deal architect

A new business model for AI?

This post is inspired by Frank Slootman, CEO of Snowflake. In an interview with CNBC he commented

“AI is not going to be cheap. I mean, somebody's paying for these wonderful Nvidia results. There needs to be a business model that's associated, you know, with the technology. One of the great things about Search, when it showed up was not only that it was great technology, but they also had a business model that paid for it.  We need that here as well. Otherwise, it's fun and games, and it's an expensive hobby, that's not going to last…”

He was alluding to another Nvidia blowout quarter. Jensen Huang, CEO of Nvidia explained some of the trends driving their demand

“The world has something along the lines of about a trillion dollars’ worth of data centers installed in the cloud and enterprise and otherwise…And that trillion dollars of data centers is in the process of transitioning into accelerated computing and generative AI.”

This of course, begs the question – Is ALL the data in ALL those data centers fodder for processing with Nvidia products? They could be - but not necessarily at today’s premium prices. This documentary does a nice job describing Nvidia’s evolution from gaming chips to a powerhouse in generative AI. It touches on “premium” use cases in healthcare, design etc. that nicely leverage his technology.

My recommendation would be vendors poll their customers for use cases where they are willing to pay premium pricing. And think broader - the investment is not just going be around the GPUs, LLMs and other plumbing. Vendors will need to accumulate data around high-value applications. That will call for hiring unique domain experts and accumulating plenty of domain specific data not easily accessible today in the cloud. It is squirreled away somewhere in those trillion dollar worth of data centers, and even worse in corporate spreadsheets.

Let’s face it – the vast majority of enterprise data in the cloud today is back office accounting, HCM, procurement and basic CRM data. If you expect premium pricing, it will likely come from operational data unique to verticals and countries. To access that data, you will have to acquire specialist vendors like Oracle did with Cerner. Not cheap – Oracle paid $28 billion for a small fraction of largely US patient-specific data and it will have to navigate HIPAA and other privacy constraints around that data. Another option – come up with incentives for some of the most innovative customers in each domain to share their data to train your machines. Either way be prepared to invest.

For many vendors, their predictive AI may offer more value to customers than generative AI. If you can preclude unplanned shutdowns of expensive assets with preventive maintenance AI or you can reduce production and logistics footprint, waste and scrap through better demand forecasting AI,  that may be exactly what your customers need.

I like Frank’s call for a business model for AI. I think vendors should start with finding out what customers are willing to pay for as “premium” use cases, then work backwards and figure out whether/how to acquire the premium infrastructure, domain knowledge and the data to train machines for those ambitious use cases.

That would be a business model better aligned with customer value and far easier to sell.

Globalization – time for a fresh look at a complex topic

I was in 4 countries recently, and it reminded me I had been to each as part of my book tour a decade ago for The New Polymath. It also reminded me I had started the book with “sprezzatura” and ended it with “shoshin” – not exactly words you hear every day.

Sprezzatura is a term from the Italian Renaissance that would translate today to “being cool” – showing a confidence even when tackling complex assignments.

Shoshin loosely translates from Japanese to a “Beginner’s or Child’s Mind”. It is a Zen Buddhist concept of looking with wide openness when studying a subject.

I certainly felt both terms at work during my conversation with a friendly German immigration officer at Frankfurt airport. Flipping through my passport he asked “first time in Germany?” I said no, been here at least 25 times. “Always to Frankfurt?” No, Berlin, Hamburg, Cologne, Hanover, Munich, Fussen….”Only travel to Germany?” no, been to 75 countries. His eyes visibly widened. The more we talked the more I admired his curiosity. The more I talked I also realized I was trying to confidently answer his questions but he had no trail to confirm my statements. They were on 9 expired passports in a safe. Some visas like the Israeli had been issued on a piece of paper, not on any of the passports.

With travel opening up in the last year, I have started traveling more outside the US, listening to global strategy experts, reading more books about regional trends. It is a brave new world, post-COVID and Ukraine crisis, where we need to balance curiosity versus the confidence that comes from previous experiences.

Lots of change – and even more noise

What is particularly striking is the plethora of bold commentary you hear. COVID driven travel restrictions and supply chain chaos have led to the “collapse of globalization”, many say. The Ukraine war related energy crisis has led to terms like “deindustrialization of Germany”. Political rancor and large deficit spending in the US is leading to terms like “dedollarisation” – spelled with an “s” it suggests an even more imminent US decline. China’s one child policy has left it with a dead-end in the form of an aging, noncompetitive workforce, others say.  BREXIT, many say, signals the end of the UK.

MNCs like Shell have long had internal analysts which shape their global strategies – in their case, “Scenario groups” have been looking at global trends since the early 70s, when the OPEC oil shock took much of the world by surprise. Their team, their website says, has expertise in fields like “economics, politics, energy analysis, climate policy, socio-cultural change and competitive intelligence.”

