Introduction to Flotek
Flotek is a well-established company based in the United States (“U.S.”) and focused on designing and supplying specialty chemicals to oil & gas operators. Flotek’s primary driver of profitability is a suite of chemical products called complex nano-fluids (“CnF”). CnF is comprised of high-value compounds that are used in hydraulic fracturing to enhance oil and gas production. Flotek marketed CnF among operators by promoting an oil & gas production uplift of 30% . In order to fund the expansion of CnF product offerings, Flotek decided to go public in 2007 .
The specialty chemicals industry in the U.S. was highly commoditized and there was little differentiation between specialty chemicals used in hydraulic fracturing. As the fracking boom began to unfold in the U.S., the players in the marketplace faced a much higher level of competition. Moreover, Flotek experienced sales decline, profit margin degradation, and share price decline. A group on hedge funds on Wall Street, led by FordWorld Capital Management, decided to short-sell the stock and publish reports criticizing Flotek’s CnF product in the public investor community. The short-sellers analyzed publicly available data and concluded that revenues would fall 20-30% in the near-term , contributing to a market capitalization drop of over 50% . Flotek’s management team reacted to the share price drop by redefining the value proposition of the CnF product. John Chisholm, CEO of Flotek, decided to pivot CnF product development strategy from a pure-play chemical product to a technology-driven product. Given the rise in real-time data collection in the oil & gas industry and the decrease in computer processing power cost, Flotek identified machine learning (“ML”) as a potential tool to improve CnF and provide a value-add solution to its customers .
Flotek’s Machine Learning Strategy
Flotek’s management team understood that the public markets demanded a change in the company’s product development strategy and a higher level of differentiation in the CnF product offering. To drive innovation in the short-term, Flotek opened a new Global Research & Innovation Center and partnered with oil & gas thought-leaders and researchers to incorporate ML into Flotek’s CnF product offerings . The research & development team used drilling equipment to collect real-time data from oil & gas wells in specific geological formations. The localized data was analyzed by the researchers through the ML tool to understand the relationship between CnF’s chemical mixture and oil & gas well production rates. This allowed Flotek to design a customized combination of high-value chemical compounds and maximize oil & gas well production rates in various geological formations . Operators reacted quite favorably after using the new CnF product given the increase in oil & gas well production rates and yield of existing oil & gas resources. To further develop the state-of-the-art ML technology and create a long-term competitive advantage, Flotek decided to independently work with IBM . By evaluating the existing in-house ML tool and IBM’s Watson capabilities, the researchers were able to fine-tune its customized CnF product and provide a differentiated value-add solution to oil & gas operators. Flotek was able to successfully take advantage of the ML mega-trend in the oil and gas industry to transform and differentiate its CnF product.
While the ML tool seems to enable Flotek to provide a differentiated product in the oil & gas sector, the incorporation of this tool faces a number of challenges that should be considered in the product development process. If Flotek aims to enhance its top-line growth, profitability, and stock price performance, then the management team should consider the following actions as part of its strategy:
First, Flotek should allow both the Global Institute of Research & Innovation Center and IBM Watson to combine their technologies and share the learnings associated with their product development process. This will allow the company to realize the synergies between the two technologies and optimize its CnF product development process.
Second, Flotek should provide free trails of its CnF product and ML tool to potential customers in the prolific geologic areas. The oil & gas industry has a high trialability cost and free samples will allow the company to capture large-scale operators in high-profile geologic areas.
Third, Flotek should promote its product suite of product internationally in order to scale is client base and increase the data set size. This would allow the company to have a much richer data set and enhance the ML tool’s effectiveness.
Will Flotek be able to scale its ML tool fast enough to maintain profitability and recover share price value? What other steps should Flotek take in order to propel innovation throughout its product development process?
 Flotek press release as of February 23, 2015.
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 Flotek annual report as of December 31, 2017.
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 IBM, “Transforming Oil & Gas with IBM Watson Presentation”, accessed November 10, 2018.