The 2022 Magic Quadrant for data analytics service providers indicates a form of standardization of the offer. What about it? We no longer talk about software or services but about assets. Gartner highlights this trend in its latest Data Analytics Quadrant. Under the label “severe”, it explains how the first two converge in the form of more or less standardized bricks, sold as is or integrated into consulting and integration services.
Under the data analytics banner, the American firm takes into consideration these consulting and integration services… associated with managed services (operational management). Mainly on the following components: data management (infrastructures, applications, best practices ), BI/ analytics, DSML ( data science & machine learning ), governance, program management (resource allocation) and metadata management.
Estimated at $142 billion in 2021, the market is very fragmented. In this case, it has “thousands” of suppliers. Gartner is interested here in the “top of the basket” to “cross-functional” players capable of managing a large-scale data analytics strategy. Its evaluation criteria are mainly functional, geographical and business (customer base, revenue).
Atos And Capgemini In The Data Analytics Quadrant
Suppliers classified in the Quadrant are positioned on two axes. One is prospective (“vision”), focused on strategies (sectoral, geographical, commercial, marketing, product, etc.). The other focuses on the ability to effectively respond to demand (“execution”: customer experience, pre-sales performance, quality of products/services, etc.).
Who Is In “Serveware” Fashion?
On the server side, Gartner gives good points to:
- DXC, notably for its library of MLOps tools – KPMG for its Ignite (AI) and Sofy Suite ( low code ) platforms – PwC, among others, for its catalog of datasets – Wipro for its HOLMES platforms (automation ), Data Science Accelerator (model management) and Smart i-Connect (IoT)
- Accenture and Deloitte, the two bridgeheads of the Quadrant, are also entitled to a favorable opinion – although less assertive – on the service side.
More generally, the first stands out on its delivery capabilities, its portfolio of AI solutions and the scale of its investments (M&A, R&D, skills). However, according to Gartner, it would benefit from project methodology and the harmonization of skills. The second also has a vast AI portfolio with several specialized solutions (taxation, audit, risk, etc.). As well as a catalog of partnerships conducive to innovation and a flexible economic model. It would, however, benefit from improving its documentation and information sharing.
Pricing And Talent Management: Areas For Improvement
Accenture, like Deloitte, is at the top of the range in terms of pricing. They are not the only ones credited with a bad point in this area:
- DXC: lack of flexibility, particularly for target-based pricing
- EY: more expensive than many competitors, in particular, because onshore has to be paid for
- IBM: among the most expensive, and pricing remains complex, even if it has opened up to risk sharing and target-based contracts
- NTT DATA: perceived as expensive, especially during tender phases
- PwC: high price and contextualization to be improved
Several suppliers stand out for their sectoral expertise. Among them are Tech Mahindra (Gartner praises its organization across five verticals), Cognizant (“capable of covering particular uses”) and PwC (“more than 650 solutions covering more than 5,000 use cases”).
Another point of distinction for several providers is their talent pool. For some, there are both positive and negative aspects.
DXC, for example, quickly provides access to its resources but must adapt them to an acquisition (that of Luxoft). Wipro benefits from a more favorable opinion on recruitment and reskilling than on the provision of staff. At HCL, it is the expertise in business transformation that needs to be improved. In the same vein, Genpact would benefit, explains Gartner, from strengthening its non-technical skills (change management, governance, decision support, etc.). As for Infosys and Tech Mahindra, the proportion of offshore staff is significant to be taken into account for delivery.
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