deal architect

Burning Platform: Dreamforce 2024 sneak preview

For the 124th episode of Burning Platform, Michael Maoz, SVP Innovation Strategies and Ed Thompson, Market Strategist at Salesforce provide a sneak preview of what to expect at Dreamforce.

Michael and Ed are former Gartner colleagues and it was great to reconnect with them as we prepped for the episode.

They cover a lot of ground in about 35 minutes. Several things stand out

• Agentforce will dominate the airwaves. Salesforce calls it a “suite of autonomous AI agents that augment employees and handle tasks in service, sales, marketing, and commerce, driving unprecedented efficiency and customer satisfaction.”  CEO Marc Benioff had previewed in a Jim Cramer Mad Money interview early examples from several industries including Wiley (publishing), Kaiser (healthcare), ADP (services), Wyndham and Open Table (hospitality). Michael promises there will be many more and DF attendees will be able to take their own personalized agent home. “That’s the new swag” he says. Ed points out attendees will learn about “71 use cases of Generative AI and agents that Salesforce is using internally ”. It’s about time the conversation in the industry moved beyond GPUs and LLMs, to practical use cases and payback and Dreamforce promises plenty of that.
• Data Cloud should also get plenty of attention. It has been scaling massively over the last couple of years “We're up to over a trillion different data interactions. And by the way, trillions of predictions. And “we have 3000 developers working on it. Everyone tends to look at Databricks and Snowflake, that category of vendors but we've got more developers than they have, just focused on this stuff.” Michael also clarifies “we're not trying to own your data. That's not our game. We're not building it so that we can charge you to store your data on our system and have it all trapped. Data Cloud is not a traditional database, the way people think about it.”
• There will be plenty more in the 1,300 sessions. As Ed summarizes “there are 500 features in the latest release, which get completely ignored.”
• Of course. Dreamforce is never just a product showcase. You get to meditate with monks, mingle with all kinds of mascots and musicians and Trailblazers and the creative team at Salesforce always takes the “National Park” to new heights. And the city of San Francisco which has been going through a rough time the last few years, always cleans up for the event.

Image Credit – Ray Wang

Nothing compares to being there in person. But you can feel the pulsating energy in their voices. Very nicely done.

 

Analyst Cam: Zoho’s Enhanced Analytics

As we have moved to virtual briefings, I have increasingly been excerpting short video segments (with permission) as part of my Analyst Cam series.

Zoho launched today a new version of Zoho Analytics—Zoho's self-service BI and analytics platform. https://www.zoho.com/analytics/ It packages over 100 enhancements including new AI and ML capabilities, enabling diagnostic insights, predictive analysis, and automated report and dashboard generation.

Zoho Analytics, first launched as Zoho Reports in 2009,  has quietly become a major player in the crowded Business Intelligence market. It is the second most used application in the Zoho One suite (which I have written about often over the last few years). That’s particularly impressive when you consider the suite has over 50 applications.

In addition to 17,000 direct customers of the analytics capabilities, several ISV and SI partners have adapted the analytics engine for their platforms and as a result Zoho can claim 70,000 analytics customers. Importantly, that also translates to a wide breadth and depth of data which Zoho’s over 500 connectors have access to.  That range also positions it well for the growing Generative AI market, especially as customers look for cross-functional and vertical use cases.

As part of the launch, I had a chance to record Sailas Sundaram, Senior Product Manager of the Zoho BI Platform, as he summarizes some of the new capabilities. He does so crisply across these 4 categories.

He goes through a long list of features across the 4 areas including the pipeline builder which enables data engineers to orchestrate and monitor the data flow from source to destination.  He discusses integration with OpenAI, MS Teams and Slack and adding support for more regional languages to Ask Zia, their natural language assistant.

He covers DSML Studio with AutoML, a no-code assistant, to easily build custom ML models. He explains the BI fabric which allows for combing insights from multiple BI platforms, such as Power BI and Tableau, onto one, easily accessible analytics portal.

