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September 2022 - Winners Dream by Bill McDermott with Joanne Gordon

This month we hear about Bill McDermott’s meteoric rise to the CEO job at SAP and his philosophy around management. I must also acknowledge the incredible and underappreciated role that Julie McDermott and Bill’s family plays in this book. Bill moved his family from NYC to Puerto Rico to Chicago to Rochester to Connecticut to California to Philadelphia over the course of his 25-year career. Sometimes with multiple moves rather quickly. The selflessness they displayed is unfathomable.

Tech Themes

  1. Growing License Revenue at SAP. When Bill McDermott got to SAP North America, he quickly realized they were behind the game. The firm had enjoyed relatively unmatched success in its early years but was now coming into competition with one of Bill’s former employers - Siebel Systems. He saw what he viewed as lackluster standards - people were late to meetings, lacked professionalism, and moved painfully slowly on new action plans. McDermott created a new strategy around a $3B revenue target, and recruited the company’s top managers to share the plan in mini-meetings across every division. After providing the new strategy, he focused on value engineering, a way of demonstrating the ROI from implementing a company’s software. He instituted a weekly Top 20 Call, where the head of sales detailed the top 20 deals in progress, and Bill unleashed his sales intensity in helping people close deals. “What’s the business case? Have we presented it to the CEO? When is the next meeting? What, you just found out the company can’t sign because its purchasing director is on vacation? What’s your plan to backfill the loss? If someone didn’t know his next move, he wasn’t doing his job.” One of McDermott’s super-powers is maintaining a big vision while being able to slip into the micro-managing intensity of Andy Grove’s Only the Paranoid Survive and Ben Horowitz’s War-time CEO. 85% of C-Suite employees left, McDermott recruited 100 new sales employees, and in 2005, SAP America delivered $3.2B of revenue.

  2. Reinvention. McDermott is unafraid to go in new directions and take on new challenges. He had earned his stripes by taking over challenged business units in Xerox, first Puerto Rico, then Chicago, and then Xerox Business Services, their outsourcing division. Xerox at the time was suffering from a classic Innovator’s Dilemma - the XBS division was growing quickly but resulted in lower profit margins, so was not getting the love and admiration it deserved. “Instead of worrying about the value of my retirement account, I was interested in growing the business. Rather than ignoring the changing market, we should have been pouncing on it…Many people thought I was crazy to join the junior varsity team. XBS represented only 5 percent of Xerox’s overall revenues. Others even tried to block my transfer to XBS.” McDermott believed in the power of pageantry and held a massive, blow-out sales conference in San Antonio, complete with fake politicians and news style interview booths. McDermott had set a $4B revenue target for XBS and he missed the target. XBS revenue’s grew from 900m of revenue to $2B in 1997, $2.7B in 1998, $3.4B in 1999, and $3.8B in 2000, just missing the $4B revenue target by 2000. “Was I upset that we fell shy of our $4B bull’s-eye? Not one bit. The point of setting audacious goals was that we could almost hit them and still accomplish something amazing. Had we never strived so high, we never would have hit as high as we did.”

  3. Internet Bubble Comes Calling. Bill is human, like all of us, and so when the internet bubble started to take off, and he found himself on the sidelines managing an outsourcing business at struggling Xerox, he started to get the itch to get into the fray. A young startup called Techies.com had reached out asking if Bill would be their CEO. Bill considered it an interesting proposition - everything was going up and to the right and Techies could IPO as soon as next year. Techies.com was an online website for tech companies to post about job openings. After meeting everyone and interviewing for the job of CEO, Bill decides he can’t do it. “ The only thing about your company that really interests me is the money, and that’s the wrong reason to work for anyone.” Bill did get whisked away though, by another IT firm - Gartner. Bill had left Xerox for a whole 2 weeks in 1995 and joined Gartner at the urging of former Xerox executive, Follett Carter. McDermott joined Gartner in 2000, serving as President while Michael Fleisher served as CEO. He felt it was off from the first couple weeks on the job. “I saw it in the jeans and tieless shirts that even senior executives wore Mondays through Fridays. I felt it in Gartner’s small-company, New Economy culture, which shocked my corporate sensibilities.” Matters were maid worse when Julie McDermott was diagnosed with Breast Cancer. Things were tough for the year Bill was at Gartner, and he decided to move on to Siebel Systems where he worked with tech legend, Tom Siebel, founder of Siebel Systems and C3.AI. Bill would only last a year at Siebel too, burnt out after working tirelessly in the months following 9/11. In hindsight, each of these smaller steps into executive roles broadened Bill’s knowledge of the technology evolution and CRM space specifically. These would be the foundation for his job offer from SAP America in 2004.

