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Outcome-driven pricing model in analytics. Does it really work?

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Outcome based pricing model, popular in US, UK market gained traction but does it have any credence in India? Analytics India Magazine caught up with industry experts from Teradata and The Smart Cube who weighed in on the topic. A Cognizant whitepaper indicates, there is a new breed of buyers who are looking for output- and outcome-based commercial pricing constructs and this could be a sourcing paradigm of the future.

Analytics vendors are no longer viewed as suppliers of solutions. As enterprises across industries grapple with disruptive technology, shifting market dynamics and economic uncertainty, companies are increasingly looking for other sourcing arrangements with service providers that would lead to measurable results.

Outcome based model vis-à-vis traditional model

So far, in a traditional model, the client procures inputs — person hours, capacity or other components from a vendor for a specific time period. However in the outcome based pricing model, the vendor takes overall delivery responsibilities and is also accountable for delivering pre-defined outputs or outcomes.

According to Sameer Walia, Co-founder and Managing Director, The Smart Cube, in an outcome-based model, the focus is on accomplishing a pre-determined target. Citing a use case, Walia elaborates, “For example, there has to be a reduction in checkout time at the store due to optimization of the store layout design. The client is not concerned about what it takes for the vendor to achieve that target. In the traditional model the vendor estimates the workload, timelines, etc., and builds a cost estimate. The implementation of the outcome is left to the client. In the instance stated above, the client will now have to use the analytics, wrapping around processes and technology, to reduce store checkout times”.

Now, in a traditional headcount based model, vendors lack the necessary ownership across the IT value chain to take necessary optimization. Also, there is a very little incentive to push the envelope leading to reduced profitability.

Outcome based model minimizes risk

So, what’s the upside here – it does help companies who are assuaged by the fact that the vendor has a big stake in ‘making things happen’ – i.e., the delivery risk is minimized. For vendors, this means that they can truly get a slice of the value that is added and it’s not just a cost-plus margin pricing, shares Walia.

Data warehousing behemoth Teradata follows on outcome-based pricing model for few global clients. Talking about the uptick in the trend, Rajesh Shewani, Head – Technology and Solution Architecture, Teradata India, said, “We got a few clients in UK in financial services and the telecom sector where it has effectively been utilized. In India, what’s happening is people are not fully aware of the value that analytics can bring. But there are some mature industries like banking, telecom that are early adopters and even the Government is trying to get a feel of what it can do.”

In fact, Happiest Mind’s Air Audit Solution follows an outcome based pricing model where the airlines pay a percentage, based on the revenue leakage identified by our solution. Happiest minds built an analytics solution — Air Audit, tailored for players in the travel sector. Air Audit, an analytical application is developed to help travel agencies prevent unnecessary GDS distribution costs and inventory spoilage caused by non compliant booking practices for Airline customers.

Citing a use case, Shewani explained — customers who are interested in the Analytics as a Service model will go for the outcome-based model. An insurance client would share data on a daily/weekly basis and based on this data, the vendor would share outcome about at-risk customers who don’t want to renew the insurance. “In this scenario, the customer will only pay for the outcome. They will not buy a data warehouse. The vendor will charge them as per the outcome on a periodic basis a period that could be monthly, quarterly yearly or so on.  “

Not getting the end value of data analytics through traditional models

It’s a view that is seconded by Walia as well. While data and analytics has gained massive traction over the last years, not many clients are able to realize the end value.  Seconding Shewani’s opinion, Walia says, “If the difficulty is in making a sale of analytics services then the outcome-based model can only help to a limited extent. The client not buying is perhaps driven by many other factors, including a fundamental lack of understanding of the impact of analytics.”

In an age of SMAC stack, outcome based model provides more agility and leads to improved performance on top and bottom lines. Organizations are facing technology disruption and there is a renewed demand for agile IT. Research indicates that clients are clamouring for non-headcount based models and want end-to-end ownership of analytics delivery. Companies are looking for partners who can give outcome and output based results over time in managed services. However, Walia believes the trend has not caught on in India or Asia as yet. “I don’t see it become prevalent in the next 2 years, at least,” he said.

Outlook

Diminishing IT budgets, uncertain global environment and the rise of automation has raised the expectation of doing more with less. The procurement landscape is undergoing a change and future outsourcing deals will become more output based. Outcome based pricing model also ushers in accountability, transparency and ownership.

Happiest Minds Sethuraman Janardhanan believes that outcome based pricing in analytics is poised to be a reality in the near future. He reiterates that pricing models that are reflective of the business value generated. By following an outcome based model, future costs can be curtailed. However, in analytics space there is one downside – to render results, there has to be enough supply of historical data over a chunk of time to account for accurate results.

 

The post Outcome-driven pricing model in analytics. Does it really work? appeared first on Analytics India Magazine.


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