Lots more in the rapid fire 20 minute video. Very nicely done.

Industry Tea Leaves – Executives, Earnings and Events

It was a rough week for tech stocks on Wall Street. And with the uncertainty around US interest rates and elections for another 2 months who knows what other whiplash effects we will encounter.

I usually take a narrower pov - how will this affect enterprise software and services? And in the last two weeks have had several interesting conversations, and will have more at upcoming industry events in the next few weeks.    

Is SAP in trouble?

I heard from a couple of folks

“Three board members gone in less than two months”

“This is a lot of executive talent to replace on short order”

Is Salesforce taking SAP’s place as a vertical leader?

Marc Benioff was in fine form as he reported an impressive quarter on Jim Cramer’s Mad Money and importantly talked about AI use cases from several industries including Wiley (publishing), Kaiser (healthcare), ADP (services), Wyndham and Open Table (hospitality)

Are we in the Gartner trough of disillusionment when it comes to Gen AI?

Dreamforce, Workday Rising, SuiteWorld should give a better perspective on the trajectory of the industry and I have heard about product announcements from Zoho and others under NDA

When are we going to see Gen AI impact on SI developer productivity? And that in common phases in most of their projects - data conversion, testing, end user training etc?

Many SIs will have large booths at the industry events and should allow a chance to ask them about Gen AI impact on their practices.

I also tend to take a long term view of the sector in line with enterprise customers. They buy solutions which serve them for 2 decades or more. They spend months evaluating options and negotiating contracts. Throw in vendor events and news and all these data points are tea leaves which help me in my tasseography. You have to drill down in to the small patterns, not jump to conclusions from the clusters

I also rely on history for macro clues. Hardware and telecom vendors have historically provided the groundwork for architectural shifts. The initial set of applications and services tend to be “safe” and under utilize the new processing power. It took Apple and Google nurturing mobile apps ecosystems to help grow sales of mobile devices. It took Amazon similar to build a massive ecommerce engine.

We are seeing the same when it comes to the power of GPUs and LLMs.  As I wrote here, the initial Gen AI use cases in the enterprise have not been very ambitious – especially when you consider the power of NVIDIA’s Blackwell platform. They have focused on SG&A, not on the much larger COGS and Revenue and Asset management opportunities on their customers’ P&L and Balance Sheets

I have said often that even after 25 years of SaaS applications, 75% of business processes across countries and industries do not have much vendor application choice. Vendors have been content to keep selling basic ERP and CRM functionality, and there mostly for English speaking countries. Those terms have been around 30 years – I helped coin some of them. If anything, the hype from GenAI has caused a pause in expanding their transactional functionality. Without the functionality they do not have data or the domain expertise to imagine ambitious AI use cases.

Even SAP which has the broadest reach of customers, functionality and talent across industries and countries has been cautious in the reach of its GenAI offerings. So about its exec departures, yes  it is somewhat concerning but I am more worried that SAP is not being more ambitious in its offerings and is mostly focused on an updated core ERP. As for Salesforce, I love Marc’s optimism but his use cases mostly focus on payback from customer service productivity. I would love to see in addition operational, vertical and geographic use cases.

And in turn this is a major opportunity for NVIDIA, other chip makers, LLM providers and hyperscalers to build a broader ecosystem of use cases and business cases. . Many of these markets should be highly differentiated and command premiums which Wall Street expects to pay for NVIDIA GPUs and hyperscaler pricing. It should be a virtuous cycle as it has turned for Apple, Amazon and Google in the last go around.

It is good to see Jensen Huang, Sam Altman, Thomas Kurian, Matt Garman make the industry rounds but I would love to see them drive more leadership and ambition in their enterprise ecosystems. As for me, I need to get an oversized coffee mug to read more tea leaves. As I wrote here, Wall Street’s definition of industry leadership has evolved over time from BOPS to FAANG to the Magnificent Seven. We cannot rely only on the current crop of application and services vendors for enterprise AI leadership.

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