Business Themes

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  1. Setting Ambitious Goals. Bill is no stranger to big roles and he absolutely relishes the spotlight. He has a smooth, calming, excited voice that shines through every word in the book. He is a big vision guy, but unafraid to get tactical in areas he knows well like sales. Having worked his way up from a rookie salesman at 22 to a district manager at Xerox, McDermott always took a similar approach to fixing broken organizations. When he got to his district manager role in Puerto Rico, the worst performing district in Xerox, he made it clear that things were going to change. He wanted to take Puerto Rico from the worst performing division to the best performing division in one year. He set out by asking the sales managers a simple question: “What do you need?” He slowly identified the issues holding the division back (a lack of investment, consistent expense cuts, and poor goal setting) and he fixed them. Puerto Rico became the number one sales group in Xerox. This extreme goal setting shows up multiple times in McDermott’s career. When he became head of Xerox’s outsourcing XBS division he set a $4B revenue goal. “Three billion dollars in revenue by 2000 was a more realistic goal yet still a dream target. So why not tell everyone $3B, Bill? Because my hurdle - getting my people ecstatic about selling outsourcing - was so high that I need to get everyone’s mind to a place where the dream soeemed so impossible that it was exciting to pursue. For more than a decade now, I’d watched teams rise to the expectations set for them. The more daring the target, the higher people rose.” When he got to SAP America, he proclaimed they’d be a $3B revenue business by 2005, after years of lackluster growth, “In the next three years, we are going to increase our revenue by one billion dollars. Since 1999, SAP America’s revenue had barely grown $100m, in total.” After a major operational overhaul, they achieved his goal. When he got to ServiceNow, he similarly announced a goal of $10B of annual revenue. Time will tell if he hits the goal.

  2. Big software M&A - Does it work? Bill McDermott was on the way to Hawaii when he got the call from SAP’s board about becoming Co-CEO of SAP. After the shock wore off, he quickly accepted the job, excited to lead the whole organization after he had successfully turned around SAP North America. Bill initially shared the CEO role with Jim Hagamann Snabe, a German engineer that would lead the product and engineering side of the business while Bill focused on commercial efforts. In 2014, Bill was named sole CEO, a new development for the traditional SAP that normally opted for a co-CEO model. Reflecting on it years later, Mcdermott commented in a Duke university visit in 2016, “Well, you know, when we were co-CEOs in 2010, it's what the company needed then. As you know, we were coming off the financial crisis of 2008. 2009 was a relatively slow recovery for the world, and SAP made a CEO change. And it was really important to have one office of the CEO with two friends, that really wanted to make a difference. And a lot of things needed to be done to build the company, build a strategy, do some major M&A moves, and get the company set up for growth again. And once that was done, then it became necessary to build on the vision but make much quicker decisions, move at a pace that was even beyond the pace we were moving at, which was pretty fast. And at that point, SAP needed that person that could make the call and be very, very decisive. And fortunately, things seem to be going pretty well.” McDermott launched an aggressive M&A campaign, spending $35B in acquisitions from 2010-2020. The acquisitions added about $3.4B of revenue to the company. These acquisitions were in all sorts of different areas but focused on SAP’s core areas including ERP, HCM, and Database technologies. I believe these acquisitions did two things simultaneously for SAP. Sirst it helped push a historically mainframe driven technology company into the cloud. Second, it broadened the capabilities of their core ERP offering while extending SAP into global markets, particularly strengthening its US position against ERP competitor Oracle, which had its own ERP and HCM applications. While these acquisitions worked for a time, the company is still fighting its license/maintenance past, and trying to move more aggressively to the cloud. The positive way to view these deals is Bill grew the organization, its capabilities, and its reach while using modest amounts of leverage and growing the company’s revenue and EPS. The negative way to view it is Bill went on a shopping spree of random technologies that were never fully integrated, and today saddle the company with enormous tech debt, little flexibility, and sub-par growth.

