How Intelligent Document Processing for Invoices Improves Enterprise Expense Management
Expense management is vital for every business, especially as we head into the next recession. NLP and computer vision-based software makes it easier to analyze and manage spend. Here's how.
Key Takeaways
Expense management refers to the process of tracking and managing vendor and payroll expenses. It has been done forever—primarily through manual methods.
Proper expense management is crucial for businesses that want to scale—even in a tighter funding environment. Managing expenses can be a great way to improve operating margins.
Expense management has different components of which vendor spend management is a very significant one. Vendor spend makes up a large portion of business expenses. Tracking vendor spend and deriving actionable insights from it are key to a successful expense management strategy.
Most of the important vendor spend data lives in semi-structured, often messy and visually-rich invoices. While processing invoices manually to extract this data is an option, doing so is tedious, not highly accurate, and inefficient. The best way to process invoices for vendor spend analysis is using AI solutions like Intelligent Document Processing (IDP).
IDP platforms can extract, categorize, and export data found in semi-structured documents like invoices. This data is clean and accurate—typically more accurate than via human data entry—and optimal for accounts payable and data analytics software.
Glean AI, a company I co-founded a few years ago, is one such comprehensive accounts payable solution for high-powered finance teams. Glean uses LayoutLM to perform intelligent document processing on invoices and delivers actionable insights about vendor spend. Glean’s vendor spend analysis helps businesses save and negotiate more intelligently with vendors.
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“A $20 Billion Startup Fueled by Silicon Valley Pixie Dust”
Such bitter words for a unicorn startup seem unfair, especially when the said startup is at its prime. But The Wall Street Journal was not wrong in calling WeWork “Silicon Valley Pixie Dust.” Just two years after this article was published, WeWork filed for an IPO and its valuation tanked soon afterwards. The CEO and co-founder Adam Neumann was to blame. The story is now infamous and has been retold via articles, books, documentaries, and TV shows as a cautionary tale for VC-backed founders and operators.
Adam’s reckless spending habits and a blatant disregard for expense management was one of the biggest reasons for WeWork’s downfall. And while there are plenty of lessons business owners can take home from the rise and fall of WeWork, one of the most important is how businesses, particularly startups, should be conscious of their spend.
Expense management is not a new concept. Today, with numerous AI tools to help track key metrics such as vendor spend, payroll, and revenue, managing expenses even in a tighter funding environment is not too complex. Yet, many businesses seem to do it poorly due to a lack of easy-to-use tools for tracking their expenses and the knowledge about such tools.
Let’s explore the importance of expense management and how business owners can use AI to efficiently analyze expenses and manage them.
What is Expense Management?
Expense management refers to the process by which businesses keep track of their key vendor and payroll expenses and manage them daily.
Every business does expense management in some way — older businesses prefer the traditional spreadsheet-based methods while newer ones make use of AI. Expense management is also referred to as cash flow management and spend management.
Why is Expense Management Important for Businesses Today?
Most startups at their peak enjoy easy funding, healthy sales, and growing customer interest. WeWork, for example, was able to score billions of dollars in funding and a growing interest from professionals looking for shared co-working spaces. Radio Shack, Quiznos, Pan Am are all examples of such businesses that once soared high but failed to manage expenses.
But why does this happen? Why do business owners lose track of how much money they are making versus how much they are spending?
First, when a business grows rapidly, it derives abundant interest from investors and getting cash is easy—such as in the summer of 2021. When cash comes in easily, not enough importance is placed on it because, even if the business ends up exhausting the funds raised during the prior round, it can always go back in the market and ask for more. Chances are the business would get that cash pretty easily, which is what happened every time WeWork went to investors. The spigots of funding kept running.
Second, during the growth phase of a business, it seems more sensible to focus more on hiring a star team, giving out the best employee perks in the industry, getting the best technology, investing in top-quality marketing, sourcing products from the best-in-class vendors, etc. Concerns about cash flow and profitability do not creep in until the business has remained unprofitable for a long period of time (and the path to profitability becomes doubtful).
But here’s something every new business owner should keep in mind: Every dollar spent is a dollar you have to raise. Your business might have lots of potential. But when we are in an environment like today where monetary policy is tighter and inflation is at a relative high, investors are highly cautious. Raising funding is not as easy as it was a year ago. The best solution is to be prudent with every dollar you have.
