New Capgemini Engineering brand fuses digital and physical
With the aim of helping the world’s largest innovators to engineers the products and services of tomorrow, Capgemini has merged its tech and software capabilities with its engineering and R&D practice, the digtial and physical to form a 52,000-strong Capgemini Engineering brand. A move that builds on its acquisition a year ago of engineering giant Altran for over $3 billion.
R&D is the new battlefield
“Today’s leading organisations understand that Engineering and R&D is fast-moving and ever-evolving,” says Aiman Ezzat, CEO, Capgemini. “As a result, an end-to-end partnership with clients is need for developing, launching, managing and modernising breakthrough products.”
Enter Capgemini Engineering. A new brand that unites a unique set of strengths from across Group, bringing together the world-class engineering and R&D capabilities of Altran with Capgemini’s own digital manufacturing expertise.
According to William Roze, CEO of Capgemini Engineering, R&D is the “battlefield” and subsdquently “must be connected and data-driven to optimise innovation and accelerate development”. In answer to this, Capgemini Engineering will offer services to address this need and to “harness the power of data to foster innovation, create new customer experiences and deliver new sources of value".
Merging the expertise of the Group
With this new endeavour, Altran’s capabilities are brought to the fore, a year on from its acquisition, perfectly complementing “the Group’s already well-established portfolio of business offerings and supporting our leadership position in intelligent industry”, says Ezzat.
In fact, just in January 2021, leading global management and strategy consulting firm Zinnov ranked Capgemini as the top of its Leadership Zone for its global Engineering, Research and Development services, pinpointing how as a Group it boasts the largest global delivery network with a presence across all major engineering hubs.
With its 52,000 engineers and scientists and a presence in all major engineering hubs worldwide, the global business line’s services cover three key domains: product and systems engineering; digital and software engineering; and industrial operations.
This is the second time Capgemini has combined various practices to form an integrated powerhouse. Capgemini Invent – a strategy and business transformation consultancy was formed in 2018 by combining Capgemini’s consulting, digital and creative units.
Gartner: CFOs should use AI in a transformative way
The finance functions of organisations must invest in artificial intelligence (AI) within the next few years, so as not to be left behind. And they must think 'big' about how AI can transform their businesses in the long term.
That’s Gartner’s advice to CFOs and finance leaders. Investing in AI is not just a business imperative, adoption of which needs to be done within the next few years, it's an imperative that needs to be undertaken intelligently with a long-term vision if businesses are to gain competitive advantage.
And to do so intelligently means to look beyond projects that only aim to modernise the function. Because, while there’s nothing wrong with using AI to “modernise the finance function”, says Clement Christensen, director in the Gartner Finance practice, “the most impressive rewards of AI will fall to the CFOs who think bigger about how the technology can fundamentally change the way their company does businesses”.
According to Gartner, the top priorities for organisations when it comes to AI are as follows:
- To improve the company’s data architecture to support future AI goals
- To invest in citizen data scientists so that AI production can be rapidly scaled where successful
- To redesign the organisation’s reporting suite so that is best aligned with internal customer needs rather than with traditional ‘finance tasks’
Using AI in a truly transformative way
While most CFOs are aware that to reach their functional digitilisation goals, they need to pursue more “experimental, less familiar digital technology projects”, says Christensen, many still “follow use-case-focused approaches to AI projects that tend to have a bias towards modernising and improving familiar processes to drive easily-quantified ROI gains”.
Gartner points to a common use case of AI as being the use of machine learning to predict customers prone to late payments and issue earlier payment reminders to such customers or chase later payers automatically. Reducing late payments has a definite ROI in that it will improve the organisation’s cashflow. That said, according to Gartner, this is not using AI to do anything new, just helping to do something a bit more efficiently.
In this use case, to really make the most of AI and use it in a way that Gartner describes as “truly transformative” would be to identify likely late payers at the sales stage so that sales prospects are prioritised according to which is likely to pay more promptly. And this could transform a company’s approach to mitigating late payments and improve cashflow further while further reducing the need to chase for payments in future and ultimately freeing up finance for higher-value work.
And while this transformative use of AI doesn’t deliver an immediate and measurable ROI like that of the common use case of AI, the ultimate long-term payoff “is potentially much bigger”, explains Christensen.
To therefore get to the transformative stage, one where AI is used for long-term business transformation, Gartner advises CFOs to shift their mindset in how they think about deploying AI and to start with a problem that needs solving, rather than with a process that needs modernising.