Purchase order (Figure 1) automation can speed up and streamline the purchasing process. A manual purchase order process is error-prone, time-consuming, and distracts the accounts payable team from focusing on higher value tasks.
For instance, a telecom company had a procurement duration of 45 business days vs. the industry average of 25. By using RPA to automate the manual steps within the procurement process, they are claimed to have1:
- Saved 800 man hours annually
- Been on track for saving ~$27K annually
- Increased per-employee transactions
- Reduced cycle times
In this article, we will explain what purchase order automation, is and what automation tools automate it. We will also discuss how purchase order automation can help companies have a more robust purchasing process, by discussing its top 8 benefits.
How do you automate a purchase order?
Purchase order automation is using automation solutions to have robots automatically generate, approve, and send purchase orders to suppliers instead of a human staff doing it.
The solutions leverage various automation tools, such as:
- RPA automates rules-based tasks within a PO creation process, such as data extraction and inputting.
- OCR and NLP read the content on a PO, standardize, and categorize it.
- API exchanges the PO’s data with other financial solutions, such as the financial close software.
However, using non-customizable legacy tools in PO automation can result by:
- Stacking of variety of automation tools
- One to one matching only
- Human interventions
- No line level matching
- Invoice line defaulting
- Fails in matching in case of deviations
Implementation of AI can enhance the level of PO automation. ML algorithms with continual learning features can overcome some of the obstacles mentioned above.
A real-life example of accelerating PO automation is Hypatos. Hypatos’ smart algorithms (Figure 2) can be customized and adapted to specific needs based on companies’ individual data. Its model can combine master & historical data and can:
- Match several invoices referencing one PO or reverse
- Contrary to only capturing data as in OCR, use data to match PO& invoice
- In next step, can try to find highest likely matches & detect patterns in the POs so teams don’t have to update info one by one
- Extract information in line items
- Match despite deviations
What are the benefits of purchase order automation?
Purchase order creation is mostly rule-based. This enables for purchase order automation, mainly by unattended RPA bots and APAI tools. The benefits of an automated purchase order system are the following:
1. Fast processing
Robots work faster than humans. It would take less time for a bot to generate a purchase order than it would take a human staff. RPA bots, thanks to their data extraction, OCR, and NLP features, would quickly:
- Create purchase orders by inputting the data onto a purchase order template
- Compare the purchase order’s terms against the rule-engine for assessment
- Send it to the vendor’s email if approved, or to a human-in-the-loop for revision if not
RPA bots can eliminate the need for manual data entry. Moreover, they can process invoices in batches and with minimal human intervention.By utilizing the feedback-driven continuous learning features of APAI tools, the processing process can be also sustained autonomously.
Processing purchase orders must be accurate in terms of the type of the good and the quantity stipulated in the purchase request. RPA bots can create accurate purchase orders by:
- Repeating the previous purchase order if needed
- Extracting data from bill of materials and inventory software
- Sending it to the correct vendor by cross-matching the category of the ordered goods and the vendor details
- Inputting the correct delivery timeline by extracting data from the manufacturing database as to when the good will be used in the production process
The benefit of automating purchase orders is minimizing the possibility of human errors.
3. Real-time purchase order approval process
Bots work within business-rules. The purchasing manager can standardize the PO process by programming the bot to assess the purchase requisition prior to sending them out to maximize oversight. This means the bots could assess the purchase requisitions based on the:
- Total amount limit
- Quantity limit
- Previous vendor history
- Lead time and the manufacturing cycle
Suppose a purchase order doesn’t meet the criteria, the RPA bots can restrict purchasing, flag the purchase order, identify the exceptions, and automatically route to the appropriate team member per the approval matrix (Figure 3). For instance, a purchase order might concern non-approved suppliers. Real-time notifications for purchase approvals stop these purchase orders before being sent out.
An automated matching process is also crucial for a real-time purchase order approval. Issues can occur when there is a need to match one PO to many invoices, or reverse. APAI Software can solve the complications with capabilities such as line matching.
4. Data-driven insights
A purchase order software can connect with other ERP and 3-rd party apps, such as order management system, resource planning, bill of material (BOM) software, and more to extract all order-related data into one location.
The benefit is complete visibility into the purchase order workflow where decision-makers have access to all the relevant data. This streamlines the purchase order management. For instance, a metric companies might care about is supplier performance, in the time it takes them to issue an invoice after receiving the purchase order. These event logs can be tracked on the visible dashboard.
Having data-driven insights help companies get closer to reaching the ideals of operational excellence.
5. Cost savings
Automating the rule-based, repetitive tasks of the purchasing process allows companies to have the accounting team focus on important matters, such as tending to internal approvals, monitoring suspicious activities, and analyzing the financial reports.
This results in the human staff spending their time in more value-driven activities. In addition, because RPA bots are scalable, a company can rest assured that its purchase orders will keep being processed without the need to hire additional staff.
A study has shown that manual purchase order processing costs ~$500 2 per purchase order. We weren’t able to find the number of individual purchase orders companies make to create an average estimate. But automating purchase orders can result in cost savings.
Purchase order automation solution digitizes the purchase orders. This creates an audit trail for quality assurance and verification. For instance, if a team member might want to check who had authorized the previous purchase order, they can view it automatically.
Digitization also allows for digital archiving of all purchase orders. This reduces paper-based interactions and makes lookups easier.
APIs and orchestrators allow interconnections of purchase order software with other financial applications. This enables other financial tasks, such as general ledger entries, cash flow estimates, and financial reports creations, to be carried automatically via finance APIs. This helps the company save time in its accounting procedures.
7. Automated three-way matching
Three-way matching is reconciliation of:
- Invoices with purchase orders to verify
- Delivery receipts with invoices to release payment goods have been received
Automated purchase order software’s integration with other financial and supply chain applications enables real-time three-way matching that adds an extra layer of security to the purchase order workflows.
The benefit of automated three-way matching is that even if there are simultaneously multiple purchase orders, concurrent execution of RPA bots means each entire process is done in a rule-based and thorough manner.
8. Improved treasury management
Treasury management is managing a company’s liquidity. Automated purchase order processing helps with this by providing insights into the monthly order amounts, payment terms, accounts payable turnover and other metrics in the procurement process that affect treasury management.
Being able to pit such metrics against wider financial indexes of a company enables the finance managers to apply PO approvals to control spending, if the inflows and outflows do not match.
What is a purchase order?
A purchase order (PO) is a document the buyer sends the seller (Figure 1). It contains:
- The kind and quantity of the product the buyer needs
- Shipping details
- Payment terms
- Total order amount
- Buyer’s approval signature
A purchase order lays the transaction terms out and asks the seller to respect them.
What is the difference between a purchase order and an invoice?
- Purchase order: A purchase order is sent by the buyer to the seller, prior to payment and receiving of the goods.
- Invoice: An invoice is sent by the seller to the buyer. It contains the details of the transaction, which would match the purchase order if nothing has been altered in between. It binds the buyer to pay for the goods.
For more on fintech
To learn more about the technologies that are automating different finance processes, read:
- KYC Automation: 5 Technologies That Increase Transparency
- 5 Ways Expense Management Automation Can Help Businesses
- Use Automation in Each 6 Steps of Loan Processing Procedure
And if you want to automate one of your financial processes, head over to our financial services hub to find data-driven lists of vendors for different use cases.
We will help you through your vendor selection journey:
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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