deal architect

Unit4 X4U – Elegant Simplicity

I was part of the Gartner team which popularized the ERP concept in the late 90s. Nearly three decades later, I am impatient and always asking vendors about vertical extensions, localization for a long list of countries, automation in implementations and support and increasingly about their AI applications.

The reality, of course, is many customers only want core ERP functionality at low effort and cost. They have "ring fenced" core ERP with other applications, they have custom developed other applications, many are not particularly global, others do not want multiple hyperscaler clouds. I hear from many of them – thank you, but we want our ERP to follow the KISS motto – Keep it Simple, Stupid! Insulate our customizations, make upgrades as easy as I am used to on my mobile device, don’t require us to hire school buses of consultants.

We have a challenge in our industry – vendors glibly call it "technical debt" and blame customers for not keeping up with their latest offerings. If it was a handful of customers, you could buy that argument. Tens of thousands of customers point to a big problem in the industry. I will explain that further in another post, but I thought Unit4 in its recent X4U customer event started to tackle the challenge in their customer base. You can watch the 2 hour session replay here. 

In fairness, Unit4 is focused on a handful of service industries (especially project-centric ones), only in key global markets and mostly on mid-sized enterprises so the customer and related product complexity is somewhat easier to manage. There was the mandatory talk of verticals and Generative AI and a slick gaming metaphor of "power-up" but I was more impressed with how much focus went into convincing customers the move to the cloud need not be a high-risk surgery.

My favorite section was that by Jean de Villiers, CCO on Success4U starting around 1.17.50 – “one point of access to everything in the service portfolio. Whether those services are partner capabilities that we bring to bear through our Success Catalog, whether they are white glove cloud operations services that enhance your usage of your SaaS platform, whether they are an extended support SLA that helps you to be properly supported in your time zone, and enhanced professional services that can assist you with driving organizational and cultural change across your organization.” Its not a new idea but I like how it is packaged – indeed they describe it as a “wrapper” with various “success packages”, milestones and service levels.   

I liked that they gave half an hour to Rachel Jordan, VP of Product starting around 46.15. She had plenty of time to go through multiple demos across 3 pillars focusing on decision velocity, automation, and integration across the financials, hcm and projects components of the suite. The demos covered Open Banking, expense reports, revenue recognition and other use cases.

Couple of things to me highlighted how grounded the event was

• I was impressed how few slides CEO, Mike Ettling used in his opening monologue and in the exec Q&A at end. The customer exec he had on stage, Michel Etienne of Foyer Health, used more slides than he did.
• Good friend, Ray Wang who is usually a wild man on stage was tethered to a desk as he presented virtually.

More on the industry challenge I pointed above in a future note. In the meantime, I look forward to Unit4’s execution on the sensible stuff they presented.

Analyst Cam: Salesforce Industries & Revenue Excellence – a Post-Dreamforce Update

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

I attended Dreamforce last month fully expecting to be inundated with AI messaging–and I was, with Salesforce taking a sensible “trust-first” approach. I also wanted to get an in-person perspective on progress within Salesforce Industries and its Revenue Lifecycle Management offerings. While there, I watched several Industry Cloud presentations (Salesforce is now up to 13-plus Industry Clouds and solutions) and also spent time with many  industry-focused customers and partners, in addition to walking the show floor which offered plenty of industry-specific product demos.

Jujhar Singh, EVP and GM, Industries & Revenue Lifecycle Management for Salesforce, generously followed up with me in a post-Dreamforce video interview to share the latest on Salesforce’s Industry Strategy. See below for links to each of the eight segments, including an annotated description of each.

For more information about Salesforce Industry Clouds, click here; watch on-demand Dreamforce Industries sessions on Salesforce+ here.

Segment One: Introduction (3:46 minutes)

Jujhar sets the stage and explains the meaning of its five Product Pillars. He also emphasizes the importance of Salesforce bringing together all its core clouds based on one common metadata, stating “that’s our special sauce.” Finally, he stresses the company’s focus on AI, saying “the AI revolution is a data revolution more than anything else.”

