In the land of the blind, the one-eyed lawyer will not be king for much longer. In my view, ChatGPT is exposing lazy people compared to smart, diligent ones, and lawyers are no exception to the rule – everyone is being held to account by their ability to use LLMs properly and professionally.
And this goes to anyone in knowledge professions, such as technology, marketing, research, science, consulting, accounting, etc. You are only as smart at what you know and how intelligently you interact with the Internet to enhance your knowledge. But let’s focus on this ChatGPT disruption of lawyers because who doesn’t love to pick on lawyers?
I’ve been riveted to the cases of lawyers and ChatGPT recently, where lazy lawyers are getting smashed in the media using bad ChatGPT information. Let’s get to the point, with the current version of ChatGPT, a lot of bad information is recycled, and some people are not smart enough, or too lazy, to check it properly. It’s the same with people researching for exams or corporate presentations – if you know what you’re looking for, ChatGPT can save you a bunch of time and make you far more productive – and even appear more knowledgeable.
The technological shift from ChatGPT-3.5 to ChatGPT-4 will have a seismic impact on the legal profession
Moreover, the impending upgrade from the current version of ChatGPT-3.5 to ChatGPT-4 is seeing a ten-fold increase in information synthesis power, a much greater ability to cite facts correctly, find nuances and mistakes in information and keep refining its capabilities. In fact, one team of GPT-4 experts has claimed that while ChatGPT-3.5 came in the bottom 10% of the Uniform Bar Exam, GPT-4 passed with flying colors approaching the 90th percentile. And this is from a team of legal experts at Stanford Law School.
Lawyers: the lazy versus the skilled will be exposed
In the case of these current legal blunders, lazy lawyers are being exposed because they are – let’s face it – too apathetic to keep current in their jobs and always looking for shortcuts to bill their clients insane amounts of money.
“Strategy” is needed in cases where the law is open to interpretation and the outcome is not cut and dried. Many lawyers can be immensely valuable – and I have been in awe of one lawyer who showed more skill, emotional intelligence, and insight than I have probably witnessed in my entire career. There are also many others who are clearly diligent and smart, who I would use again.
However, I have also worked with many (and observed many) who are simply a huge waste of money. Having lived through many contractual negotiations, there is rarely any “strategy” from some lawyers. They are highly-paid billable administrators following processes and delegating most of the work to juniors to rack up the billings.
It’s these lawyers who should be very scared of GPT4, especially in areas like outsourcing where most of these contracts are cut and dried, and there is very little room for “innovation” for anything beyond keeping on the green lights.
The Bottom-line: In the land of the blind, the one-eyed lawyer will not be king for much longer
When you’re in a situation where lawyers and procurement are sparring over the useless minutiae of standard contracts, you are simply wasting hundreds of thousands (or millions) of dollars. Seriously, what is the point of paying $1m+ to draw up a valueless, standard outsourcing contract when you can find a smart lawyer who can do it for a fraction of the price using sophisticated LLMs?
The smart clients are those who know how to manage lawyers, hold them to set budgets, and know where they are useful beyond being glorified – and very expensive – process followers. And those lawyers who know how to use ChatGPT to be more productive – and continually increase their knowledge – will quickly rise to the forefront.
For example, would you go to a dentist who hasn’t read a dental journal in 20 years or uses the latest software and equipment? Or course you wouldn’t! If my lawyer was super in-tune with their practice area, I would want them to be 20%+ smarter and more productive because they know how to use ChatGPT properly. I want more for less, and GPT-4 will deliver that to those who learn how to use it effectively.
Many people have viewed Cognizant as losing its mojo over the past few years, with staff attrition among the worst in the services industry last year, a demoralized Indian organization, and a general lack of raison d’être. What had been the poster child for modern offshore-centric outsourcing for a decade and a half has struggled since activist investor Elliot Management squeezed the life out of the firm in 2017.
“Why Cognizant”. Can the poster child for spectacular offshore-centric services growth find a new raison d’être?
Fast-forward to 2023 and the firm has a charismatic new CEO at the helm, Ravi Kumar S, who is looking to reinvigorate the firm’s culture while also setting out a new course for growth in the era of The Generative EnterpriseTM. A noticeable uptick in bookings this year is already indicating that the Cognizant mojo is starting to reemerge.
Back in the good old days, the firm could do little wrong by challenging Accenture’s strategy – driving a hard-digital bargain and offering a simplified approach that many clients wanted: easy to partner with and able to deliver what they wanted at much more competitive rates. In short, many clients wanted to work with Cognizant because they loved the energy and simplicity of the firm, which was in stark contrast to the consulting-led arrogance of the transitional IT services model. Simply put, client-centricity was always the table stakes for the firm during its rampant growth days.
Cognizant had achieved what most of the industry still fails at today: Everyone understood the “Why Cognizant”, versus just the “what” and the “how”.