  3. The Journey: Ithaca to CEO. Bill is a strong proponent of enjoying one’s career journey over its destination. As a night MBA student at Kellogg, he learned of the C.P Cavafy poem, Ithaca, which reads: “Keep Ithaka always in your mind. Arriving there is what you’re destined for. But don’t hurry the journey at all. Better if it lasts for years, so you’re old by the time you reach the island, wealthy with all you’ve gained on the way, not expecting Ithaka to make you rich. Ithaka gave you the marvelous journey. Without her you wouldn't have set out. She has nothing left to give you now. And if you find her poor, Ithaka won’t have fooled you. Wise as you will have become, so full of experience, you’ll have understood by then what these Ithakas mean.” As he contemplated moving on from Xerox, and pushing away his dream of becoming CEO, he came back to this poem, using it as a base before writing out his core beliefs and goals. “ My personal goals included having quality time with my family; to love Julie with the enthusiasm and compassion of our wedding day; to help my son (and eventually his sibling) grow into a healthy, happy, well-adjusted adult; to love my parents and my brother and sister, always remembering my roots, and to live with passion every day. Next, I listed my career aspirations: 1. To be a winner. 2. To lead others to the doorstep of their dreams. 3. To manage a career and not the other way around. 4. To never confuse that which is most important with that which is not. 5. To earn a living commensurate with my talent, but not be ruled by the shallow shadows of money. 6. To be the ruler of my own destiny, not to slave for what someone else wants my destiny to be - in control.” Ten years later, when he was considering moving on from Siebel Systems, Bill re-wrote his goals again and realized that he wanted to be in control of his own destiny. “ I wanted my freedom back. I was ready to be a CEO.”

Dig Deeper

  • SAP’s CEO on Being the American Head of a German Multinational

  • Distinguished Speakers Series - Bill McDermott, CEO, SAP

  • The Inside View with Bill McDermott

  • Grit Podcast - Chairman & CEO ServiceNow, Bill McDermott

  • Think bold - Tough times call for tough people, says Kellogg School alum and CEO

tags: Bill McDermott, SAP, ServiceNow, Xerox, Gartner, Sybase, Siebel Systems, Andy Grove, Techies.com, Tom Siebel
categories: Non-Fiction
 

February 2021 - Rise of the Data Cloud by Frank Slootman and Steve Hamm

This month we read a new book by the CEO of Snowflake and author of our November 2020 book, Tape Sucks. The book covers Snowflake’s founding, products, strategy, industry specific solutions and partnerships. Although the content is somewhat interesting, it reads more like a marketing book than an actually useful guide to cloud data warehousing. Nonetheless, its a solid quick read on the state of the data infrastructure ecosystem.

