Key takeaways from the blog
Professional services businesses, such as accounting, management consulting, legal, human resource management, and security and compliance, face challenges in organic growth. Their profit stakes are high; however, their profit realization or cash flow is significantly slow. Detailed due diligence reveals that manual process inefficiencies build into mammoth delays in profit realization, often in months, that ultimately create a strain on the business’ working capital and limit the organic growth.
Analysts such as Forrester say, "Significant cash flow is hindered due to inefficient billing and payment processes, poor visibility into financial data, and high days-sales-outstanding (DSO) metrics." Blocked cash flows are a bigger threat to the business’ sustenance, often significantly larger than customer churn. Here, intelligent automation or AI-driven automation eliminates your biggest revenue impediment, ensuring that every hourly billed record becomes cash collected.
Systemic process inefficiencies, usually traced back to slow and error-prone human operations, block cash flows in professional services businesses. Some of the manual processes that heavily impact revenue realization include revenue leakage, delayed billing, and slow collections.
AI-driven automation is a convergence of robotic process automation (RPA), artificial intelligence/machine learning (AI/ML), intelligent document processing (IDP), and generative AI (GenAI). It serves as an efficient vehicle for unlocking cash flow and realizing trapped revenue. Some of the key nodes in the AI-driven order-to-cash (O2C) conversions and cash realization are auto-project governance, automated invoice generation, AI-driven cash application, and cash flow forecasting.
Auto-project governance:
Scenario 1:
Professional services consultants, who work on the customer side, find it challenging to log their time sheets. It amounts to non-compliance and results in costly billability losses.
AI-driven tracking mechanisms track email, Outlook calendar, and note-taking activity to auto-generate the daily time sheet logs. It results in up to 98% accuracy in timesheet updates, reducing lost billable hours, and thereby generating almost 10% more billed hours per consultant.
Scenario 2:
Often, professional services projects encounter scope creep that transgresses the contract terms and approved budgets. This is a common professional services project phenomenon leading to unaccounted revenue leakage.
AI-driven mechanisms analyze the project contracts and the corresponding approved project budgets to predict scope creep. Timely alerts enable the project managers to raise change orders and convert the project scope creep into sanctioned revenue.
Scenario 3:
Consultants find it challenging to have their expenses processed accurately and in a timely manner on the customer’s side. Stagnated expense reports become difficult to track in expense audits, which also contribute to revenue leakage.
AI-driven solutions and IDP enable professional services consultants to extract the out-of-pocket expenses on the fly and track non-compliant or duplicate expense sheets, thereby having faster expense sheet processing and minimizing disputes.
Automated invoice generation:
Scenario 1:
In the case of professional services, the monthly account closures are cumbersome. Aggregating hundreds and thousands of approved timesheets and expense sheets, and then applying the respective rate cards, is a lengthy process. Besides, each day, which adds to the DTB, further increases the DSO. Such scenarios unnecessarily drag the cash realization by weeks.
Automating the O2C cycle using RPA bots simplifies such complex scenarios that impede cash flow. It aggregates the different supporting sheets and rate cards using business rules and quickly generates invoices. Automation accelerates the monthly closures and reduces the DTB by nearly 90%, thereby positively impacting cash flow.
Scenario 2:
Invoice reconciliations between the professional services companies and their customers are associated with frequent heartburn. Manually resolving invoice mismatches can raise disputes and, at times, negatively impact the ongoing customer projects.
AI-driven invoice reconciliations eliminate mismatches in invoices, service orders, and rate cards, and route only the exceptions for human review and handling. Associated audit trails reduce customer disputes and improve the invoice processing cycle.
Scenario 3:
Invoice distribution or invoicing through traditional manual methods leaves gaps for the recipients to deny having received the invoice. It falls out of tracking mechanisms and impairs the cash flow.
AI automation solutions that include RPA frameworks augmented with AI algorithms raise e-invoices to customer accounts payable (AP) portals while generating a fool-proof audit trail. The mechanism reduces DTB and reinforces the customer’s payment terms from day-1.
O2C optimization:
Scenario 1:
Cash collection is a reactive and subjective manual process in traditional O2C frameworks. It gives equal importance to low-risk, high-risk, and high-value collections. It leads to slower cash realization.
AI-driven cash collection generates a risk score depending on the customer’s payment history and assigns automated follow-ups to high-value and high-risk cases first through a greater number of automated reminders. It reduces DSO by approximately 25 to 30%.
AI-driven cash application:
Scenario 1:
Manually matching incoming payments to open invoices is a time-consuming and error-prone activity. It is human resource-intensive and lacks real-time cash visibility. Accounts receivable (AR) resources face undue challenges in cash application during book closures.
Here, RPA and IDP-driven solutions read the remittance statements and payment amounts received and match them with the correct open invoices in the ERP systems. It accelerates cash recognition, automates the cash application with great accuracy, and offers high cash visibility.
Cash flow forecasting:
Scenario 1:
Human resources find it challenging to forecast cash flow based on static data in multiple different siloes by using a simple spreadsheet-based forecasting solution.
AI models collate data from multiple business systems to predict cash flow with high confidence. It helps to predict cash inflow and outflow with high accuracy.
Scenario 2:
Anticipating real-time liquidity using traditional approaches is difficult. Identifying future cash shortages for investing in new ventures or reducing payables is also challenging.
AI models help businesses to create simulations of how one variable can positively or negatively affect existing and future business scenarios, to ensure adequate liquidity.
Additionally, the AI-driven automation solution stops revenue leakage due to bad debt write-offs by nearly 20%, which translates into millions of dollars in terms of revenue savings. As a result, the AI automation pays for itself and generates RoI in weeks and unlocks massive cash gains that improve the company’s financial status.
AI-driven automation solution positively impacts the professional services businesses in many ways beyond P&L. Some of the strategic advantages of AI automation are:
The roadmap for AI automation for cash flow optimization involves definite phases:
In the professional services landscape, cash flow is at the core of consultant retention, innovation, and business expansion. Process inefficiencies and revenue leakage are detrimental to business sustenance. AI-driven automation is a proven solution to unlock cash flow by bridging the gap between professional services delivered and the cash realization. By using AI automation for project governance, invoice generation, O2C optimization, cash application, and cash flow forecasting, the professional services business can unlock cash worth millions of dollars that directly adds to the working capital and achieves a significant RoI within a few weeks.