Sure, Cognizant, at $20bn, still has an array of outstanding capabilities, but without a clear message to the market, it has become difficult for enterprises to understand what makes the firm a desirable transformational partner that can deliver both cost and innovation impact. Winning by embracing heritage means reinforcing the three strong strengths in its roots – a confluence of industry and technology, flexibility and client centricity and entrepreneurial spirit
The firm needs a new identity, renewed direction, and a reenergized culture to reclaim its former glory. However, the precise ingredients that provided the magic formula in the past may not be the right ones in the medium-long term as the services industry faces the vast dichotomy of transforming clients at speed and pre-inflationary prices.
Enter new CEO Ravi Kumar S, former Infosys rainmaker, ready to right the ship. The HFS team descended on Cognizant’s 2023 US Analyst and Advisor Summit – the first significant analyst event since Ravi took the helm – ready to hear the master plan.
Victimized by its past success, Cognizant became encumbered with low-value work while lacking a spark to attract new business.
Cognizant is the firm that made digital real for various industries over the past two decades. Its digital focus purveyed a powerful value proposition for clients and investors, yielding substantial dividends, revenues, and profits. But as digital became Horizon One table stakes, Cognizant became encumbered with supporting technologies, processes, and agreements associated with yesterday’s tech – not theRead More
While everyone a year ago thought that nuclear war could threaten humanity’s future yet again, 61% of Americans now say that AI threatens Humanity, according to a new IPSOS/Reuters poll of Americans. 70% of Trump voters believe this, compared with 60% of Biden’s. Not quite sure why we shared that last stat, but it seems to convey how ridiculously this new fad of “AI-washing” is taking us over.
AI means both Everything and Nothing
On the back of the generative AI hype, “AI” has quickly become the new catch-all phrase in modern IT, despite being around for 50 years. People have never been so aware of fake news, internet scams, security breaches, etc., as the public trust in technology reaches a new low.
Massive public misidentifications are making the AI term both a scapegoat for unpopular job layoffs and a magic hype-wand for vendor marketing, as literally every firm touching technology is launching their “GenAI” suite of offerings on a daily basis. The pressure is on executives, investors, public decision-makers, and influencers to skill-up fast and learn how to approach the AI craze with cunning instead of credulity.
We must learn to question what is meant by “AI” and stop it everywhere we lack an agenda or a justification. While the same lack of meaning can be said for the term “Digital,” at least “Digital” tends to be used in a positive context to describe “modern technology,” whereas “AI” is currently being used to describe pretty much anything. AI’s use has become so vague it essentially means “modern computing” in many cases.
However, AI is bloody everywhere
Since the public release of ChatGPT in November, “AI” has been snowballing in usage and popularity. Take a simple Google trend search, and you’ll see the meteoric rise of the term, with “AI” quadrupling since November. In this timespan, most people everywhere have encountered it.
Whether you are a business leader looking for the next innovation to drive profit or cut costs or a parent to a school child getting ready for exams, AI has been doing the rounds at dinner tables and coffee meetings as well as getting a high share of attention on mainstream TV news, from journalists and politicians across the globe. Even many people’s grandparents ask about it as if it’s some sudden new thing.
AI becomes a fashionable excuse to sack people
Back in the days when jobs were being cut because of “outsourcing,” there was always political uproar, and evil corporates were vilified for destroying livelihoods to save a few dirty dollars. I’ve even had protesters demonstrating outside of conferences with the “O” word plastered over them. Suddenly these same corporates (most of whom have already outsourced staff to the bone) are victims of the evil realities of technology where they have no choice but then whack thousands more “because of AI”. Puh-lease… is AI now some dreaded disease inflicted on our corporations where we have no choice but to fire people to survive? Talk about AI-washing our way to Disneyland of Delusion…
For example, in a recent article, BBC explained how Telecom giant BT was planning to cut 55.000 jobs during this decade, with more than 10000 of these coming “from using new tech including AI.” However, the largest bulk of the 55,000 layoffs is projected to stem from BT finishing the rollout of fiber technology, a massive long-term strategic project involving thousands of workers. In turn, the success of this project would further reduce maintenance needs due to fiber’s higher durability.
The story was thus, in essence, about technology efficiency gains, reduced waste, and the success of a strategic project – 15,000 layoffs would come from finalizing the project, and 10,000 from reduced maintenance. What was the headline of this article?: “BT to cut 55,000 jobs with up to a fifth replaced by AI”. While most BT cuts have nothing to do with AI, AI is still in the headline. A more accurate headline for the BBC article could have been: “BT to cut 25,000 jobs due to fiber technology” – it could even get a positive spin: “BT to reduce waste and cut cost due to low-maintenance fiber technology.”
We are yet to see any materialized mass layoffs directly related to AI
We are likely to see increases in these supposedly AI-induced layoffs that are not entirely related to AI, and these will, in turn, most probably also increase the scaremongering across ardent AI reactionaries. However, the reality is that we are yet to see any materialized mass layoffs directly related to AI. Although there will surely be layoffs (like IBM envisioning 7.800 fewer workers in 5 years related to AI), there is no indications that the layoffs will not be offset by massive collective investments made into AI technology (OpenAI already worth $30bn) or other jobs. Goldman Sachs anticipates 300m full-time jobs exposed to automation, and this message took headline in a recent Forbes article in a similar vein to the BT news mentioned above, with AI also here the culprit at center stage. But in GS’ actual report, the prediction is quickly followed up with: “Worker displacement from automation has historically been offset by the creation of new jobs.” As so often before, could it be that we will see more of a restructuring of the workforce than a complete collapse? Very possibly so.