Segment Two: AI Strategy (2:31 minutes)

Jujhar says the goal is to make sure that AI is a continuum from predictive to generative, not segmented in different boxes. The key to that is a solid data foundation. Salesforce was one of the first enterprise vendors to bring predictive AI to customers. Via Einstein, it claims to have made a trillion predictions. Now around vertical scenarios, it is packaging 31 industry AI applications out-of-the-box and looking at industry-focused LLMs and other verticalization. This segment includes examples of AI use cases.

Segment Three: Deep AI + Data Cloud Applications (5:46 minutes)

Jujhar highlights four vertical AI and Data investments announced at Dreamforce across a wide range of sectors:

• Connected Twins for Auto and other industrial markets (in a partnership with Qualcomm)
• Personalized Finance for Banking and Financial Services
• Trade Promotion Optimization & Effectiveness for Consumer Goods
• Unified Health Score for Healthcare – both at an individual and population level

He also emphasizes the “trust” factor which was repeated early and often at Dreamforce. “We don’t own the data. Customers do.”

Segment Four: Generative AI Scenarios (1:37 minutes)

Here, Jujhar highlights 10 industry-specific GenAI use cases. He also drills into Education Cloud, which is being built to support lifelong learning. Jujhar explains that as an institution designs courses, GenAI can recommend skills needed as a baseline for each course. As individuals complete different courses, they can see the aggregation of skills they’re building.

Segment Five: Revenue Management Foundations (1:44 minutes)

Jujhar discusses three solutions: Enterprise Product Catalog, Pricing, and Contracts. This segment includes Generative AI to generate contract language and collaborative redlining among other features.

Segment Six: Strengthen Scale Clouds: Financial Services and Health Cloud (5:07 minutes)

Here, we talk about two of Salesforce’s most successful verticals: Financial Services Cloud and Health Cloud, with the latter being complemented by the company’s latest industry offering: Life Sciences Cloud. He explains that Life Sciences Cloud isn’t just about the Pharma sector, but also includes MedTech. Jujhar also shares what’s going up-market with Group Insurance, expanding into compliance with more Know Your Customer (KYC) integrations for banks, and other new functionality for the Financial sector.

Segment Seven: Impact Portfolio: ESG, Nonprofit, Education, and Public Sector (6:00 minutes)

Jujhar covers four pillars in what the company calls its “Impact Portfolio.” For ESG, he talks about how the “E” is covered by the company’s Net Zero Cloud. He shares that Nonprofit Cloud provides a lifecycle approach, from fundraising, to program execution, and to a scorecard on outcomes. For Education Cloud, he says the company is starting to focus on lifelong learning, emphasizing that “You cannot be in a model of ‘one and done.’” And for Public Sector, he says “It’s one of our fastest-growing Industry Clouds. We’re getting traction across the board, really, whether it’s state and local, or the whole domain of federal, and across functions from benefits management to social, as well as licensing permits and inspections.”

Segment Eight: Maturing & Emerging Portfolio: Manufacturing, Connected Cars, Loyalty by Industry, Referral Marketing by Industry, Clean Energy (1:35 minutes)

Here, Jujhar talks about other recent investments, and they span across sectors. He says “the next set of innovation is going to come through the focus on clean energy.” For industrial sectors, he talks about a focus on assets and their maintenance, warranty management, and the concept of connected costs. He also explains how the company is investing in loyalty programs by vertical, and a referral marketing module for Education, Nonprofit, and Financial Services.