Tech Themes

  1. The Data Warehouse. A data warehouse is a type of database that is optimized for analytics. These optimizations mainly revolve around complex query performance, the ability to handle multiple data types, the ability to integrate data from different applications, and the ability to run fast queries across large data sets. In contrast to a normal database (like Postgres), a data warehouse is purpose-built for efficient retrieval of large data sets and not high performance read/write transactions like a typical relational database. The industry began in the late 1970s and early 80’s, driven by work done by the “Father of Data Warehousing” Bill Inmon and early competitor Ralph Kimball, who was a former Xerox PARC designer. In 1986, Kimball launched Redbrick Systems and Inmon launched Prism Solutions in 1991, with its leading product the Prism Warehouse Manager. Prism went public in 1995 and was acquired by Ardent Software in 1998 for $42M while Red Brick was acquired by Informix for ~$35M in 1998. In the background, a company called Teradata, which was formed in the late 1970s by researchers at Cal and employees from Citibank, was going through their own journey to the data warehouse. Teradata would IPO in 1987, get acquired by NCR in 1991; NCR itself would get acquired by AT&T in 1991; NCR would then spin out of AT&T in 1997, and Teradata would spin out of NCR through IPO in 2007. What a whirlwind of corporate acquisitions! Around that time, other new data warehouses were popping up on the scene including Netezza (launched in 1999) and Vertica (2005). Netezza, Vertica, and Teradata were great solutions but they were physical hardware that ran a highly efficient data warehouse on-premise. The issue was, as data began to grow on the hardware, it became really difficult to add more hardware boxes and to know how to manage queries optimally across the disparate hardware. Snowflake wanted to leverage the unlimited storage and computing power of the cloud to allow for infinitely scalable data warehouses. This was an absolute game-changer as early customer Accordant Media described, “In the first five minutes, I was sold. Cloud-based. Storage separate from compute. Virtual warehouses that can go up and down. I said, ‘That’s what we want!’”

  2. Storage + Compute. Snowflake was launched in 2012 by Benoit Dageville (Oracle), Thierry Cruanes (Oracle) and Marcin Żukowski (Vectorwise). Mike Speiser and Sutter Hill Ventures provided the initial capital to fund the formation of the company. After numerous whiteboarding sessions, the technical founders decided to try something crazy, separating data storage from compute (processing power). This allowed Snowflake’s product to scale the storage (i.e. add more boxes) and put tons of computing power behind very complex queries. What may have been limited by Vertica hardware, was now possible with Snowflake. At this point, the cloud had only been around for about 5 years and unlike today, there were only a few services offered by the main providers. The team took a huge risk to 1) bet on the long-term success of the public cloud providers and 2) try something that had never successfully been accomplished before. When they got it to work, it felt like magic. “One of the early customers was using a $20 million system to do behavioral analysis of online advertising results. Typically, one big analytics job would take about thirty days to complete. When they tried the same job on an early version of Snowflake;’s data warehouse, it took just six minutes. After Mike learned about this, he said to himself: ‘Holy shit, we need to hire a lot of sales people. This product will sell itself.’” This idea was so crazy that not even Amazon (where Snowflake runs) thought of unbundling storage and compute when they built their cloud-native data warehouse, Redshift, in 2013. Funny enough, Amazon also sought to attract people away from Oracle, hence the name Red-Shift. It would take Amazon almost seven years to re-design their data warehouse to separate storage and compute in Redshift RA3 which launched in 2019. On top of these functional benefits, there is a massive gap in the cost of storage and the cost of compute and separating the two made Snowflake a significantly more cost-competitive solution than traditional hardware systems.