Two primary perspectives, then, are tangible and reasonable: AI will impact our jobs, and AI will spur the reinvention of and investment into other, new jobs. Our first POV on ChatGPT in December highlighted precisely this – that we will see impacts on our jobs and enhancements of our productivity but no actual job removal yet – it is simply not visible nor historically justified. The “misleading impression of greatness” that ChatGPT has stirred (quote by Sam Altman) has also created, in one sweeping move, a misleading impression of AI dystopia. Remember when Gartner said your next boss would be a bot during the RPA craze?
The Bottom Line: let’s learn from this example and keep focused on the task at hand – improving and enhancing the way we work – and stick to concrete use cases instead of idealistic meta-narratives.
As an industry, we will do wise to start spreading the simple word that not all algorithms are AI –and that the generative AI we are currently enthusiastic about is still very much an algorithm. We can be sure the spread of AI as a term and as a technology is not slowing down or losing any steam, but we cannot be sure that the term and the tech will remain focused on the same thing. The tangible and productive AI we have today is getting unhinged from public discourse, and public discourse is power in modern democracies, markets, and minds. After all, we are anticipating a new economy, not no economy.
The Pandemic will forever go down as a seismic game changer in our lifetimes – and our careers. The whole 2+ year experience took a lot of us, cost so many people loved ones and changed the work/life perspectives for so many. Now we face a new world where new rules are still being set (and those rules are likely to be no actual rules at all), but we are faced with no choice but to reinvent ourselves if we want to remain relevant in the business ecosystem of the future.
Or we could choose to ignore the change and pray we aren’t assigned to the dinosaur mausoleum anytime soon… it’s critical to prepare ourselves for the Great LLM-ization as AI becomes the interface to the Internet – and to physical business. LLMs will blow a hole in predictable high-cost operations like call center services and back office business process services, where their entire business models will eventually become defunct in the wake of technological and behavioral change.
Nothing is quite like it was before, and many of us struggle to adapt to these new uncertain surroundings.
Scratch that; most of us are struggling to re-adapt because there are no hard and fast business rules or norms these days. People guard their time religiously, especially when it comes to leaving the house for meetings, events, or office visits. Meanwhile, many corporates are wracked with politics and toxicity, as many workers panic about upcoming layoffs, driving peculiar behaviors from many. There are so many people existing at home for weeks on end, praying not to get the sack in the next round of layoffs because they know they lack energy and focus. This stress of uncertainty and unfamiliarity with the emerging work environment is having a major negative effect on our mental stamina. A lot of folks can barely make it through a full day of meetings these days.
We are living through a time of realization and reevaluation
While I am not going to advocate people to force themselves into an office (those days are pretty much over), I strongly advocate everyone refocus on adapting to the emerging work environment in order to re-energize themselves. The current environment demands you meet regularly with colleagues and clients, suppliers and ecosystem partners if you want to be visible and relevant in your market.
So bloody well do something about it! You need to find your mental stamina to hustle again, learn new ways of thinking, and prepare for the AI-dominant future.
Seven golden recommendations to reinvent ourselves and survive the onslaught of change
1. Accept the way business works has changed… and will keep changing. Accept the way things are emerging are not necessarily a mirror of the past… how we interact, invest our time, communicate, influence, focus, relax, etc. Get used to change and embrace it.
2. Prioritize meeting in person with clients and colleagues more than ever. Don’t fade away in your cave… the sheer scale of change AI and automation are bringing demands us to lock heads and learn together. There’s nothing wrong with working from home, but nothing is better than locking heads with our colleagues and other people to come up with inspired ideas.
3. Adopt an autonomous mindset. Make a real effort to stop yourself and others wasting time on tasks, interactions, and processes that can be automated. Focus your time on making smart decisions based on the data your systems and teams create for you. And developments in LLM models are adding a whole new dimension to the quality of data and insight at our disposal.
4. Change your narrative from ‘effort’ to ‘performance’. The only way to do more with less is to focus on measuring the outcomes we need and the smartest way to achieve them. Work with people who share that mentality. We need to focus on speed to data, not some trudging, painful set of activities.
5. Invest time in understanding AI tools and capabilities, or get left well behind. Don’t be a dinosaur and get with the program, as AI becomes our interface to the internet. AI is changing business as we know it… and at pace, both electronically and physically. Large Language Models are quick and easy to learn and don’t need a Ph.D. in mathematics or computer science. These tools are low/no code environments to develop new workflows or processes that threaten the old guard of programming, where technical staff loved building brick walls to prevent any meaningful business/IT collaboration. Now those walls are crashing down with the onset of these tools that can find patterns in large bodies of text which can predict the next word to write, create sentences and assemble paragraphs of coherent content.
6. Humans are ‘back in the loop’ as we have toprompt AI to get ahead of the LLM explosion. Prompt engineers are the fastest-emerging class of digitally fluent business/tech designers. We already using a conversational interface to ask questions and generate text with an LLM in 2023, and we will be unable to avoid it by 2024. Learning how to do this effectively will become a standard skill that all of us are expected to have. You must understand the mental maps to direct what your team does, as LLMs dictate how we interface with the Internet and run our businesses.
