How can CIOs address rising geopolitical risks?

On McKinsey Perspectives

DELIVERING ACTIONABLE INSIGHTS ON THE DAY’S NEWS

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Confronting geopolitical challenges

In the news

•

C-suite priorities. In an era of heightened uncertainty, CEOs regard their chief information officers (CIOs) as critical to mitigating risks, enhancing profitability, and leading organizational transformations, with a strong focus on using AI to achieve these goals, CIO reports. Geopolitical issues such as trade disputes and regional tensions are becoming top concerns for CEOs. A Conference Board survey finds that eight in ten CEOs view supply chain changes—an area where CIOs play a key role in evaluating—as an opportunity to reduce costs and minimize disruptions. [CIO]

•

A global approach to compliance. Before kicking off AI projects, businesses face many considerations. As CIO Dive notes, a chief concern for CIOs is compliance with the range of AI laws and regulations across countries and jurisdictions. Enterprises must be aware of the specific locations where AI platforms are deployed, as the legal requirements differ widely. Some organizations are tackling this complexity by striving to meet the most stringent standards. “A siloed approach . . . just doesn’t cut it anymore,” a senior legal adviser explains. [CIO Dive]

Recent McKinsey Global Surveys on economic sentiment find that geopolitics is a top concern for executives, which creates broad momentum and support for tech leaders to address these issues.

On McKinsey.com

•

Under pressure. In the past decade, geopolitical developments have put the global IT operating model under immense pressure—and corporate CIOs are on the front line. They are confronting a patchwork of data laws, increased costs and complexity, and escalating cyberattacks. But current IT policies and models generally aren’t up to the task of addressing the range of geopolitical risks, McKinsey Partner James Kaplan and his coauthors explain. They say that CIOs will need to revise their risk practices, create new ones, and adjust their global operations—by, for example, partnering with business leaders to help shape decisions regarding geopolitical risk.

•

Mapping critical assets. A focus on traditional tech risk goals such as availability, delivery, and uptime isn’t sufficient for organizations to tackle geopolitical risk. (For example, a company might pass a cyberattack test but still be vulnerable if too many of its assets are concentrated into a single geographic area.) To understand their companies’ true risks, CIOs and chief technology officers need to identify which assets and teams support critical business functions and have a detailed understanding of both their assets and people. Discover nine types of failure modes related to geopolitical risk.

Navigate volatility

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EP166: What is Event Sourcing?

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EP166: What is Event Sourcing?

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This week’s system design refresher:

Trillions of Web Pages: Where Does Google Store Them? (Youtube video)
How Do Companies Ship Code to Production?
What is Event Sourcing?
How Data Lake Architecture Works
How Netflix Built a Distributed Counter
How TCP Handshake Works?
Early teams hiring engineers
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How Do Companies Ship Code to Production?

No alternative text description for this image

Here are 11 steps from planning to production:

The Product Owner starts the entire process by creating user stories in a tool like Jira.
The Developer Team performs Sprint Planning activity and adds the user stories to the sprint.
Developers work on the assigned stories. Once a story is finished, they commit the code to Git and push it to GitHub.
Jenkins builds and runs the code through testing and quality check tools such as JUnit, Jacoco, and SonarQube.
If the build is successful, it is stored in the artifactory such as JFrog. Jenkins also deploys the build to the Dev Environment via Docker.
Next up, the feature gets deployed to the QA environment. Since multiple teams may be working on the same code base, multiple QA environments will be created
The QA team uses a particular QA environment and runs multiple test types such as QA, regression, and performance.
Once the QA verification is complete, features are deployed to the UAT (User Acceptance Testing) environment.
UAT testing verifies whether the feature satisfies the user’s requirements.
Once the UAT testing is successful, the builds become release candidates. They are deployed to the production environment based on a specific schedule.
The SRE team uses tools like ELK and Prometheus to monitor the production environment and handle alerts in case of issues.

Over to you: Will you add any other steps to the process?