Expense management is crucial for every business today. Analyzing and managing spend in a timely manner is the only way to effectively control cash flow and survive a recession with decent operating margins.
How Does AI Help with Expense Management?
Artificial intelligence can be used to enhance expense management in several ways. For example, different types of AI tools can be used to analyze payroll expenses, credit card expenses, and invoice spend. One of the most significant ways to use AI for expense management is using it for Vendor Spend Analysis.
AI-powered vendor spend analysis is one of the most efficient ways for modern, scaling businesses to take control of their expenditures and weather the storm of a global recession. Before we dive into these AI solutions and why they make more sense over traditional expense management methods, let’s first understand why business owners need to care about vendor spend management in the first place.
Vendor Spend Analysis and Expense Management
Vendor spend refers explicitly to the amount of cash businesses spend on external vendors for sourcing products or services. Vendors refer to not only contractors or other physical businesses but also refer to the SaaS products or inventory supplies you purchase for your business.
These expenses make a huge portion of the overall expenditure for businesses and are usually contained in invoices. For example, if you purchase a product from a manufacturer, they will send you an invoice with all the details of the purchase in it. On the surface, this invoice is just for your records and for you to make the payment. However, the data it contains is detail-rich and a crucial part of managing expenses.
Analyzing this invoice data can give you insight into the amount of money you end up spending on a particular product or service and the value or material profit it delivers to your business. This process is well-established, and businesses have always done it, albeit manually.
Most traditional businesses perform vendor spend analysis just a few times annually. While doing that is useful to an extent, something as important as vendor spend data should be analyzed much more frequently.
Lack of regular invoice assessment and analysis can cause a host of problems. If there is a vendor on whom you are overspending, your annual vendor spend analysis is when you will detect the problem. By then, you will have already burned a huge chunk of cash.
Good vendor spend analysis can help businesses:
Identify opportunities for growth and saving cash
Reduce zombie spend
Remain on budget
Assess vendor risk
For business owners to be able to manage expenses effectively and avoid unnecessary cash burn, they need to invest in modern, faster, more accurate, and more regular vendor spend analysis.
AI-Powered Vendor Spend Analysis — The Future of Better Expense Management
Businesses have always done vendor spend analysis. But traditional methods involve human employees extracting data from invoices, mapping and categorizing it, putting it in spreadsheets, and then using charts to generate insights. This manual process is incredibly time-consuming, prone to errors, and generally inefficient.
That’s where automated or AI-powered vendor spend analysis comes in. Many AI tools exist at the CRM level to help with revenue and sales analysis. But very few cater to expense management.
While a lot goes into expense management, in this article, we will discuss vendor spend analysis because it is particularly ripe for AI software to solve.
Spend analysis can involve tedious data extraction and categorization, which have been manual for a long time. But with intelligent document processing tools, there is room for AI to dramatically improve and enhance this part of expense management.
For example, extracting the data such as line items, amounts, vendor name, and vendor address out of invoices and labeling it is complex. Intelligent Document Processing platforms can do all of this efficiently before cleaning this data and passing the relevant pieces of it to a data analysis program, which can then generate analytics that help you with expense management.
Why Use Intelligent Document Processing for Invoice Processing?
Intelligent Document Processing is the best way to approach invoices for vendor spend analysis. Here are a couple of reasons why.
Accounts payable solutions are a critical part of expense management for most modern enterprises. Modern accounts payable software requires structured digital data. This data is contained in invoices. Getting this data would be extremely easy if all the vendors were on a uniform, electronic invoicing network. But this is not the case — instead, invoices come in a lot of different variations.
A templating approach to invoice extraction requires too much maintenance and is not effective at scale. To use templating, you would need thousands of templates, updated every few months.
Different invoices have different structures, and all of them are semi-structured documents. Using a robotic process automation software to extract the data from such documents is also not effective for the same reasons templating is not an effective solution.
Using simple OCR to extract data from such semi-structured documents is effective, but businesses would still have to classify it manually before it becomes fit for accounts payable software. Manual accounts payable data entry and verification takes a huge amount of time and money.