This skillset needed to build effective conversational interfaces is not steeped in NLP or deep learning, instead these LLM orchestration skills demand constant self-improvement in the following:
Asking questions(design prompts). ChatGPT, for example, never gives exactly the same response twice. Learn how to prompt your LLM more intelligently with both short and long prompts to compare quality and accuracy. One of the key benefits of GPT4.0 is the ability to absorb very long prompts (as large as 1000s of words) at rapid speed.
How to iterate. Try asking the same question in different ways, exploring multiple responses to the same prompt, and then comparing the results, detecting bias, and being aware of it.
Evaluating responses is critical as much of what we have experienced so far is how ChatGPT gets it wrong. By asking questions in different ways, discovering contradictions, and asking to self-assess is a key aspect of GPT4 that has improved significantly since the prior version.
Eradicating bias by constantly expanding our understanding of bias in LLMs. ChatGPT, for example, is biased based on the underlying approach used to build the LLM and the data used to train it.
How to generate new ideas(Generative Thinking). The big challenge now confronting us as we approach the Great LLM-ization is to constantly seek new ideas beyond the constraints of our current LLM. You should ask ChatGPT to summarize, synthesize and find the contradictions in the result it creates. Invest time in learning how conceptual blending approaches are evolving.
7. Understand the significance of the technical improvements of GPT-4… it’s the beginning of the Generative Enterprise.
HFS’ Generative Enterprise articulates the pursuit of AI technologies based on Large Language Models (LLMs) and ChatGPT to reap huge business benefits to organizations in terms of continuously generating new ideas, redefining how work gets done, and disrupting business models steeped in decades of antiquated process and technology.
We are learning the new version of GPT is ten times more powerful, cites sources, understands dialects, and even has eyes… just click here to learn more.
A decade on from the trials and tribulations of IBM Watson, IBM unveiled its multi-model and multi-cloud Watsonx to drive AI-first enterprises – what we are calling “The Generative Enterprise” at HFS.
IBM is describing the platform as a “full technology stack” for training, tuning, and deploying AI models, including foundation and large language models, while ensuring tight data governance controls. Watsonx.data focuses on the data scientist; Watsonx.ai the application developer; and Watsonx.governance is then used to deploy the model using a data model factory to ensure that AI is used ethically and responsibly.
In our view, Watsonx is the first enterprise-grade offering to address the Generative Enterprise holistically. Here’s our interpretation of Watsonx:
Watsonx.data helps you create the data model. It focused on the data scientist leveraging Red Hat Open Shift to prepare, tokenize, train, and validate internal and external data.
Watson.ai helps you ask the relevant questions (design prompts). ChatGPT, for example, never gives exactly the same response twice. Learn how to prompt your LLM more intelligently with both short and long prompts to compare quality and accuracy. One of the key benefits of GPT4.0 is the ability to absorb very long prompts (as large as 1000s of words) at rapid speed.
Watson.ai also helps to iterate. Try asking the same question in different ways, exploring multiple responses to the same prompt, and then comparing the results, detecting bias, and being aware of it.
Watsonx.governance evaluates responses which is as critical as much of what we have experienced so far as how ChatGPT gets it wrong. Asking questions in different ways, discovering contradictions, and asking to self-assess, is a key aspect of GPT4 that has improved significantly since the prior version.
Watsonx.governance helps eradicate bias by constantly expanding our understanding of bias in LLMs. ChatGPT, for example, is biased based on the underlying approach used to build the LLM and the data used to train it.
Watsonx overall fosters the generation of new ideas (Generative Thinking). The big challenge now confronting us as we pursue becoming a true Generative Enterprise is to constantly seek new ideas beyond the constraints of our current LLM. You should ask ChatGPT to summarize, synthesize and find the contradictions in the result it creates. Invest time in learning how conceptual blending approaches are evolving.
The Bottom-line: IBM could have been at the center of the AI revolution but was left out as a bystander. Watsonx has the potential to put IBM front and center of the Generative Enterprise
Watsonx seems very well thought through for AI-powered enterprise use cases, especially for horizontal call centers, HR, and F&A. IBM seems to have learned from its original Watson launch by deploying it internally first, launching an apps development platform to demystify the technology. However, the IBM narrative for Watsonx continues to be more technology-centric versus business-centric, which they need to address with their Watsonx narrative.
IBM still woos the CIO budget, but that’s only a third of the total enterprise tech spend. We believe IBM runs the risk of missing out on the broader CXO budgets but polarizing itself around the CIO.
The health of most enterprises depends on the robustness of their supply chains, and our latest Pulse study of 600 G2K orgs shows supply chain disruption is posing the second-greatest challenge to enterprise leaders after cybersecurity:
Today’s enterprises grapple with unprecedented challenges, including disrupted supply from hubs like China, heightened sustainability expectations, a lack of resources, and increasing raw material and fulfillment costs. Service providers help enterprises improve inventory allocation through artificial intelligence (AI) and machine learning (ML) algorithms, optimize supplier management through dynamic supplier management systems, improve visibility by building advanced control tower solutions, and reduce people dependency by introducing automation across processes. The objective is that enterprises should be able to detect and react to “change” quickly, transforming from linear to circular to eventually autonomous supply chain networks.