  3. The Battle for Data Pipelines. A typical data pipeline (shown below) consists of pulling data from many sources, perform ETL/ELT (extract, load, transform and vice versa), centralizing it in a data warehouse or data lake, and connecting that data to visualization tools like Tableau or Looker. All parts of this data stack are facing intense competition. On the ETL/ELT side, you have companies like Fivetran and Matillion and on the data warehouse/data lake side you have Snowflake and Databricks. Fivetran focuses on the extract and load portion of ETL, providing a data integration tool that allows you to connect to all of your operational systems (salesforce, zendesk, workday, etc.) and pull them all together in Snowflake for comprehensive analysis. Matillion is similar, except it connects to your systems and imports raw data into Snowflake, and then transforms it (checking for NULL’s, ensuring matching records, removing blanks) in your Snowflake data warehouse. Matillion thus focuses on the load and transform steps in ETL while Fivetran focuses on the extract and load portions and leverages dbt (data build tool) to do transformations. The data warehouse vs. data lake debate is a complex and highly technical discussion but it mainly comes down to Databricks vs. Snowflake. Databricks is primarily a Machine Learning platform that allows you to run Apache Spark (an open-source ML framework) at scale. Databricks’s main product, Delta Lake allows you to store all data types - structured and unstructured for real-time and complex analytical processes. As Datagrom points out here, the platforms come down to three differences: data structure, data ownership, and use case versatility. Snowflake requires structured or semi-structured data prior to running a query while Databricks does not. Similarly, while Snowflake decouples data storage from compute, it does not decouple data ownership meaning Snowflake maintains all of your data, whereas you can run Databricks on top of any data source you have whether it be on-premise or in the cloud. Lastly, Databricks acts more as a processing layer (able to function in code like python as well as SQL) while Snowflake acts as a query and storage layer (mainly driven by SQL). Snowflake performs best with business intelligence querying while Databricks performs best with data science and machine learning. Both platforms can be used by the same organizations and I expect both to be massive companies (Databricks recently raised at a $28B valuation!). All of these tools are blending together and competing against each other - Databricks just launched a new LakeHouse (Data lake + data warehouse - I know the name is hilarious) and Snowflake is leaning heavily into its data lake. We will see who wins!

An interesting data platform battle is brewing that will play out over the next 5-10 years: The Data Warehouse vs the Data Lakehouse, and the race to create the data cloud

Who's the biggest threat to @snowflake? I think it's @databricks, not AWS Redshifthttps://t.co/R2b77XPXB7

— Jamin Ball (@jaminball) January 26, 2021

Business Themes

Lakehouse_v1.png
architecture-overview.png
  1. Marketing Customers. This book at its core, is a marketing document. Sure, it gives a nice story of how the company was built, the insights of its founding team, and some obstacles they overcame. But the majority of the book is just a “Imagine what you could do with data” exploration across a variety of industries and use cases. Its not good or bad, but its an interesting way of marketing - that’s for sure. Its annoying they spent so little on the technology and actual company building. Our May 2019 book, The Everything Store, about Jeff Bezos and Amazon was perfect because it covered all of the decision making and challenging moments to build a long-term company. This book just talks about customer and partner use cases over and over. Slootman’s section is only about 20 pages and five of them cover case studies from Square, Walmart, Capital One, Fair, and Blackboard. I suspect it may be due to the controversial ousting of their long-time CEO Bob Muglia for Frank Slootman, co-author of this book. As this Forbes article noted: “Just one problem: No one told Muglia until the day the company announced the coup. Speaking publicly about his departure for the first time, Muglia tells Forbes that it took him months to get over the shock.” One day we will hear the actual unfiltered story of Snowflake and it will make for an interesting comparison to this book.

  2. Timing & Building. We often forget how important timing is in startups. Being the right investor or company at the right time can do a lot to drive unbelievable returns. Consider Don Valentine at Sequoia in the early 1970’s. We know that venture capital fund performance persists, in part due to incredible branding at firms like Sequoia that has built up over years and years (obviously reinforced by top-notch talents like Mike Moritz and Doug Leone). Don is a great investor and took significant risks on unproven individuals like Steve Jobs (Apple), Nolan Bushnell (Atari), and Trip Hawkins (EA). But he also had unfettered access to the birth of an entirely new ecosystem and knowledge of how that ecosystem would change business, built up from his years at Fairchild Semiconductor. Don is a unique person and capitalized on that incredible knowledgebase, veritably creating the VC industry. Sequoia is a top firm because he was in the right place at the right time with the right knowledge. Now let’s cover some companies that weren’t: Cloudera, Hortonworks, and MapR. In 2005, Yahoo engineers Doug Cutting and Mike Cafarella, inspired by the Google File System paper, created Hadoop, a distributed file system for storing and accessing data like never before. Hadoop spawned many companies like Cloudera, Hortonworks, and MapR that were built to commercialize the open-source Hadoop project. All of the companies came out of the gate fast with big funding - Cloudera raised $1B at a $4B valuation prior to its 2017 IPO, Hortonworks raised $260M at a $1B valuation prior to its 2014 IPO, and MapR $300M before it was acquired by HPE in 2019. The companies all had one thing in problem however, they were on-premise and built prior to the cloud gaining traction. That meant it required significant internal expertise and resources to run Cloudera, Hortonworks, and MapR software. In 2018, Cloudera and Hortonworks merged (at a $5B valuation) because the competitive pressure from the cloud was eroding both of their businesses. MapR was quietly acquired for less than it raised. Today Cloudera trades at a $5B valuation meaning no shareholder return since the merger and the business is only recently slightly profitable at its current low growth rate. This cautionary case study shows how important timing is and how difficult it is to build a lasting company in the data infrastructure world. As the new analytics stack is built with Fivetran, Matillion, dbt, Snowflake, and Databricks, it will be interesting to see which companies exist 10 years from now. Its probable that some new technology will come along and hurt every company in the stack, but for now the coast is clear - the scariest time for any of these companies.