As demonstrated by a Forrester survey, about 47% of businesses continue to use paper-based invoices, at least partially. Such invoices are even more challenging to process using traditional electronic or manual methods.
IDP software can extract, identify, and categorize all the semi-structured data contained in invoices with stunning accuracy and in record time. Whereas manual methods and even RPA software can take several minutes to perform these tasks, most IDP systems can do it in just a few seconds.
Also, because IDP primarily functions using machine learning, results improve over time in terms of both speed and accuracy. Since any machine learning or AI-based software is only as good as the data that it learns from, IDP-based accounts payable solutions also work better with more accurate and better labeled data.
Glean AI is a great example of such a tool. It is not just an intelligent document processing or data extraction platform. Rather, it is a complete spend management tool that can help you process invoices and use invoice-derived data for vendor spend analysis.
Glean also automates data extraction, GL coding, bill approvals & payments, prepaid amortizations, and more. Let’s understand a bit more about how Glean works and in what ways it can help your business.
Glean AI — A Comprehensive Vendor Spend Management Platform
Glean AI is an accounts payable platform that helps businesses understand vendor spend in real time. Glean also surfaces vendor spend insights and benchmarking, helping businesses negotiate with vendors better.
Glean AI works on the principles of intelligent document processing and machine learning. Intelligent document processing, or IDP, at Glean is carried out in two major stages:
Extraction: Performing optical character recognition on semi-structured invoices to extract text data such as dates, addresses, due dates, amounts, line items, vendor name and addresses, etc. Extraction is followed by classification of each data into Glean’s custom schema.
Mapping: Linking the raw text for vendor name and address and line item descriptions to their canonical forms before using this information for deriving insights and analytics.
Both extraction and mapping use natural language processing and computer vision to classify the data. These technologies help Glean deal with the high volume and variety of data effortlessly — something humans would struggle with.
How Glean AI Uses LayoutLM for Processing Invoices for Vendor Spend Analysis
Glean uses LayoutLM, a pre-trained IDP model perfect for processing semi-structured, visually-rich documents like invoices. It considers the text and document layout information in context with the image information. In fact, LayoutLM is one of the first models that consider all three effectively.
LayoutLM works by first performing OCR and then using the image and layout embeddings to extract the data. Afterwards, using its pre-training on the IIT-CDIP test dataset, it labels the data.
Even though LayoutLM is pre-trained and gives better results than benchmark NLP models like BERT and RoBERTA, it does need to be fine-tuned to process custom invoices. Glean manages the fine-tuning and feeds the model with its own data collected from invoices processed to make it more and more accurate.
Using LayoutLM for invoice processing lets Glean fully customize the IDP architecture to an enterprise’s custom requirements. Moreover, it also helps with better benchmarking.
How Glean AI Helps With Better Expense Management
Glean’s intelligent vendor spend analytics helps businesses decode:
The sudden increase or decrease in vendor spend for a particular vendor or industry
Key vendor cost drivers, unit prices, volumes ordered, etc.
Efficient procurement and budgeting
Collaboration with the main stakeholders both internally and externally
Savings (Glean’s savings recommendations) and payments
Glean also supports multiple integrations with business management, accounting, and financial software to facilitate seamless payment and general ledger synchronization.
Sturdy Exchange, one of the businesses that uses Glean for its AP management, admits how using an AI solution like Glean allows them to save when they are just in the build phase. The accuracy that comes with Glean’s vendor spend insights eliminates unnecessary expenses and allows quick financial changes.
What Other Financial Verticals Can Intelligent Document Processing Improve?
While we have explored how IDP helps with invoice processing, which is a critical part of expense management for businesses, there are other areas where IDP is valuable. IDP can help businesses better manage spend in all of the following areas:
Analyzing receipts and managing accounts receivable
Purchase order analysis and comparison for better negotiation
Processing bank statements to extract data for record-keeping or tallying expenses
Extracting significant employee expenses
Analyzing credit card spend
Conclusion
Using artificial intelligence for expense management is convenient and cost-efficient for businesses that are scaling rapidly. Manual methods are not just tedious but also prone to errors and not as timely as expense management should be. With solutions like Glean AI, it is easier for all business owners to incorporate AI into their everyday expense management.
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Here is a bit more about my experience in this space and the two books I’ve written on unsupervised learning and natural language processing.
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