Burning Platform: Operational Excellence at Bergen Logistics using Zoho

In the 95th episode of Burning Platform, we host Keith Cooper, VP of Customer Experience at Bergen Logistics

This is a two-fer – an overview of Bergen and a discussion about how they have grown explosively and with all kinds of metrics with Zoho

Keith does a nice job (in about 10 minutes starting at 4.48) summarizing Bergen’s focus in the logistics world, particularly for the fashion/apparel sector (the “better-to-luxury” segment), how they have tripled in revenues over the last four years, how their acquisition by Elanders (of Sweden) opens up significant global opportunities, their warehouse management and other software that most of their customers utilize

What’s impressive about Keith is the constant thread of operational excellence. He has taken his continuous improvement mindset from the fulfillment world and applied it to his current role in customer service – terms like volume and velocity flow naturally

He talks about the journey with Zoho, how his staff keep discovering new applications in the Zoho One suite, his global expectations of Zoho, how he is starting to leverage their AI capabilities.  

We then spend some time talking more broadly about AI and use cases which excite him both in the CRM and transportation management areas.

Two very competent and fast growing entities – Bergen and Zoho. Real pleasure to have Keith cover so much ground in about half an hour.

Will Workday lead us out of the Enterprise “AI Winter”?

I smiled when Sayan Chakraborty, Co-President mentioned “AI Winter” in his presentation at the Workday AI and ML Innovation Summit last week. I smiled for two reasons:

He expressed eloquently in two words what took me much longer to describe in my 2016 book, Silicon Collar.

“Since the 1950s! That is when Alan Turing defined his famous test to measure a machine’s ability to exhibit intelligent behavior equivalent to that of a human. In 1959, we got excited when Allen Newell and his colleagues coded the General Problem Solver. In 1968, Stanley Kubrick sent our minds into overdrive with HAL in his movie, 2001: A Space Odyssey. We applauded when IBM’s Deep Blue supercomputer beat Grandmaster Garry Kasparov at chess in 1997. We were impressed in 2011 when IBM’s Watson beat human champions at Jeopardy! and again in 2016 when Google’s AiphaGo showed it had mastered Go, the ancient board game. Currently, we are so excited about Amazon’s Echo digital assistant/home automation hub and its ability to recognize the human voice, that we are saying a machine has finally passed the Turing Test. Almost.”

Also, a few days prior, Margaret and I had returned to the US via New York JFK. I have done so countless times especially in the 80s when I did multiple overseas assignments for PwC. Each entry required long lines, paperwork and interaction with human bureaucrats. Even my signing up for Global Entry a decade ago had not changed things much. Broken kiosks, clumsy fingerprint scans – the UX was not pleasant. This time, Margaret went to a manned line (she does not have Global Entry), while I walked into a completely empty room with my choice of twenty kiosks. While I fumbled for my passport, the associate guided me “Just take off your glasses”. A bit cynically I did and facial recognition took over and a few seconds later I was through. Wow!

It took Margaret another 20 minutes to go through her more analog process and while I waited for her, I reminisced about the hundred times (not kidding) our passports had been touched during our trip to India. With a ten-year visa which the Indian government would not transfer from expired US passports, we were each required to travel with two passports. Several times at each airport, at every hotel, every currency conversion, even entry to monuments like the Taj Mahal our 4 passports were eyeballed by a human and a scanner and likely printed and filed. Think of all the wasted time and paper, not to mention the constant worry of losing our passports.  This when the Indian government already has digital records of our passports and visas. Talk about a stark contrast to my JFK experience – the term “AI winter” definitely struck a chord.

But I am an enterprise technology analyst. Most AI innovation we have seen in the last decade has come from the consumer world – speech to text, machine vision, etc. I have been excited about enterprise AI countless times and it always appears to deliver less than promised. Like when I interviewed Zach Nelson, then CEO of NetSuite in 2009 for my book, The New Polymath.

He had told me:

“We have some of the best leading indicators on the economy. We can aggregate order value, cash flow, and several other metrics instantly in our base of over 6,000 customers and watch trends.”