The HFS Horizons report on supply chain services features 18 providers across three Horizons manifesting incremental business value for enterprise clients. Horizon 1 focuses on a linear supply chain driving functional optimization, followed by Horizon 2, which retains the values of Horizon 1 plus drives circular supply chains with end-to-end transformation capabilities, creating unmatched stakeholder experience with a “OneOffice” mindset. At the pinnacle is Horizon 3, which encapsulates all values of previous Horizons plus encompasses a networked and autonomous vision of the supply chain, driving completely new sources of value with a “OneEcosystem” approach.
The chart below summarizes the Horizons philosophy and key underlying dynamics, showcasing the providers across the three Horizons.
Note: All providers within a Horizon are listed alphabetically
According to the report’s lead author, Ashish Chaturvedi, “The pandemic coerced enterprises to prioritize resilience in their supply chain management and modernization programs. They are achieving this by increasing supply chain visibility, limiting human intervention, and creating multiple fallback options at a process level, such as source-to-pay (S2P). This newfound focus transcends the traditional linear, albeit constrained, supply chain management approach. Gradually, the industry is inching toward a connected, autonomous, sustainable, and collaborative supply chain paradigm.”
Report highlights include
Supply chain resilience has become the central theme of contemporary supply chain engagements. Service providers are helping move enterprises from just-in-time to inventory overstock and single-supplier–single-country sourcing to multi-supplier–multi-country sourcing, demanding more dynamic control tower solutions and a higher degree of automation in demand planning, warehousing, and fulfillment. The objective is to have more control and visibility of the supply chain to navigate unforeseen disruptions.
Sustainability offerings have evolved but not baked into engagements. More than two-thirds of the providers participating in the study have formulated offerings around sustainable sourcing, circular economy, green logistics, and decarbonization metrics. Interestingly, most of the cases discussed were standalone sustainability engagements with a supply chain angle rather than the other way around. It came to light that enterprises are also putting a half-hearted effort into baking sustainability across the supply chain.
HFS assessed 18 leading supply chain service providers. Of these 18 providers, six are positioned in Horizon 3 as leaders, nine in Horizon 2 as innovators, and three in Horizon 1 as disruptors. The services firms that lead the market and ecosystem-level change in Horizon 3 are Accenture, Capgemini, EY, IBM, TCS, and Tech Mahindra. The services firms innovating across organizations and supply chains in Horizon 2 are Cognizant, Deloitte, Genpact, GEP, HCLTech, Infosys, KPMG, PWC, and Wipro. The services firms disrupting and transforming business processes and functions in Horizon 1 are Atos, Hitachi Vantara, and Zensar.
The report includes detailed profiles of each service provider, outlining their capabilities, strengths, provider facts, and development opportunities.
To paraphrase Freddie Mercury, “Another bank bites the dust.” This time it’s First Republic Bank – the latest financial institution that was unable to sufficiently rebound from the liquidity crisis borne out of rising interest rates. J.P. Morgan scooped them up on May 1, with its Chairman and CEO Jamie Dimon widely quoted in the press insisting that this is not a global financial crisis repeat.
HFS tends to agree with him. Central banks and the financial services community have too much at stake to let that happen. It was a long road back from 2008. Trust in banks is still dicey at best. We expect we’ll see continued regulatory oversight, financial support and rescue buy-outs if needed to keep the global banking system functional.
While there is an undeniable crisis of confidence at play fueled by various macroeconomic factors and exacerbated by the spate of bank failures, crisis begets opportunity for the bold. Here are three recommended actions that growth-minded banks should take immediately to ensure survival at a minimum and potential leadership if done well.
Continue investment in critical modernization initiatives.
Digitize your commercial banking offerings
Create actual offerings for small and medium enterprise clients, inclusive of start-ups and scale-ups
Let’s break these down…
1. Continue investment in critical modernization initiatives
Before Silicon Valley Bank went belly up, global IT spending was already in a death spiral from the strain of ongoing macroeconomic conditions. With the pandemic largely at bay, everyone was forced to now pay attention to all the other contributors to macroeconomic malaise – global conflict, inflation, recession, talent challenges, and heightening cybersecurity risk. HFS saw this crisis of confidence reveal itself through a massive year-on-year slowdown in projected IT spending. As the below chart showcases, BFSI spending went from 10% projected growth in 2022 to just 3% in 2023, with the greatest portion of spending now sitting in the “no change” bucket.
This will further slow enterprise spending and related deal closures for services firms. This will persist for at least a quarter with the potential for stabilization and turnaround when banks fail and interest rate hikes quiet down, possibly in Q3 or Q4 2023.
