That’s according to BuzzFeed’s William Alden, who obtained internal documents detailing how Palantir has struggled with some of its blue chip clients, some of which pay more than $1m per month for the company’s services.
According to Alden three of those clients, Coca-Cola, American Express, and Nasdaq, “have walked away” in the past 13 months, and Palantir’s effort to create a data sharing consortium for CPG companies “has stumbled.”
The documents also reveal that not all of Palantir’s current clients are convinced that their collaborations are paying off yet.
For example, Alden points to Michele Buck, the North American president for The Hershey Company, who indicated that the company ”did not see value from Palantir in 2015.”
A Hershey Company spokesperson told BuzzFeed that it considers Palantir “a valued partner” and stated “we have now identified areas for commercial and operational value and are targeting our efforts there,” but Alden’s story highlights a number of challenges that companies are facing as they seek to take advantage of Big Data.
Big data requires people
Companies have more data than ever, but data on its own only becomes truly valuable when it’s translated into actionable insight.
One of Palantir’s selling points is that it has the brilliant people required to do just that. But even with more than $2bn in funding and access to the Silicon Valley labor pool, the company has apparently struggled to retain employees.
According to Alden:
A chart from Palantir’s internal wiki said the departures through mid-April amounted to 5.8% of all staff, or an annualized rate of 20%. That compares to a departure rate of 13.6% in 2015, 12.2% in 2014, and 9.2% in 2013.
Domain expertise is often important
But delivering actionable insight isn’t just about having butts in seats. It’s about having the right butts in seats.
Coca-Cola conducted a pilot with Palantir in 2014 that was designed, in part, “to help revive sales of Diet Coke in North America through analysis of customer data.”
But the beverage behemonth ultimately decided not to sign a five-year agreement with the big data analytics firm.
An internal email from a Palantir executive revealed that Coca-Cola “wanted deeper industry expertise in a partner” and that the brand’s staff often found it hard to work with Palantir’s team which, like many companies in Silicon Valley, skews young.
Data is cheap but Big Data analytics is expensive
Then there’s the issue of cost. While generating and storing data is increasingly cheap, hiring a company like Palantir to make sense of it isn’t.
Coca-Cola “balked” at the contract Palantir presented, which called for $18m in fees in the fifth year of the deal.
And Kimberly-Clark, when presented with an agreement that also called for $18m per year in fees, also got cold feet. According to an email from a Palantir executive, the CPG giant “wanted to see if they could do it cheaper themselves.”
That makes sense. After all, if Big Data analytics can really move the needle in a big way, wouldn’t companies like Coca-Cola and Kimberly-Clark want it to become a core competency?
Paying a third-party, one which may not have industry expertise and also faces staff turnover risk, might be easy, but it seems like a short-sighted strategy.
The Palantir response
Palantir has taken steps to address staff turnover issues and suggests that its turnover is expected given that its “really strong culture” isn’t for everyone.
It can also point to seemingly successful relationships like those it has with oil company BP, bank Credit Suisse, credit card processor First Data and insurer Axa.
Palantir’s 10-year deal with BP could be worth more than $1.2bn.
One Palantir business development rep felt that executives at American Express were “low-vision,” a reminder that shared vision and values, not just technology and smarts, can make or break relationships for firms like Palantir and their clients.
Finally, according to Palantir co-founder Joe Lonsdale, who is no longer involved in the company’s day-to-day operations:
[Palantir] had been expansive in who it worked with and then scaled with the areas that made sense and were aligned with its ethos and goals. Of course a few of its client relationships might not have worked out – if that wasn’t the case it would have meant they weren’t exploring new industries properly.
That is perhaps the key take-away for brands exploring their Big Data opportunities.
As the number of third parties offering products and services that promise to turn Big Data into big bucks grows, brands should remember that many of these firms are themselves trying to figure out their own markets and will experiment accordingly.
The obvious risks this creates doesn’t necessarily mean that brands should bring their Big Data efforts completely in-house.
But the realistic, forward-thinking ones probably won’t put all their eggs in one basket either.