Other MNCs leverage think tanks and geopolitical analysts (similar in some ways to us technology market analysts) like Ian Bremmer of Eurasia, Shaun Rein of China Market Research Group and Peter Zaihen among others. There is a ton of global intelligence available – demographic, industrial, energy, agricultural, climate and other data, military assets, political trajectory etc.

When you read the cross-currents across this mountain of data, most individual projections tend to be overly simplistic. Incumbent powerhouses, be they corporations or countries, rarely just roll over and die. They decline slowly and, in many cases, bounce back. Japan has started to grow nicely after a couple of decades of relative stagnation. Most companies have also become way more agile post-COVID and Ukraine. German industrial companies have moved aggressively away from Russian gas with moves to gas from other countries, to metallurgical coal, to their lignite and increasingly a focus on hydrogen as a fuel. The 2023 Fortune Global 500 list shows the power of incumbency – “The companies’ revenue adds up to more than a third of the world’s GDP. And 68% of that revenue is concentrated in companies in Japan. Greater China (including Taiwan), and the U.S.”

A wave of “re-globalization” – a gradual realignment

MNCs are not static. I am seeing more reallocation of resources across countries than I have ever seen before. Supply chains are moving to “China+1”. Sanctions against Russia have forced even more sourcing diversity for fuel, fertilizers, minerals and other commodities. High inflation in places like Argentina is causing a move to neighbors.   

Emerging economies are generating their own MNCs. In fact, Saudi Aramco barely missed being ranked number 1 on the Fortune Global 500 list – only $7 billion less revenues than Walmart which has held that rank for a decade. Companies from other rapidly growing economies – India, Indonesia, Nigeria, Brazil among them are joining the next wave of MNCs – servicing their own large markets and focusing on markets western companies have traditionally neglected

There is also a surge in digitally savvy governments. Assisted by proliferation of mobile technology and hyperscaler clouds, entrepreneurs and SMEs in places like Kenya and Estonia are flourishing. We are seeing more real-time digital tax compliance, digital citizen services and other innovation in the public sector around the world. Many governments see AI as a strategic investment focus.

An exciting time for technology vendors

We have come a long way from the time when “two-tier ERP” meant global subsidiaries were on very different software on LANs and AS/400s versus those at the HQ. We have moved to a world of hyperscalers like MS Azure, AWS and Google Cloud which have democratized DevOps across the world. We have moved to a world where Eva Zauke of SAP talks about “585 local versions (including support for payroll processing in 104 countries) as it supports 200+ million users at 440k customers worldwide.” At a smaller scale – both functionally and regionally – vendors like Zoho and Papaya Global are allowing SMEs to think beyond their borders. In the next wave of AI and ML, operational data needed to train machines will be increasingly localized and verticalized.

Not every vendor is keeping pace. It will take the investments the hyperscalers have made with presence in most major markets while meeting local data protection guidelines. It will take localization like SAP has done across so many country tax regimes, currencies and languages.

Here’s why every vendor needs to re-think global opportunity. Forget all the glib talk and simple projections. There are vibrant markets around the world. Someone else will step up to service them if you don’t.  

Time for lots more curiosity and yes, the confidence which comes from new investments and customer validation. much more than previous experiences.

Fall research agenda

As summer comes to an end – never feels that way in Florida, but I digress – I am looking forward to a packed Fall. Have two big projects, several industry events, a list of video recordings and other items to juggle on the agenda.

Some major goals – in line with the on-going research agenda I shared earlier in the year here, where I said we are seeing a pivot in the software industry

Enterprise AI

AI and ML have been evolving for decades. I hope to hear from vendors about all branches of AI, not just Generative AI. We all heard endless talk about GenAI in the first half of the year. We also heard why vendors believe they are entitled to premium pricing. I want to hear about specific and hopefully differentiated use cases to justify those premiums. Also, examples of customer payback and ROI for that premium.  There is so much talk about “ethical AI”. My definition is I want more candor about how much data volumes vendors are training their machines with. And how they have handled the thorny issues of customer permissions and GDPR compliance around such data. What audit trails and other risk mitigation they are providing their customers around the AI results. In other words, much more detailed conversations at a use case, not just a conceptual, level.

Verticalization and Globalization

Vinnie Vertical is always prodding vendors to showcase what they are doing around industry specific operational applications, especially at the edge of massively changed industries. That’s not changing. However, the shocks of the last few years did not merely transform industries, they have shaken up whole countries. In my travels this year, I have seen seismic changes across many of them. I am pushing vendors to showcase how their MNC customer base has evolved and also what they are doing around rapidly emerging economies. And how their AI training data and use cases are becoming richer as a result of more vertical and global data.

Hope you have had as enjoyable a summer as I have had. Time to look forward to an exciting Fall. We are squarely in the midst of a pivot in the industry.  

Enterprise Software: Don’t stop thinking about tomorrow!