As banks navigate the current mess, we beseech you – do not fall prey to the cost reduction path to perpetual mediocrity. While digital native competitors may be loads smaller than established banks, their technology nimbleness is real, enabling their ability to swiftly spin up new personalized offerings, use data to not just have a 360 views of customers but also to do something useful with the data immediately, and they can and are driving interesting new business models built on open banking and embedded finance. Smart banks need to have a firm understanding of which modernization initiatives are essential to enable growth. Core banking modernization and data migration to the cloud are two likely candidates that are well worth staying the investment course.
2. Digitize your commercial banking offerings
The four fallen banks of 2023 thus far – Silicon Valley Bank (SVB), Signature Bank, Credit Suisse, and First Republic Bank all had varied portfolios and customers. Still, they all offered a significant commercial banking proposition. These failures have already sounded the alarm for updated regulatory standards pertaining to interest rate risk. But they should also serve to raise awareness about the shoddy state of commercial banking – built for large enterprises and starved of digital investment. Smart banks should turn this so-called crisis into an opportunity to finally modernize their aging commercial banking capabilities. The impact will be better quality of service for existing clients and realization of the growth potential in SMEs.
A recent HFS survey of 150 commercial banking leaders revealed investment in offering expansion is heavily focused on enhancing existing capabilities not spinning up sexy new offerings:
The same but better. The top three areas for commercial banking offering expansion are lending and lines of credit, deposit accounts, and commercial cards. Treasury services rolled in at number four. The emphasis is less on new offerings and more on better versions of existing offerings.
Customer onboarding time takes too long. Respondents indicated the average time to onboard a commercial customer is 32 days. The leading factor slowing onboarding is implementation or integration requirements.
Host-to-host connectivity still rules customer access. 65% of respondents indicated that host-to-host connectivity is still the primary standard for accessing products and services. Commercial banking leaders expect strong growth in API connectivity in the next two years.
Current investments favor operations automation. Commercial banks indicated their current top area of investment is in intelligent automation of transaction and operations management. The top areas of investment in two years’ time shift from process optimization to international enablement with trade finance and embedded finance opportunities.
As banks consider their paths forward in the low-confidence economy, there is a clear need and growth potential in commercial banking that can be unlocked with appropriate investment.
3. Create actual offerings for small and medium enterprise clients, inclusive of start-ups and scale-ups
Commercial banking has largely been built for large corporates. The definitions of “large” tend to change based on the size of bank, but the customer baseline is very consistent – with large corporations making up the lion’s share of commercial customers served (see below). SMEs, start-ups, and scale-ups are represented, but often these segments are clubbed with and supported by retail banking businesses rather than being treated as commercial clients – or as their own unique customer segments. This is a missed opportunity to support and enable the growth of SMEs.
As Exhibit 2 also shows, commercial banks realize future growth will come from SMEs. The conundrum, though, is how to truly cater to these segments. The gaps left in the market by SVB, Signature, and now First Republic – all firms that were notable backers and supporters of SMEs – raise issues of bank choice, who is willing to support SMEs and innovative start-ups, and how to do so. As we suggested earlier in this piece, banks supporting commercial customers must invest in digitizing their offerings to deliver better services to existing clients. But it is also a critical ingredient to customer expansion. SMEs want the digital capabilities they’ve been enjoying on the retail side of the house with the benefit of traditional commercial services like various treasury services, lending and lines of credit, and merchant services – but done digitally. SMEs and start-ups, and scale-ups need to be treated as a distinct business segment.
The Bottom Line. Despite the crisis of confidence, there is a glaring opportunity in the face of the banking mess – better commercial banking
Banks should clearly shore up their balance sheets in the face of the liquidity crisis. Those not on Moody’s or other watchlists should consider seizing smart opportunities The need for better commercial banking is not new. But the recent bank failures have put a spotlight on banking choices and the options available to SMEs and innovative start-ups and scale-ups. There is a clear need and opportunity for digitization in commercial banking. As part of this investment, banks need to consider the needs of the SME community – typically representing over 99% of business in most country markets. These are your future growth customers, and they want offerings designed for them.
Anyone tracking HFS will have noticed some terrific new brains join us over the past couple of years from all over the world, but one area we have been really keen to bolter is engineering services. And we’ve been lucky enough to hire a smiling insomniac in Nandini Tare, who’s helped us grow our practice and coverage significantly, especially with her recent flagship Horizons report on Digital Engineering Service Providers.
So let’s hear from her directly what makes her tick and her views in the industry…
Hi Nandini – you’ve been causing quite the excitement for HFS over in India in the year you’ve been with us. Can you tell us a little bit about yourself? What gets you up in the morning?
On the professional front, Phil, I have been in research and consulting for almost 15 years. I started my research career in the automotive sector and now have about 3 areas of expertise under my wing. It has been an exciting journey so far, engaging with business leaders and talking about changing technology landscapes. The world is moving at such a fast pace, and everyone is trying to play catch up. I can’t help but quote Leena Nair the global CEO of CHANEL, ‘Don’t wait for the storms to pass, learn to dance in the rain.’
On a personal front, travel is my weakness. I find traveling an opportunity to engage in experiences that bring me inspiration and keep me motivated. I recently started on a fitness journey that has me up and running in the mornings. The endorphins keep me going. I am hoping to get certified as a coach in the future hopefully! And when I manage to get some free time, I ride my Royal Enfield Classic 500.
