Clarifying Customer Contracts

by | Sep 30, 2024 | Legal Tech

Clarifying Customer Contracts

Computer analytics and AI can crunch through and provide insights for large volumes of data. However, sometimes it is more efficient and cost effective for humans to review and analyse data – than to spend the time and money setting up an end-to-end digital review system. That is especially the case if there are time constraints, the volume of documents/data is relatively small, and the data will take time to digitize.

Lawflex recently helped a client in the midst of a M&A transaction get clarity quickly, as to the true value and status of its customers. The company was built up by years of acquisitions of small local companies, and efforts to maintain the customer base of each acquired company. The company was proud that it had grown to a position of servicing over 10,000 customers, but it had no ability to break-down and understand what percentage of customers had out of date contracts, contracts that enabled yearly CPI increases, varying termination provisions and other variables. The client had a CRM system, but data entry over the years was often poor, wrong or absent. In the space of 6 weeks, a team of Lawflex lawyers reviewed every customer contract, to facilitate an accurate understanding by the client of its customer base. There were countless permutations in the contracts and many were poorly scanned decades old contracts (we even found one drafted in the 70’s). We reviewed the contracts, entered data into spreadsheets, in the process identifying many errors in the client’s CRM system, instances of expired contracts, conflicting clauses and more. The Lawflex team’s human driven review and analysis enabled contract information to be accurately processed by computer driven analytics and provide the required insights and understanding – quickly and cost effectively.

Lawflex’s client was grateful for the human-computer driven process. The CEO of the company that engaged us, commented at the end of the 6 week period, that he didn’t actually think we would achieve the task he had set us, until we did.