What is Event Sourcing? How is it different from normal CRUD design?

The diagram below shows a comparison of normal CRUD system design and event sourcing system design. We use an order service as an example.

The event sourcing paradigm is used to design a system with determinism. This changes the philosophy of normal system designs.

How does this work? Instead of recording the order states in the database, the event sourcing design persists the events that lead to the state changes in the event store. The event store is an append-only log. The events must be sequenced with incremental numbers to guarantee their ordering. The order states can be rebuilt from the events and maintained in OrderView. If the OrderView is down, we can always rely on the event store which is the source of truth to recover the order states.

Let's look at the detailed steps.

Non-Event Sourcing
- Steps 1 and 2: Bob wants to buy a product. The order is created and inserted into the database.
- Steps 3 and 4: Bob wants to change the quantity from 5 to 6. The order is modified with a new state.
Event Sourcing
- Steps 1 and 2: Bob wants to buy a product. A NewOrderEvent is created, sequenced, and stored in the event store with eventID=321.
- Steps 3 and 4: Bob wants to change the quantity from 5 to 6. A ModifyOrderEvent is created, sequenced, and persisted in the event store with eventID=322.
- Step 5: The order view is rebuilt from the order events, showing the latest state of an order.

Over to you: Which type of system is suitable for event sourcing design? Have you used this paradigm in your work?

How Data Lake Architecture Works?

A data lake is a centralized storage system that holds large volumes of structured, semi-structured, and unstructured data in its raw form. It allows organizations to store data at scale and process it later for different requirements.

Here’s how it works on a high level:

Data from diverse sources like S3, Excel files, databases, videos, images, sensors, and PDFs is collected for ingestion.
Ingestion happens via real-time streaming or batch/scheduled jobs, depending on the data type and source.
Ingested data is first stored in a raw data store before any transformation or processing occurs.
Data is then processed through batch or real-time processing systems to clean, transform, and prepare it for use.
The processed data is stored and made ready for downstream consumption by various tools and platforms.
Final data consumption happens through dashboard, AI models, data warehouse, real-time alerts, and reporting systems.

Over to you: What else will you add to better understand the Data Lake Architecture?

How Netflix Built a Distributed Counter

The Netflix distributed counter is a masterclass for learning system design.

A Distributed Counter is a system where the responsibility of counting events is spread across multiple servers or nodes in a network. Netflix needs to track and measure multiple user interactions to make real-time decisions and optimize its infrastructure.

For this reason, they built a Distributed Counter Abstraction.

Netflix’s Distributed Counter Abstraction operates in four main layers, ensuring high performance, scalability, and eventual consistency.

Client API Layer
Users interact with the system by sending AddCount, GetCount, or ClearCount requests. The Netflix Data Gateway efficiently processes and routes these requests.
Event Logging and TimeSeries Storage
Events are stored in Netflix TimeSeries Abstraction for scalability. Each event is tagged with an Event ID to ensure idempotency. To avoid database contention, events are grouped into time partitions known as buckets. Data is stored in Cassandra.
Rollup Pipeline or Aggregation
Rollup Queues collect event changes and process them in batches. Aggregation occurs in immutable time windows, ensuring accurate rollup calculations. Data is stored in the Cassandra Rollup Store for eventual consistency.
Read Optimization (Cache & Query Handling)
Aggregated counter values are cached in EVCache for ultra-fast reads. If a cache value is stale, a background rollup refresh updates it. This model allows Netflix to process 75K requests per second with single-digit millisecond latency.

Reference: Netflix’s Distributed Counter Abstraction

How TCP Handshake Works?