And I had written:

“Soon, those customers will be able to benchmark themselves against aggregated data of their peers. That would obviate the need for mailed–in surveys. That capability has been the domain of benchmarking firms like Hackett, not of the software industry, so that is another innovation NetSuite is working to deliver. Nelson explains: “Take those benchmarks and some of the creative BPO [business process outsourcing] partnerships we are exploring (such as one announced in April 2010 with Genpact, the spinoff from GE described in Chapter 3), and the industry could see SLAs [service - level agreements] that don’t just monitor technical metrics like systems availability but business process metrics that have been elusive to codify.”

The reality nearly 15 years later, is that much of enterprise data is still locked up in on-premise systems and private clouds/proprietary data centers that few vendors are allowed to access. Corporations love to see benchmark data from their peers – but have been (overly) cautious in sharing their own data. Bureaucrats around the world have complicated data gathering with their privacy and data residence regulations. The amount of enterprise data available to train computers is minuscule compared to the billions of images, voicemail messages and other data that Google, Microsoft, Amazon and others were able to collect without the data gathering restrictions they have used to train their machines.

Workday Co-Founder, Co-CEO, and Chair Aneel Bhusri had got me excited about enterprise vs. consumer AI when at an investor conference the week prior, he commented:

“With ChatGPT, you can ask good questions but you get some wacky answers at times, because the Internet is the Wild West... But our data is absolutely constrained, normalized, it's clean. And as a result, we can produce pretty powerful results.”

The point about caution about the consumer web as a data source for ML data was reinforced several times during the Workday event. Adobe’s event this week also focused on protection against the coming misuse of Generative AI and had coincided with deep-fake photos of President Trump being arrested.  

Sayan had also elaborated in a blog post:

“Workday was an early adopter of large language models (LLMs), the technology that has enabled Generative AI, and we use them in production today. We have started adopting Generative AI at Workday to solve a host of additional customer challenges. A canonical case for LLMs is content creation, and we can see how drafting performance reviews, job descriptions, and a host of other documents will be transformed by this approach. We’re going to continue to identify key use cases where Generative AI can add value to our customers and develop unique models that leverage both Workday data and external data sets.”    

Thankfully, the AI/ML Innovation Summit was not just about ChatGPT. Workday provided several optimistic cues about the broader evolution of Enterprise AI and their own role in shaping the journey.

Here are some:

Large enterprise databases to train machines and related customer permissions

Workday today services 60 million users. Skills Cloud was launched 5 years ago. Half of Workday’s HR customers have participated and shared their continually evolving employee skills with their peers. At its scale it would be impossible to maintain without machine support. And it gives Workday a template to build similar clouds around other enterprise data attributes.

Now, you may say, 60 million users is not that large. These users generate plenty of data - over 400 billion transactions a year. Very few enterprise vendors can show that scale – at least in their clouds.

Side note - CMO and Executive Vice President, Corporate Growth Pete Schlampp’s comments on Workday’s Rock Star commercial during this year’s Super Bowl brought home another significant impact of these 60 million users. Enterprise tech companies have had a patchy record advertising on that widely watched show, but, Workday’s brand is much stronger and their logo is more recognized in the consumer world because of this user base. Aneel’s comments about conversations with CEOs and politicians suggest we may also see Workday active on policy matters.

Analytics and ML

Since Workday acquired Platfora in 2016 and branded it as Prism, it has become a vital tool for its users to analyze cross-functional data especially that from vertical feeder applications. As a result, we heard plenty from Workday and from several customers on panels that Workday’s datasets are growing beyond its traditional Finance and HR focus. But the vertical perspectives are still skin-deep. From a process design perspective you want to ensure quality and accuracy at the source. Anomalies and variances should be presented to operational users like clinical professionals, not wait for a Financial or HR user to notice them.  A big reason, I believe, why Workday will grow a solid core of vertical processes (in what it defines as service industries) and its base of operational users, employees and partners. I am a broken record when it comes to verticals but think their expanded ML focus will accelerate the demand for industry specific operational data. However, Workday is not likely to acquire a legacy vertical application. As Aneel said during the event “We are always looking for next generation players - cloud native using AI and ML for industry applications. We would never take something that is outdated technology because the first thing we have to do is throw it all away and rewrite it from scratch.”

