No such thing as pure TNM: Happiest Minds CFO on Time & Material pricing model debate

Venkatraman Narayanan, MD & CFO, Happiest Minds

Mid-tier information technology firm Happiest Minds believes that the traditional concept of Time & Material (TNM) pricing doesn’t exist in its purest form in today’s software industry. According to Managing Director and Chief Financial Officer Venkatraman Narayanan, every TNM contract carries elements of outcome-based pricing, making it a hybrid model.

“There is nothing called a true T&M. Every contract has a rate, an effort, and a defined outcome,” Narayanan told Moneycontrol. For instance, the expectation is clear if a client asks that a particular outcome must be achieved within two months at $60,000, he explained. “If we don’t deliver within the agreed timeline and stretch into a third month, no one is going to pay us extra because the statement of work (SoW) caps it at $60,000.”

The remarks come at a time when a former Wipro chief criticised the TNM model for allowing tech companies to pass inefficiencies to customers. Kurien's perspective appears to be resonating in the market, in all probability, as the IT major Cognizant recently said it has been winning large deals by sharing AI-induced productivity benefits with clients.

Moneycontrol also reported that the contribution of TNM contracts to IT firms' revenue has halved to 35 percent in a span of decades.

Narayanan highlighted that this is not a pure TNM model, rather a hybrid one. “It’s often referred to as TNM with a cap or TNM with an SoW.”

He mentioned another billing model, capacity-based, where clients hire teams and manage them directly. “In such cases, the client might say, ‘Give me 50 people, and I’ll manage them.’ My job is to wrap up the team, train them, and hand them over. But even here, the expectation is tied to deliverables, not just showing up for work,” the former CFO of the erstwhile Mindtree Consulting, TeamLease Services, and Sonata Software said.

With the launch of ChatGPT in November 2022, many dynamics changed as far as the tech world is concerned.

Narayanan explained that Generative AI (Gen AI) operates on two fronts: the input side, where it enhances efficiency in coding and development by 5–15 percent, and the output side, where it enables new capabilities for customers.

“On the supply side, generative AI impacts productivity, potentially reducing volume growth by increasing efficiency. However, this gets offset by the additional demand for generative AI-driven capabilities that we can deliver to clients,” Narayanan said.

Going forward, the balance between cost savings from efficiency and the revenue generated from AI-based offerings will determine the impact on overall growth.

Also read: Shift to fixed-price deals, Gen AI challenges IT offshore models