There are three steps in the handshake process:

SYN (Synchronize)
Think of it as one party extending its hand for a handshake. The process starts with the client sending a TCP segment to the server with the SYN flag. Also, an initial sequence number (ISN) is sent along with the message.
SYN-ACK
This is like the second party agreeing to the handshake. The server receives the SYN segment and responds by sending a TCP segment to the client. It sets the SYN flag and the ACK flag in the segment. The ACK flag is meant to acknowledge the receipt of the client’s SYN segment by incrementing the ISN.
ACK
This is where the two parties shake hands. The client receives the SYN-ACK segment and acknowledges the server’s response by sending another TCP segment with the ACK flag set. The sequence number is set to the server’s ISN after incrementing.

Some more points worth considering:

SYN and ACK are control flags used to manage different aspects of the communication process.
Sequence numbers (ISN) help the client and server keep track of the message order so that nothing gets missed.

Over to you: What else will you add to understand the TCP Handshake process in a better way?

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5 moves CEOs can make to strengthen organizational resilience

Monthly Highlights

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Monthly Highlights, June 2025

Today’s CEOs accept that disruption is inevitable, but many still underestimate the importance of building resilience. In this month’s featured article, McKinsey’s Ida Kristensen and coauthors outline five actions leaders can take to strengthen their organizations against future shocks. They also unpack the four essential types of resilience every CEO should master: financial, operational, organizational, and external. Other highlights include the following topics:

•

how a handful of standout organizations are powering most of national productivity growth

•

key insights into the state of global private markets in 2024

•

how business leaders can stay ahead by aligning near- and long-term strategies amid shifting trade policies

•

why upskilling is critical to building a more flexible, future-ready American workforce

Editor’s choice

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The CEO as chief resilience officer

CEOs sit at the nexus of strategy, finance, and operations, which makes them uniquely positioned to champion for and build resilience that can protect their companies from—and take advantage of—disruption.

Rise to the occasion

THIS MONTH’s HIGHLIGHTS

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The power of one: How standout firms grow national productivity

National productivity growth is a matter of few firms taking bold strategic action rather than millions of firms raising efficiency.
A new playbook

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Global Private Markets Report 2025: Braced for shifting weather

Global private markets navigated uncertain conditions in 2024, leading to an uneven recovery across different asset classes.
Access the 92-page report

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In a moment of tariffs, can the world find balance and trust to thrive?

Amid tariff uncertainty and a possible recession, the world needs a new base of balance and trust to create a thriving economy. Business has a vital role to play.
Build trust and balance

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The upskilling imperative: Required at scale for the future of work

Survey results highlight Americans’ willingness to change jobs and occupations—if they can gain the needed skills.
The missing ingredient

The State of Aviation 2025

Can the aviation industry soar to new heights, or will headwinds slow its progress?
Navigate the key trends

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The path toward a metabolic health revolution

The advent of weight management drugs such as GLP-1s have brought the treatment of obesity to the forefront of public attention, provoking a larger opportunity to work toward metabolic health for all.
Explore groundbreaking treatments

ALSO New

Risk rebalancing: Five important geopolitical-risk questions for CIOs

The new face of wealth: The rise of the female investor

Don’t get stuck in a rut—update how you operate

From protection to promotion: The new age of industrial policy

Leading, not lagging: Africa’s gen AI opportunity

GLP-1s are boosting demand for medical aesthetics

Lessons for US deputy secretaries on effective federal management

How CEOs can outcompete by building new B2C businesses

A generational shift: The future of foreign aid

Lead or lag: CEOs must embrace AI at full speed

Women in the Workplace 2025: India, Nigeria, and Kenya

The new economics of enterprise technology in an AI world

How circularity can make the built environment more sustainable

Heartbeat of health: Reimagining the healthcare workforce of the future

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by "Cotheran Poduska" <poduskacotheran@gmail.com> - 08:01 - 6 Jun 2025

Let’s talk API governance in 2025

View in browser

Let's talk
API governance
in 2025

Hi Md Abul

APIs now make up over 71% of web traffic, and security incidents are on the rise.