Planning and ML

Since Workday acquired Adaptive Insights in 2018 it has become a planning powerhouse. The pandemic and the chaotic maneuvering at most enterprises the last few years have led to more continuous planning, and increased the need for more machine-driven planning. I also heard at the summit about an expanded range of planning in areas such as demand forecasting. All the more reason to mine external weather and vertical data. I wrote a case study in 2019 about Costco and demand forecasting at its Food Courts. Besides factoring weather and nearby events, their algorithms were also starting to factor gas prices and related impact on pump traffic. If a customer comes for gas, he/she is likely to also be a prospect for prepared food.

No scary job loss forecasts

Many vendors will use an event focused on AI and ML to talk about doom and gloom around job losses. Frankly, that complicates enterprise adoption even more. Sayan took a contrarian step. He presented a slide which shows that at least in developing nations, we face shrinking workforces. Machines will be needed to make up this shortfall.

In Silicon Collar, I had highlighted how even the smart folks at Oxford U. and Gartner had fallen prey to wild doomsday models of job losses from automation. I had presented several examples of slow adoption of automation technologies over the last century – UPC scanners, ATM machines, autonomous cars and others. I had summarized the examples in this Strategy+Business article. Job losses from automation tend to be gradual – and in many scenarios there are job gains. I also made the point that automation helps eliminate what are 3D - dull, dirty and dangerous - tasks. Automation reshapes jobs, not eliminates them.

Enterprise AI will do similar – think of the drudgery I described above that India will be able to reduce as tourism booms over the next decade. Air India just placed a massive order of 500 new planes in anticipation of this boom.

Of course, from the questions during the Summit, today’s smart folks appear to want to focus more on bias in AI, Federated ML and other contemporary topics that will keep Workday engaged from other angles.

Aneel’s comments

Aneel’s prepared and casual comments showed his belief we are at yet another inflection point in the industry. Having upended the client/server market with Workday’s cloud offering, he is acutely aware of architectural disruptions in our industry. The arrival of new Co-CEO Carl Eschenbach has clearly energized him and he wants to get back to more of a product and platform focus. He said he is looking for a condo in Boulder, Colorado to spend more time with Sayan and the ML team.

One of his comments summarized his sentiments “I am not afraid of Oracle or SAP. I am more afraid of a disruptive new enterprise player built on ML and AI.”

Bottom Line

I walked away feeling more optimistic that enterprise tech may finally be poised to exit its “AI winter” – and that Workday will play a key role in this transition.

Salesforce: Plenty of growth markets

Most of the recent analysis I have read about Salesforce has focused on the stakes taken by Starboard Value and Elliott Management. Activist investors play a useful role as they push for efficiencies and resets to increase shareholder value.  I hope in this case, however, the activists don’t just use old playbooks and benchmarks. We have entered a very different world of enterprise applications. Four big drivers – COVID, the Ukraine energy crisis, climate change urgency and major digital transformations – have opened up a slew of new enterprise application markets.

Take intelligent returns in retail as nearly 15-20% of ecommerce sales are returned and have to be efficiently restocked, refurbished, scrapped or donated to charity. Or complex CPQ as companies “servitize” and bundle products, services, spares, financing and more in outcome based contracts. Direct to consumer models that take advantage of new micro-fulfillment ecosystems. Field service of complex equipment which leverage mixed reality and digital twins. Smart insurance as cars get smarter and more connected. EV battery charging operations. Applications for the emerging hydrogen economy. Applications for the growing utility prosumer market. Telemedicine. Digital mortgages.

I could highlight another hundred such applications which have emerged or accelerated in the last few years. These are nascent markets and easy to dismiss.  There is plenty of wishful thinking – help me find the next ERP or CRM market. I have been in the industry long enough to have seen when both ERP and CRM were tiny markets. I have seen them mature and I am seeing them get commoditized as too much investment has chased after core functionality in each.

