the lifecycle of your third party suppliers and caters to the entire Third Party Risk Management process. Through utilizing procurement data to build better relationships with suppliers, Certa streamlines the digital transformation within your business, permitting cost savings and giving you more time to focus on other critical areas of procurement.
