Information Technology Update : Analytics – From Passive Insights to Active Decisioning by PL Capital
Quick Pointers
* Underwriting decisions drive longer transformational engagement vs. scope-bound project work
* Platform-led approach builds deeper client engagement
We met the management of Mu Sigma, a data analytics and decision sciences company, to understand the AI-led structural changes underway in the industry. The management indicated that the nature of enterprise engagement, scope, and delivery has become more dynamic, which requires quality judgment at scale while embedding AI into the enterprise decision framework. The decision framework is deeply integrated and has built broader ‘institutional dependency’ instead of relying upon ‘individual deliveries’, aided by decision ontologies and knowledge graphs. Hence, the intensity of multi-faceted domain depth that the company has garnered over decades is less likely to replace against any advancements in AI. The management remains focused on operating and scaling non-commoditized service lines (Data Science and Decision Architecture), while leveraging Data Engineering largely as a support function. The company has pivoted its business mix toward continuous service as software (CSaaS), while peers are still evaluating business models to achieve better cost transparency and tangible value delivery.
Our read-through for close peers – Fractal and LatentView – is positive. Anchoring platforms and solutions within the enterprise ecosystem are helping make client relationships deeper and stickier. Although these 2 companies are yet to fully capitalize their investments in R&D and CoEs, there is a strong intent to monetize AI platforms and tools. The trade-off for these companies appears to have aggressively tilted toward revenue growth over margins. The playbook for these companies has evolved over time to include more complex upstream activities, rather than playing downstream data engineering. A similar strategy is evident in the LatentView + Databricks partnership, which is largely (~80%) focused on model training and experimentations within enterprise territory, vs. ~20% directed toward data fabric.
We believe there is a marginal business risk for LatentView, given the higher concentration of diagnostics (60% of revenue) and the insourcing risk (US$5-6mn) from its top account, which is largely factored into the CMP. Fractal on the other hand, stands to benefit through premium service orientation (Fractal.ai) and an improving annuity-led mix (Fractal Alpha), but current valuations capture all positives. We reiterate our ‘BUY’ for LatentView and HOLD for Fractal.
Structural service shift:
The industry is doubling down on high-end complex activities that involve decision accountability, risk tiering, AI governance and other activities simplifying the decision-making process
Proactive engagement improves incremental scope:
Multidomain vendor capabilities help unlock adjacencies and improve incremental scope within the same accounts. Owning and underwriting decisions with shared mentality help participate in longer horizon transformation initiatives vs. scope-bounded project-led work.
Horizontal service orientation:
The management highlighted that partnerships with database companies (Snowflake and Databricks) are deliberate infrastructure choices that allow Mu Sigma to transit the commodity layer quickly and reach strategic Layer 3/4 at a faster pace
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SEBI Registration number is INH000000933