I have spent a fair amount of time with Salesforce’s vertical teams and many have presented in my Analyst Cam video series. They are not anywhere as deep as SAP’s vertical capabilities but that is by design. Salesforce focuses on front office, revenue centric apps, not as much on operational areas that SAP thrives in. But compared to other enterprise vendors and even hyperscalers, Salesforce is very well positioned when it comes to many verticals. 

As I like to say business as usual, circa 2019, is a recipe for mediocrity. We have had too many black swan events in the last few years to pretend the world has not turned upside down. One of my recommendations as Salesforce and its investors chart a new course is to double down on its application savvy and lead its customers with a new generation of enterprise applications. Plenty of growth opportunities to mine and generate shareholder value. 

Burning Platform: The enterprise suite does not always win - Zoho One is a standout

In the 78th episode of Burning Platform, we host Raju Vegesna, Chief Evangelist at Zoho, a repeat guest in this series

Zoho One – also branded as “the Operating System for Business” - is a suite of 50 and growing applications across sales, marketing, finance, hr, legal, collaboration and other functional areas – see the full list here (btw it does not list the 50+ mobile apps which are also included)

We discuss a major milestone in the evolution of Zoho One – its fifth anniversary.

In those 5 years, it has been adopted by over 50.000 customers. Notably, it has also penetrated markets like UAE, Nigeria, Kenya, Mexico and others that few enterprise vendors ever cover.

The glib statement in the enterprise applications market is “the suite always wins”. Yes, it is compelling to have an integrated solution with a common UX, single version of truth across the enterprise. The reality is first-gen ERP, CRM and other suites were inconsistent in their functionality by module, often cobbled together via acquisitions, attracted lots of Sis who were comfortable in HQ functions but not in operational areas the suite promised to cover, resulted in massive overruns. My view is that experience has made enterprise buyers much more cautious and back to buying at a much more modular level. With that backdrop, Zoho One has done very well.

Raju discusses many things Zoho has done right – “a dollar a day” pricing; organic, self-discovery of applications so users expand their use of the suite at their own pace, rather than being oversold what ends up becoming shelfware; and a focus on customers without much of a legacy application portfolio to migrate.

He also discusses what’s next in the evolution of this success story.

Crisply (and modestly) done in 16 minutes.    

Workday’s Relentless Discipline and the Power to Adapt

Some of us are old enough to remember Workday’s pioneering analyst summit in August 2010. I wrote back then

“Few vendors have the guts to be open to such a smart and opinionated bunch as Workday was during its Technology Day yesterday. Like a marathon tennis match with plenty of volleys and lobs and aces, the back and forth was something to watch.  As you can see from the Twitterstream and blog posts from the day a wide set of angles were covered - object models, user interface design, change management processes, analytics and integration tools (in a SaaS market where both are still weak), stuff from the labs - tablet and voice interfaces, mobile applications - and more.”

So, when we were invited to the latest iteration of their Innovation Summit for analysts last week, I had two questions:

• How many of my peers would show up given continued pandemic travel restrictions and worries?
• What would count for innovation at a company which is now almost 80 times as large and for an event whose theme was a confident “Made for this Moment”?

The first question was relatively easy to answer. I ran an informal survey when I arrived and tweeted to a colleague

“…talking to a few analysts here, we have become more selective about attending in-person events. Travel experience is still not that business friendly. Puts more pressure on vendors to rethink events. Well-crafted analyst summits like #wdaysummit are ideal format.”

It helped that this was their first in-person summit in 3 years and they took elaborate COVID testing precautions. They shipped a Lucira kit for PCR quality testing at home. We ran a test 24 hours before our flight to Silicon Valley and repeated that test upon arrival at the event hotel. About 20 analysts showed up.

