How Many Beans Does a Bean Cost When You Manually Count Beans
- 1 How Many Beans Does a Bean Cost When You Manually Count Beans?
- 2 The Costs of Processing Sales Orders, Purchase Orders, and Invoices
- 3 How to Use Machine Learning for Processing Invoices, SOs, and POs
- 4 Machine Learning vs. Manual Processing of SOs, POs, and Invoices
- 5 Subscribe to our blog for the latest industry trends
How Many Beans Does a Bean Cost When You Manually Count Beans?
Sales orders (SOs), purchase orders (POs), and invoice processing can be quite costly to a business, with the processing costs cutting into a company’s profit margin – sometimes, quite significantly. Moreover, the sheer volume of these documents can make manual SO, PO, and invoice processing a somewhat overwhelming task for accounting staff. This is especially true when these documents are all mission-critical and time-sensitive. As such, they tend to garner attention, mainly when an error or delay occurs. But there is a solution, and it comes in the form of machine learning (ML). Machine learning technology can simplify invoicing, sales order processing, and purchase order processing.
The Costs of Processing Sales Orders, Purchase Orders, and Invoices
The actual costs of purchase orders, sales orders, and invoice processing can be significant, especially when the accounting team is forced to push other tasks aside to expedite the process. After all, invoices are what your company needs to get paid! The same is true of sales orders, while timely and accurate purchase orders allow you to remain in the good graces of your company’s clients/customers.
The actual SO, PO, and invoice processing costs include the following.
- Training staff to manually process invoices, SOs, and POs carries a cost, both financial and time-wise.
- Staff must spend time manually inputting data into the form in question. It’s time that could be spent on more productive, higher-level tasks.
- Data on these accounting documents must be audited and verified. This takes a fair amount of time, and there is a risk that a human reviewer could miss an error.
- Human error carries a cost, too, since staff must take time to correct any errors identified in the auditing process.
- Damaged client/customer relationships carry a cost. If a flawed invoice, sales order, or purchase order is sent out, this can cause frustration and a loss of trust, which could cause clients and customers to take their business elsewhere.
Delays in sending a purchase order, sales order, or invoice can lead to delays in payment. Regardless of whether you are spending or receiving money, these delays have financial and operational costs and even the cost of damaged relationships with vendors, customers, and clients.
How to Use Machine Learning for Processing Invoices, SOs, and POs
Machine learning (ML) is a great technology for processing sales orders, purchase orders, and invoices. Machine learning allows for highly accurate data capture when combined with optical character recognition (OCR) scanning. This is ideal for cases where you have existing paper sales orders, purchase orders, and invoices that need to be digitized, making them searchable, sortable, and suitable for cloud storage.
Machine learning can also be used with a platform to compile these documents using integrations with the company’s enterprise software and third-party platforms. For example, you may integrate your platform with a point-of-sale system, ERP platform, or CRM software. The system can pull data from various integrated platforms to generate these accounting documents. This reduces the risk of human error, and you see benefits from automating the process to eliminate some or all of the need for human intervention.
Machine learning not only boosts accuracy and removes much of the burden from accounting staff but also “learns” and improves over time. This means a machine learning-powered platform can generate a greater return on investment (ROI) in the long run.
Machine Learning vs. Manual Processing of SOs, POs, and Invoices
When you compare manual vs. machine learning, invoice, PO, and SO processing, the differences are significant, and most would agree that it’s machine learning for the win.
Human error is minimized or eliminated from the equation when you can automate some or all processes with machine learning. Manual processing has an inherent and unavoidable risk of human error.
Speed is improved dramatically by machine learning. Manual processing can take 30 minutes or longer, while machine learning processing can be performed in seconds.
Cost is reduced when you maximize accuracy, minimize errors and maximize speed. That’s yet another advantage that machine learning processing holds over manual processing.
The wrong technology can be disastrous, transforming a workable process into a costly digital nightmare. To maximize ROI and boost productivity as much as possible, you need the right technology for your business and its operations. Sometimes, that may entail purchasing the technology and performing these tasks in-house. In other cases, outsourcing the company’s SO, PO, and invoice processing may be better.
At iTech, we help companies make the most of their data. This is true whether you’re seeking machine learning-powered OCR technology, a data management platform, or another data-related digital transformation project. Contact iTech today to discuss your invoicing, sales order, and purchase order-related challenges.