So why an analyst? Is this something you always wanted to do as a profession, or did you just fall into it by circumstance?
I believe I had the skills but didn’t tap into them early, but I forayed into industries accidentally. By no means am I an engineer, but I know how engineering impacts businesses. After experimenting with various roles from pre-sales to operations to consulting in my early career, I later chose to play by my strengths. It was a wholesome transition. The early experiments in my career gave me first-hand experience and widen my thought process. This experience has helped me analyze a subject or a topic from all angles and then conclude my opinion.
So what makes a good analyst, in your opinion?
An independent voice and an ability to be unbiased. I feel these two qualities can set an analyst apart from the regular crowd. Believing in the research and methodology one has created and proudly owns it. One can develop skills to be an SME, but providing an unbiased opinion is a conscious effort.
You’ve clearly demonstrated an aptitude for covering engineering markets… what’s so exciting about them, Nandini?
The whole ecosystem is getting connected. Businesses now have access to the latest and greatest technologies to reduce costs and make themselves profitable. The influx of IoT, AI, Robotics, 3D printing, 5G, Cloud, and emerging technologies like Blockchain, Metaverse, Digital Twin, etc. are impacting the consumption side and changing the way traditional business functions. Businesses are now spending on R&D to identify early-stage use cases and commercialize them to bring themselves to the forefront of the industry. All these changes must be a steady progression. ER&D is set to expand as it further gains acceptance in outsourcing and digital engineering. While all of this has me excited, I have intentionally kept generative AI out of this conversation as we would never stop discussing it and arrive at a conclusion on its influence on the ways of working.
And what do you think we’ll be talking about in 2 years time in this space?
Digital engineering services, as most of us would agree, have largely been known for building new products and solutions, Phil. The current set of available technologies has improved business efficiencies, augmented the speed at which a product is brought to the market, and aided product as a service. There is a small portion of the industry that is already talking about how digital engineering is advancing digital transformation strategy to business transformation. One would see a reduction in the lift and shift process and an increase in well-thought-through utilization of technologies to bring true value to the business. It would be interesting to see how service providers and enterprises develop a purpose-led ecosystem and outcome-based pricing. One would also see businesses engaging with niche players to build capabilities to provide enhanced customer experience. Overall, I see this space growing in the next few years.
Thanks for your time today, and looking forward to the next big insights, Nandini!
Recent headlines such as those in the WSJ (The Metaverse is Quickly Turning Into the Meh-taverse), and similar in the FT, remind us of such classics as ‘Internet may be just a passing fad as millions give up on it’ from the year 2000 edition of the UK’s treasure trove of fact, The Daily Mail. Such black-and-white premature pronouncements are typical of headline hunters. As leaders planning their investments and ensuring we extract the advantages we need from technologies as they emerge, we must take a more measured approach and a longer view. The Metaverse is so much more than Zuckerburg’s stumbling business model; it’s the complete immersion of augmented experiences enabled by AI and, ultimately, by Web3.
Anyone who thinks Disney has given up on the Metaverse has lost the plot
The headlines are being made by what are largely corrections in investment in the consumer Metaverse. For example, Disney is reported to have shut down the division, which (among other things) handled Metaverse strategies.
But these layoffs are part of a broader effort to reduce corporate spending and boost free cash flow. Disney is cutting $3 billion in content spend. No one is saying that’s the end of Disney content.
Let’s be real here. The idea that Disney has entirely shelved its Metaverse ambitions just does not ring true. Their ambitions “for storytelling without boundaries in our Disney Metaverse” have not gone away.
Meta’s rollback is no surprise and is likely to encourage investment from others
Mark Zuckerberg may be playing bait and switch with AI on his most recent earnings call rather than with the Metaverse, but then again, who isn’t? ChatGPT is investors’ latest drug of choice; why wouldn’t he play up Meta’s capabilities in it? Frankly, Meta distancing itself from the Metaverse landgrab will be welcome in a community that prefers decentralization and cooperative collaboration to the Zuckerberg monopoly any day of the week. We expect the Meta roll-back to encourage investment from elsewhere.
So what is really going on? A figure of $1 trillion for the Metaverse economy was reported at Davos just a few short months ago. Where did that come from? The answer: a global survey of CEOs who were asked roughly what percentage of their revenues they expected to come from Metaverse-related activities by the end of 2025. For context, this represents less than 1% of global GDP (which is predicted to deliver $118 trillion in 2025 – source, Statista).
The predicted opportunity equates to the size of a 1000m high skyscraper in comparison to the current reality – which at the same scale would appear just 2.45m tall
Source: HFS Research 2023
The $1 trillion opportunity is one Accenture takes seriously and CEO Julia Sweet has referenced it in public. Accenture is investing heavily in the Metaverse and believes it is one of five pillars of success for the enterprise over the next decade.
18 Metaverse services providers expect, on average, to see 15% growth this year
Accenture is far from alone in believing there is a very real and present opportunity in the Metaverse. Our recently published – and inaugural – HFS Horizons Metaverse Services report 2023, includes profiles of 18 leading services and consulting businesses who are designing and delivering Metaverse services and products right now. HFS estimates they are collectively generating $2.45 billion from these services – and across the board that is expected to grow by 15% this year.