The second question turned out to be far more complex. Ray Wang of Constellation Research would have liked to have heard about the metaverse, DeFi and more contemporary tech trends. Other analysts had other questions like “what about treasury management?” I myself would have liked a bit more about how Workday is reacting given the "made for the moment" theme to current events in Ukraine and the energy transition focus it has created in every country and industry.

I have been lucky to feature in my Analyst Cam and Burning Platform video episodes several Workday executives and products in the last 2 years.  So, I expected a nice recap during the event.

What we did hear a lot about is Workday's architectural journey, their distinct M&A strategy and how their solutions enable what Workday calls the “Power to Adapt”.

I particularly liked the presentation by Sayan Chakraborty, EVP, Product & Technology where he said “We believe great applications can only exist alongside a great platform and from this combination - you get the 'power to adapt’”. Rather than try to just absorb acquisitions, Workday tries to benefit from the contemporary thinking at startups they acquire. More on how Workday’s architecture has evolved over 15 years in this episode of Analyst Cam with Sayan Chakraborty.

Pete Schlampp, Workday’s Chief Strategic Officer, told us about their growth in packaged solutions.  “Since starting this program last year, Workday and our partners have published 15 Packaged Solutions supporting the oCFO and oCHRO, with another 20 slated for FY23.” Packaged solutions are small bundles of contemporary features like VIBE they had presented to me here .

I have been pushing Workday to get more into operational areas in industries where they have plenty of presence – most in the services sector. For now, I am not worried about Workday’s disciplined approach and  continued focus on the financial, hcm and planning/analytical areas. Workday has been delivering plenty of innovation in these areas. They also have miles to go with their current focus. During the session, they talked about their global growth – there is so much more of the world to grow into. By my estimate only 5% of its employee base is in the APJ region. Same thing with the SME market – there are plenty of opportunities in subsidiaries of large companies and the higher end of the SME spectrum.

In my analyst role, I get to hear competition bashing on a regular basis. Workday is a frequent target. My question to the haters is “Why are you letting Workday so dramatically narrow your definition of addressable market? There is so much white space around them for you to exploit”.

Frankly, I wish they would speak like C0-CEO Aneel Bhusri did at the event. He generously complimented his peers and said he was proud of the software industry for how it had responded to the pandemic.

Analyst Cam: CaptivateIQ – Demystifying Sales Commissions

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

This time it is Mark Schopmeyer, co-founder and co-CEO of CaptivateIQ which has a no-code SaaS solution to manage the thorny area of sales compensation.

As with many “junction points” in the enterprise – in this case between sales operations, finance and HR compensation management - you find many spreadsheet applications and convoluted legacy/custom developed and user-unfriendly applications. CaptivateIQ has thrived in this niche. It is barely 5 years old. and says it has crunched $2.5 billion in sales commissions. Importantly it allows for transparency to the calcs so salespeople can focus more on selling and less on algorithms which drive their paycheck. No wonder they are already a “unicorn” - valued earlier this year in its Series C round at a $1.25 billion valuation.

Mark does a nice job explaining why sales commissions can be obtuse in many enterprises and how they are likely to become even more so as business models evolve and customer contracts blend product, service, data and other components across a product lifecycle.

I was introduced to them by Workday Ventures. They are an investor along with many others like Accel, Bessemer and Sequoia.

Crisply done in about 25 minutes.

Analyst Cam: Workday’s architectural journey

In a February episode of Burning Platform, we hosted a back and forth on architectural trends in the industry with Sayan Chakraborty, EVP of Product and Technology at Workday.  Here we have him back to present more specifically on Workday’s architectural journey.  He only presents 5 slides but makes powerful commentary.

He presents some high-level philosophy, he discusses how Workday has integrated several acquisitions – some analytical, other transaction processing heavy. But I really liked his description of how Workday’s architecture has evolved over 15 years

"Today, we have a highly scalable platform that can support millions of employees on a single instance of Workday. We have elastic capability, horizontally scaling elastic capability because you have business cycles. You do payroll on particular days and times. You run specific reports at times during the month or during the fiscal year.