  3. Burn Baby Burn. Snowflake burns A LOT of money. In the Nine months ended October 31, 2020, Snowflake burned $343M, including $169M in their third quarter alone. Why would Snowflake burn so much money? Because they are growing efficiently! What does efficient growth mean? As we discussed in the last Frank Slootman book - sales and marketing efficiency is a key hallmark to understand the quality of growth a company is experiencing. According to their filings, Snowflake added ~$230M of revenue and spent $325M in sales and marketing. This is actually not terribly efficient - it supposes a dollar invested in sales and marketing yielded $0.70 of incremental revenue. While you would like this number to be closer to 1x (i.e. $1 in S&M yield $1 in revenue - hence a repeatable go-to-market motion), it is not terrible. ServiceNow (Slootman’s old company), actually operates less efficiently - for every dollar it invests in sales and marketing, it generates only $0.55 of subscription revenue. Crowdstrike, on the other hand, operates a partner-driven go-to-market, which enables it to generate more while spending less - created $0.90 for every dollar invested in sales and marketing over the last nine months. However, there is a key thing that distinguishes the data warehouse compared to these other companies and Ben Thompson at Stratechery nails it here: “Think about this in the context of Snowflake’s business: the entire concept of a data warehouse is that it contains nearly all of a company’s data, which (1) it has to be sold to the highest levels of the company, because you will only get the full benefit if everyone in the company is contributing their data and (2) once the data is in the data warehouse it will be exceptionally difficult and expensive to move it somewhere else. Both of these suggest that Snowflake should spend more on sales and marketing, not less. Selling to the executive suite is inherently more expensive than a bottoms-up approach. Data warehouses have inherently large lifetime values given the fact that the data, once imported, isn’t going anywhere.” I hope Snowflake burns more money in the future, and builds a sustainable long-term business.

Dig Deeper

  • Early Youtube Videos Describing Snowflake’s Architecture and Re-inventing the Data Warehouse

  • NCR’s spinoff of Teradata in 2007

  • Fraser Harris of Fivetran and Tristan Handy of dbt speak at the Modern Data Stack Conference

  • Don Valentine, Sequoia Capital: "Target Big Markets" - A discussion at Stanford

  • The Mike Speiser Incubation Playbook (an essay by Kevin Kwok)

tags: Snowflake, Data Warehouse, Oracle, Vertica, Netezza, IBM, Databricks, Apache Spark, Open Source, Fivetran, Matillion, dbt, Data Lake, Sequoia, ServiceNow, Crowdstrike, Cloudera, Hortonworks, MapR, BigQuery, Frank Slootman, Teradata, Xerox, Informix, NCR, AT&T, Benoit Dageville, Mike Speiser, Sutter Hill Ventures, Redshift, Amazon, ETL, Hadoop, SQL
categories: Non-Fiction
 

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