What does Machine Learning mean for a technology services vendor?

Machine learning is disrupting Zensar's business model in the short term but also creating significant opportunities over the medium and long term

Zensar Technologies is a Technology Services Company headquartered in India that provides information technology (IT) services such as application development and maintenance, testing, and infrastructure management. Zensar serves clients in the retail, manufacturing, insurance and high-tech space across the globe. Zensar is part of the Indian IT services industry, which is a $170b industry growing at 7-9% annualy[1].

Traditionally, IT services companies have operated in an extremely labor intensive and linear business model helping customers manage legacy hardware and software. Over the last 3 years the IT landscape has changed given the increased adoption of cloud and digital solutions and the enhanced focused that enterprises have towards customer experience. Given this shift, Zensar has been trying to pivot its business towards providing next generation technology services such as cloud, artificial intelligence, and machine learning to drive customer experience for clients. In the context of IT services, the evolution of machine learning and AI ranges from the automation of manual tasks to the eventual use of self-aware systems[2].

These industry dynamics have differing short term and long term implications for Zensar. In the short term AI and automation have resulted in a significant headwind for Zensar’s existing projects. Clients are dropping prices because they expect Zensar to execute legacy work at lower costs and with fewer resources. In addition, all the incremental IT spend is shifting away from legacy solutions (ERP, on premise software) towards new-age solutions (mobile app development, augmented reality, data analytics, etc.). This has led Zensar to report eight quarters of consecutive negative / muted revenue growth and a decline in operating margins by 4%[3]. In the long run, the use of AI and machine learning could open up new avenues for IT services companies to improve customer experiences and enhance process efficiencies.

In order to pivot the business towards providing AI and machine learning Zensar replaced its CEO in 2016 and launched an intensive training program to re-train its 8,500 labor force[3]. Furthermore, Zensar acquired four companies over the past year to increase its presence in digital technologies, machine learning and data analytics. These new technologies now comprise 35% of overall revenues.

Zensar has also identified opportunities that require investment over the medium term. The company has set-up a dedicated research and development team to develop differentiated AI and machine learning solutions. Last year the product team launched Zensar’s first such offering called ZenAnalytica, an integrated platform that converts data into business insights using an autonomous engine for data crunching. ZenAnalytica has a suite of over 30 business apps ranging from predictive analytics, business intelligence, recommendation engines, etc. An example of a use case is when the platform helped a retail client in Africa increase sales via cross-sell and up-sell. Using algorithms and machine learning, ZenAnalytica identified correlation patterns and generated insights on purchasing patterns of products frequently bought together. This project led to a 33% increase in revenue and 15% increase in order size per customer[4]. These initiatives are only a small step towards what will be an organization wide overhaul towards digital solutions including artificial intelligence and machine learning.

Although Zensar is investing in AI and machine learning it is still approaching the problem from a services point of view. So far the company has made marginal changes and has not done enough to radically transform the company. I believe Zensar will need to increase capital expenditure (currently only 2% of revenue) to bring it in line with software companies (6-8% of revenue) and launch cutting edge products that have a sustained competitive advantage. Currently, Zensar is focused on niche use cases and is not thinking of an enterprises overall AI needs. These changes will require an upgrade of talent, organizational wide cultural change, and a board of directors focused on long term value creation.

The path forward for Zensar is uncertain given the massive transformation required for the company to not only compete against their traditional IT services competitors such as Accenture but also well-funded start-ups that are born in the “AI age’’. I would like to get a perspective on whether investing in AI and machine learning is the right path for Zensar given the competitive landscape. Is the pace of innovation too rapid in AI and machine learning for Zensar to remain competitive? Should the Company pursue a different / less radical business strategy? Additionally, what are the challenges of transitioning a services oriented company towards a product based software business?

 

[1] “Indian IT to Clock 7-9% Growth in FY19, Job Creation to Remain Flat: Nasscom.” The Economic Times, Economic Times, 20 Feb. 2018, economictimes.indiatimes.com/tech/ites/indian-software-services-sector-to-grow-7-9 in-fy19-nasscom/articleshow/62995685.cms.

[2] The AI Era: Artificial Intelligence Fusing Man and Machine, CLSA, May 2017

[3] Zensar Technologies, 2017 – 2018, Annual Report, https://www.zensar.com/investor/reports

[4] Increased Retail Sales via Cross-Sell and up-Sell. Zensar Technologies, pp. 1-2, Increased Retail Sales via Cross-Sell and up-Sell.

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3 thoughts on “What does Machine Learning mean for a technology services vendor?

  1. Fenomenal article. Impressed how the change of CEO from 2016 was possible to capture 35% of revenue in a new business market, and result in successful transformation for the business.
    I would like to point out my concern about “ZenAnalytica has a suite of over 30 business apps ranging from predictive analytics, business intelligence, recommendation engines, etc”. Having a business with already that quantity of apps seems to me a bit lack of focus, and also the need for manual work to input data, that makes it even more probable not many of these 30 apps will survive.
    So going into the questions of the article, I would say that investing in AI and machine learning is the right path for Zensar, however I would try to narrow a bit the objectives and how to attack the problem instead of so many options. But investing, is extremely critical for the survival of the business. I would even try to expand the revenue more than 35%.

  2. This is a great article, interesting information!
    It’s interesting to see how IT services companies are having to revamp their service offerings to meet market changes. I believe Zensar is doing the right thing investing in these technologies given that, as mentioned, other services are becoming commoditized and customers are requesting cost reduction or they can move to other competitors.
    I believe that Zensar can further differentiate itself and retain customers by coupling their existing services, such as ERP systems, with analytics and machine learning. Zensar can bundle products in order to cross sell these services by offering discounts. For example, for ERP, Zensar can provide workforce management analytics for the HR module.
    In addition, I believe Zensar can focus on targeting markets where analytics offerings are still nascent (e.g. Middle East) specifically given that these services can be provided remotely and that Zensar can compete on pricing, benefiting from experienced employees and from lower labor costs.

  3. Very interesting article. I have experienced this trend as well in my previous work. Our relationship with our IT service vendor mostly encompassed traditional enterprise application integration. But towards the end of my tenure we saw a shift in this relationship as our vendor increasingly pushed its data analytics and resource planning services, both backed by AI. I definitely agree that the future of these firms will be in analytics and AI. However I do think it will be hard for companies like Zensar to be competitive in this space given how rapidly the space is evolving. I think the value a firm like Zensar can offer is more in the nuances of implementation than in the actual development of AI. Thus I think focusing on niche cases might be a sustainable way to grow in the space for now.

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