Exhibit 1: 18 leading service providers and consultancies feature across three value horizons in our inaugural Metavese Service report
These include (exhibit 1) Accenture, Capgemini, Coforge, Cognizant, EY, Foundever, Hexaware, IBM, Infosys, KPMG, LTI Mindtree, Publicis Sapient, PWC, RRD, TCS, Tech Mahindra, UST, and Wipro.
Enterprises are continuing to increase Metaverse investments
We also found that Metaverse spending, along with low–code investment, were the only two areas in which enterprise investment in emerging tech is not being cut. Metaverse investments showed the greatest increase in investment, with 87% of enterprises committing between 5% and 20% more spend in 2023. The important caveat to this is that most are starting from very low bases.
The Bottom Line: Investment, services, practices, and products prove the Metaverse is not going away. Join investors now or scramble to catch-up later
Enterprise leaders should not allow knee-jerk headlines to distract them. The Metaverse is not going away, as proven by the investments continuing to be made and the practices, products, and services being established by leading service providers and consultancies. Your rivals are increasing their investment in the Metaverse. Your choice is between joining them now or scrambling to catch up later.
One of the most talked about sessions at the HFS Super Summit in New York was my on-stage 1-1 with one of the IT and business services industry’s most revered voices, Ravi Kumar. When he’s not getting invitations to the White House to advise on expanding IT talent development in the US, he’s often spotted on stage at the Milken Institute or Davos – all the while working many major customer engagements – and some of the largest in the history of services. Not many people have been as steeped in the development of global IT services over the last couple of decades as Ravi
So getting Ravi to talk candidly to a senior audience of IT and operations leaders at the recent HFS Summit was a terrific opportunity to get his perspective on the current crisis engulfing tech services to attract the best and brightest – and reverse this depressing drift towards becoming a commodity business.
Phil Fersht: Well, Ravi, do tell the audience a bit about yourself. Because you’ve kind of grown up with this industry, you’re still fairly young, as well, so you have a good affiliation with younger staff, as well as senior management, being one yourself. So maybe you could share a little bit about how what used to be sexy about this industry and maybe where it’s lost its sheen a bit.
Ravi Kumar: Phil, thank you so much for the opportunity to talk to you and the audience here.
When I joined this Industry two+ decades ago, I would say the tech services industry, in general, hired from tier 1 schools. Twenty years hence, I think this industry hires from lower-tier schools. So it’s a significant shift. I think the classical economics of when demand outstrips supply, you think the billing rates are going to go up. That’s not happened. And because the rates have not gone up… I think somebody in the audience mentioned that their son didn’t join one of the tech services companies because it’s not an innovation industry. I think, historically, the industry has been a fast follower in that way. So you fast follow tech cycles, tech waves, and you monetize on it.
And I would also say, Phil, that for the last 30 years, Global 2000 firms used system integrators for enabling technology in the non-core; building HR systems, building CRM systems, building financial systems, etc. So when tech is non-core – and for the last 30 years, the Global 2000 went global, and they used technology to make their operations efficient – it wasn’t so critical, honestly. It was critical to scale, technology was the enabler, but it wasn’t like technology was core.
So every time there was commoditization, it actually hit the tech services industry the most, and the tech services industry held up the margin, and to hold up to the margin, they actually went down the chain to lower-cost schools and hired talent in addition to building productivity improvement cycles. And that actually is the reason why it went from being a sexy business to where it is today.
Phil: Ravi, so how do we reverse this depressing cycle down the service value chain?
Ravi: Phil, we have this unique opportunity to change that. Tech has gone from non-core to core. The Global 2000 today want to use technology not just to build HR and CRM systems; they want to use technology to get extended reach to their consumers through digital platforms. Now, they actually want to embed technology into their products and services. So tech is going to go core. Every Industry today is in the technology and software business. When tech is core for a company, the kind of talent you need is going to be extraordinary, and the rates you are going to get are going to be elastic. And therefore, we have this unique opportunity to repivot. And I would say that the ones who will really make it are the ones who can pivot from enabling technology from the non-core to the core.
There is a new segment of customers that is showing up, which is digitally native companies. Digitally native companies did not outsource for the last 20 years or so. They had a free runway on EBITA, capital was freely available, and they hired talent at an abnormally high cost, which is why they are attractive as employers. Now, the cost of capital is high, and there is accountability to EBITA. So these same set of companies are outsourcing, but they were born digital, so they are outsourcing for core work, and therefore they’re willing to pay more money for high-quality talent. So we could repivot if we want to. So that’s the second shift. Tech is core, and we have a new segment of clients.
And the third is the universe for tech services companies was 2 to 7% of the revenue ofRead More
A decade on from the trials and tribulations of IBM Watson, IBM unveiled its multi-model and multi-cloud Watsonx to drive AI-first enterprises – what we are calling “The Generative Enterprise” at HFS.
One of the most talked about sessions at the HFS Super Summit in New York was my on-stage 1-1 with one of the IT and business services industry’s most revered voices, 