In my role as industry analyst, I have always pushed vendors to look ahead, rethink what they had in their bags over 5 years old and to cannibalize legacy revenues. Especially after the turmoil of the last few years. No industry or country has come out unscathed from the recent shocks of COVID, the Ukraine crisis, increasing climate change urgency and massive digital transformations. No surprise, as I wrote here, we are tracking 4 large software and services markets – hundreds of vertical “edge” applications, applications for fast-growing global economies, custom development using low and no-code tools and Generative and other AI.  

So imagine my surprise when I got from DSAG (the German speaking SAP user group) an email which led off with

“At SAP's annual press conference on July 20, 2023, Christian Klein, CEO and member of the Executive Board, announced that SAP's latest innovations would only be available in the cloud. Specifically, they are to be accessible only to customers using SAP S/4HANA Cloud, Public Edition or SAP S/4HANA Cloud, Private Edition via GROW-with-SAP or RISE-with-SAP contracts. This does not mean that on-premise solutions in general will not be functionally enhanced. But on-premise customers cannot, for example, benefit from major innovations such as artificial intelligence (AI) and green ledger. This also applies to larger function modules and extensions based on the Business Technology Platform (BTP). At the same time, SAP plans to increase maintenance fees. From the point of view of the German-speaking SAP User Group (DSAG), SAP is leaving numerous loyal customer companies in the lurch with this approach.”

And of course, several bloggers and journalists have piled on top of the DSAG reaction.

Huh? By our research benchmarks, SAP is one of the few vendors to have kept expanding its portfolio of vertical edge applications and global functionality. Try finding anything close with its on-prem or cloud competitors. In fact without the vertical and global functionality these vendor’s AI talk runs a huge risk – their machines and LLMs will mostly have access to what will increasingly be commoditized back office data. The next battle field will be around operational data, highly verticalized and regionalized.  BTW, AI will be lot easier in the enterprise as cloud data grows along with customer permissions – today, it is mostly squirreled away in proprietary data centers – highly fragmented and not easy to train machines with.

User groups play a very useful role in our industry and DSAG has faithfully represented the voice of the customer, especially mid-market ones in Europe, but this commentary sounded like Rip Van Winkle waking up, shocked after a long slumber. The enterprise world has been moving to the cloud for 3 decades now, and contrary to industry myth, SAP and its customers have been a major force in this transition. Some data points:

1. In my 2014 book, SAP Nation, I pointed out one of the most common strategies at many SAP customers was to “ring-fence” core ECC functionality with cloud solutions – 10, 20, 50 of them.
2. SAP, under Bill McDermott, Rob Enslin et al acquired a number of cloud properties in the HCM, procurement and CRM areas. The Ariba and Concur acquisitions have created one of the largest business networks in the industry – which SAP is increasingly verticalizing to include direct material suppliers. You think continuing to expand ECC or even S/4HANA would have easily accomplished that?
3. SAP has been delivering vertical edge applications in the cloud – intelligent returns around eCommerce, cell and gen therapy orchestration in healthcare, e-mobility and EV charge point billing for auto and utilities sectors among others
4. Countless customers are taking advantage of hyperscaler clouds as part of signing up for RISE with SAP.
5. In my 2019 book, SAP Nation 3,0, we had discussed the growing emphasis on cloud functionality and increasing talent challenges recruiting and retaining ECC and on-prem talent. Holger Mueller of Constellation had looked ahead and asked “Do you want to be in 2030…with an ERP system that cannot run machine learning, which does not have a good IOT story and so on?”

So, not sure I understand the DSAG surprise about Christian’s comment given all these signals going back so long.

About SAP’s economics – no CIO I have worked with pays full list price. There is no single enterprise software price point. Given SAP’s vertical investments and country presence it has a dominant position in many segments and can demand a premium. In many other segments it will not be able to do so. It has a very capable Value Advisory team which will have to help it justify its pricing.  I may be off base, but I don’t see a repeat of the customer pushback to maintenance price increases in 2008. That was boneheaded in the middle of a recession. This is aspirational and each customer will do their own value analysis and in case of AI, I am already seeing plenty of risk mitigation being factored in ROI assessments.

Not just picking on DSAG, I am also increasingly impatient with industry analysts. As I wrote a few weeks ago “I go to too many events where we still use dated TLAs (I admit I coined some of them in the mid-90s at Gartner). Two flagrant ones are ERP and CRM. Research firms have armies of analysts who still create Magic Quadrants, Waves and other tools around those TLAs and they parachute in droves to industry events. Worse, vendors spend months responding to questionnaires from these analysts to justify microscopic changes in their annual scorecards.” And “Let’s get away from umbrella, fossilized terms. Let’s talk the language of today’s business.”    

Every customer decides its own technology footprint and path. For many staying with the true and tested is the best path. But let’s not shackle our vendors to that past. Let’s push them to keep thinking about the future. The world has changed dramatically in the last few years and the pace of change will only accelerate.