If we look back 15 years ago, we would see a lot of general compute engines in the Workday stack. Today, you see a lot of highly specialized compute engines, and we send the right workload to the right engine.

• If you've got an analytics workload, it will go to the Prism technology that came in through the Platfora acquisition that is designed for that type of workload and optimize for that workload.
• We have the OMS transaction service in the middle of this diagram that handles our high-performance transaction workloads.
• We've got integration servers that handle the ins and outs, as you connect Workday to systems outside of Workday.
• You have ML workloads that move into our ML environment that have a different kind of usage rate, memory consumption, CPU usage than these other workloads.

            We can optimize for all of those, and I think that's really the dramatic difference. If you time-traveled back 15 years and showed this slide to architects at Workday, what they would be surprised by is the specialization and the elasticity and the horizontal scale that's now ...

The age when you would do machine learning processing at a hardware level on standard CPUs from Intel or AMD is essentially over. The industry realized that there were these devices, these GPUs that had been developed primarily for gaming, and realized that, hey, these are really, really interesting because of the way they tackle the processing problem, and we can leverage that capability – essentially, parallel processing versus serial processing (parallel at scale) – and those kinds of problems are the kinds of problems we have in deep learning networks or other kinds of workloads within the ML AI capability."

25 minutes of wizardry. Very well done.

Analyst Cam: CRM Watchlist

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

This time it is Paul Greenberg, Managing Principal, The 56 Group, LLC. He summarizes the results from his latest CRM Watchlist survey. He is a repeat guest and was last on the Burning Platform episode where we discussed generational shifts in content creation and distribution.

This is the 19^th edition of his signature, annual project. He describes how the effort has evolved over the years. Lot of factors go into his scoring and they change every year. As he says, he looks at a vendor’s strategy and scores it on how well they executed on what they said they would. He then measures the impact they had on the market. Impact as a company – so not just their architectural excellence or financial performance or social responsibility posture. And it is based on the vendor’s stated strategy and market focus – which allows smaller vendors to be evaluated fairly depending on how they delivered against their geographic, vertical or size of customer focus.

He does factor in what he calls “intangibles”. His scoring for that category is a bit less transparent considering how much he guides vendors about the others. But he shares one nugget - he deducts points for “competition bashing”. Good for him.

He is tough and thorough, but very fair. Does not matter if you are a client of his or a close friend. This year, he evaluated 59 vendors reading every word of the 4,682 pages (yes!) if they were submitted to his guidelines. It is a testament to his market impact that vendors spend so much time and effort on their responses.

He has three winning categories -Winners, Winners with Distinction, and Elite. Only a handful have qualified for the Elite designation over all these years. There were 4 winners with Distinction this time around – Oracle, ServiceNow, Thunderhead and Zoho. He discusses another 12 in the Winners tier. Zoho scored highest in total this year. It also submitted the longest response at 259 pages. Paul insists there is no correlation between size of the response and his scoring.

He also shares the vendors who scored highest for each of his categories and summarizes with 4 promising and 2 concerning trends he gleaned from this year's responses.

I have run competitive evaluations of software vendors and outsourcers for many a client. At Gartner, I ran similar structured reviews for Magic Quadrants and other long-form content. I feel no shame saying I did not ever come close to evaluating 50+ vendors or reading 4000+ response pages for a single deliverable.

Next year, Paul says will be the final Watchlist. I suspect he will get an even larger population of vendors who pay homage by participating. In the blog post he said “Since this upcoming one is the very last one so, if I'm you, I'm registering to take a crack at it. Even if most companies don't win the award, they more often than not appreciate the exercise that you go through to put together the submission because it, when completed, gives you a holistic look at your company that you otherwise do not have.  It's worth it for the workout.”

I will absolutely bring him back for to describe the process for the 20th in the series. In the meantime, I need to have him back around his other passion – professional sports. We can discuss Tom Brady’s “un-retirement”, the return of baseball after a near shutout and so much else.