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Jamin Ball Profile picture
@jaminball
Jan 12, 2022 • 8 tweets • 2 min read • Read on X
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Some takeaways from Morgan Stanley's Q4 CIO survey

- Software has the highest growth expectations in IT
- Strong demand in software persisting (not simply pull forward in 2021)
- Cloud computing remains CIO's top priorities
- Security software most defensible

More graphs below
"Survey data suggests 25% of application workloads are running in the public cloud today, up from 23%... in 2Q21. The multi-year trend in the migration of applications to the cloud remains intact, with CIOs expecting 44% of workloads to reside in public cloud by 2024"
Similar data but presented differently. We're in the early innings of the cloud
Cloud computing, security software, and digital transformation are the top 3 priorities
Security software remains the most defensible category
"As workloads continue to shift from on-premise to the cloud, Microsoft and Amazon remain the largest beneficiaries , both in 2021, as well as over the next three years"
"Snowflake screens as the vendor with the highest weighted average growth expectations in 2022 at +7.1%...30% of CIOs surveyed expecting spend to increase in 2022, vs. 0% of CIOs expecting spend to decrease."

Microsoft has the highest up-to-down ratio of 70%
Maybe most importantly:

"Expectations for software spending growth in 2022 remain ahead of historical levels, refuting the notion of a pull forward in demand in CY21"

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More from @jaminball

Jamin Ball Profile picture
Jul 17
We're entering the Fourth Industrial Revolution: The Intelligence Revolution

The First Industrial Revolution (circa 1760-1840): Known for the rise of mechanized manufacturing, and the rise of new technologies like the steam engine and power loom

The Second Industrial Revolution (circa 1870-1914): The Technological Revolution. This period was characterized by the advent of electricity and mass production processes. Railways and the invention of the telegraph and telephone were key developments

The Third Industrial Revolution (circa 1960-early 2000's): The Digital Revolution. This period introduced the shift from analog and mechanical technologies to digital electronics. Computers, the internet and proliferation of digital communication were key developments

The Fourth Industrial Revolution (~2017 - Present): The Intelligence Revolution. Foundation models and AI are just starting to drive significant change, and we're only a couple years in. I expect huge developments in life sciences, robotics, software, and many other markets

But what needs to happen to enable the Intelligence Revolution? We need significant infrastructure buildout of data centers. Data centers are the enabling piece, the foundational layer. In every industrial revolution we had an infrastructure buildout followed by a dramatic increase in revenue / production. Much has been written on one component of the data center - the GPUs / compute. In particular, the spend on GPUs vs the relative revenue generated from AI Intelligence Systems. Right now we are in the early days - the infrastructure buildout phase of this industrial revolution. The revenue / production phase will follow

In my post below (end of thread) I explore the 11 core components of a data center

1. Servers
2. Networking
3. Storage
4. Cooling
5. Power Infrastructure + Power Utility
6. Security
7. Management and Monitoring
8. Racks and Cabinets
9. Cabling
10. Environmental Controls
11. Software
1. Servers. Servers are the backbone of data centers, providing the computational power necessary for processing and managing data. They house crucial components such as CPUs, GPUs, memory, and storage.
2. Networking. Networking infrastructure ensures efficient data flow within and between data centers. This includes routers, switches, firewalls, load balancers, and high-speed interconnects, and communication standards like ethernet and infiniband
Read 13 tweets
Jamin Ball Profile picture
Mar 2, 2023
After Q3 '22 Snowflake guided to 47% growth in 2023. Yesterday they dropped that guide to 40%. What was the cause? 3 things primarily (in ascending order of impact)

1. Change in existing customer purchasing behavior
2. Weaker new logo bookings
3. Slower ramp from newer customers
1. Change in existing customer purchasing behavior

Snowflake sells annual / multi year deals that come with minimum consumption spend. Once customers reach those committed spend levels, they have the choice to re-up with another multi-year commitment. Usually, they do...
...however, this quarter Snowflake saw more of these customers buy just enough capacity to get them through the next few months, nothing more.

Important to remember - the bigger impact of this is on bookings (more on this later), not revenue. Customers are still consuming...
Read 10 tweets
Jamin Ball Profile picture
Feb 17, 2023
Some takeaways from the Datadog earnings call:

Positives
- Strongest new logo quarter
- Gross churn very low
- Healthy pipeline generation

Negatives
- More optimizations in Q4 than Q2 / Q3
- Things got worse in December
- Weak 2023 guide

$DDOG
The best summary quote from the earnings call was "Overall, we observed slower usage growth with existing customers while continuing to scale our new logo acquisition and new product cross-sells."
The tricky balance is the commentary around the record new logo quarter + strong pipeline generation with weaker near term optimization headwinds

Some quotes:

"we had our strongest new logo quarter to date, with a record level of new logo ARR bookings"
Read 9 tweets
Jamin Ball Profile picture
Jan 31, 2023
Investing in infrastructure businesses, particularly data infrastructure, has been incredibly exciting over the last few years (and will continue to be!). A couple data infra stacks Im excited about

1) Analytics stack
2) Real time stack
3) Data Lake stack
4) AI stack

More below
1. The Analytics Stack (or Modern Data Stack). Typically consists of:
1) Data Source (transactional database, SaaS app, etc)
2) ELT tool (Fivetran, Airbyte, etc)
3) Data Warehouse (Snowflake, Redshift, etc)
4) Data Transformation tool (dbt)
5) BI (Looker, Sigma, etc)
We hear a lot about this stack. Budgets are massive for it, and many companies have hit escape velocity building different layers of the stack. How each vendor evolves will be interesting to watch. There are also newer parts of this stack emerging (Reverse ETL, Data quality, etc
Read 14 tweets
Jamin Ball Profile picture
Dec 1, 2022
Consumption models under fire this year given easier to optimize (reduce) spend quickly. This pain happens quick.

However, everything I'm hearing pointing to new customer signups posing the biggest challenges currently, and expansion / churn seeing relatively less pressure...
...Models more reliant on new customer signups for growth feeling more pain now, vs consumption models felt it earlier in the year.

What do I think of this? 2023 might be the year consumption models actually show more resiliency (less growth decay)...
...If more of your growth is coming from scaling existing customers vs signing up new ones, it'll be easier next year when the burden of getting through procurement / legal for a new customer signup gets tougher.

Of course, it's never purely a business model question...
Read 6 tweets
Jamin Ball Profile picture
Nov 30, 2022
Read through the Crowdstrike transcript. Some takeaways re macro. Let's start with the positives

1. Gross & net retention not deteriorating:

"Our dollar-based net retention rate was well above Q3 of last year and consistent with our Q2 performance, which was at the...
... highest level in seven quarters. Our best-in-class gross retention rates remained at record levels above 98%"

2. Enterprise sales cycles staying constant:

"In the enterprise, sales cycles or average days to close remain consistent with last quarter's modestly higher level."
3. Deals delayed, not lost:

"While sales cycles lengthen, we believe the vast majority of these deals are not lost, just delayed."
Read 16 tweets

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