Could the cure be better governance? Done well, it can:

Promote creativity and innovation
Deliver business agility
Enhance API reusability
Reduce total cost of ownership
Help measure ROI
Reduce security risks
Support a seamless compliance journey

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by "Carol from Tyk" <communities@tyk.io> - 08:53 - 6 Jun 2025

How standout firms propel productivity growth

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Boosting productivity at the business level

In the news

•

Deferred investments. In recent years, the US economy has seen its labor productivity grow—an important trend that enables businesses to raise employee wages, manage inflation, and propel long-term economic growth, according to Marketplace. The country’s recent productivity gains are due in part to low unemployment, which empowers employees to seek better-paying roles, a senior economist says. However, shifting trade policies could threaten this progress by causing businesses to delay their investments in equipment, factories, and R&D. A slowdown in productivity could have lasting effects on the US economy for decades to come. [Marketplace]

•

Declining productivity. Bloomberg reports that in the first quarter of 2025, US labor productivity declined for the first time since 2022, ending a stretch of efficiency improvements that had helped keep inflation in check. Government data showed that productivity, measured as nonfarm worker output per hour, decreased at an annualized rate of 0.8%. The drop in productivity was driven primarily by a decline in business output, which fell by 0.3%. [Bloomberg]

In the US, 5% of surveyed firms generated 78% of positive productivity growth between 2011 and 2019.

On McKinsey.com

•

Rethinking productivity. Now more than ever, the world needs robust productivity growth to address major global issues, and businesses play a vital role in boosting national productivity. The conventional view of productivity growth is that it emerges gradually, through the incremental improvements of many companies. However, analysis from the McKinsey Global Institute (MGI) finds that a small number of firms actually contribute the lion’s share of national productivity growth, according to Senior Partners Chris Bradley and Olivia White and their coauthors.

•

Powerful growth. As companies find new ways to create and scale new value, the MGI findings suggest that productivity grows in powerful bursts. In a sample of about 8,300 large companies across Germany, the UK, and the US, fewer than 100 firms—called productivity “standouts”—accounted for two-thirds of productivity growth in each of those countries. See the four types of productivity standouts, including improvers (large companies that made the largest contribution to productivity growth) and register for a webcast with several of the authors on Tuesday, June 24.

Reimagine the path to productivity

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SQL vs NoSQL: Choosing the Right Database for An Application

͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏

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SQL vs NoSQL: Choosing the Right Database for An Application

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Every modern application, from a ride-hailing service to an e-commerce platform, relies on data, and behind that data sits a database. Whether it's storing customer profiles, tracking inventory, or logging user actions, the database is more than just a storage engine. It's the core system that holds an application’s state together. When the database fails, everything else (APIs, front-end, business logic) comes tumbling down.

Therefore, choosing the right kind of database is critical, but it isn't a one-size-fits-all decision.

Relational databases, such as MySQL and PostgreSQL, have been the default for decades. They offer strong consistency, well-understood query languages, and battle-tested reliability. However, as systems scale and use cases diversify, traditional SQL starts to exhibit problems.

That’s where NoSQL enters the picture with a flexible schema design, horizontal scalability, and models tailored to specific access patterns. The promise is to scale fast and iterate freely. However, there are trade-offs in consistency, structure, and operations.

Then there’s a growing third category: NewSQL systems such as Google Spanner and CockroachDB. These attempt to bridge the gap by retaining SQL semantics and ACID guarantees, while scaling like NoSQL across regions and nodes. There are also specialized databases that push performance in specific directions. In-memory stores like Redis blur the line between cache and persistence. Search engines like Elasticsearch offer lightning-fast text search and analytics capabilities that relational databases were never built for.

The wrong database choice can throttle performance, slow down development, or break under scale. The right one can unlock speed, agility, and reliability.

In this article, we break down the core database paradigms, such as SQL and NoSQL, along with specialized database types and how developers can choose the appropriate database for their requirements.

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by "ByteByteGo" <bytebytego@substack.com> - 11:35 - 5 Jun 2025

Russell goes LIVE in… (calling all funnel builders!)

I’ll make this quick! Russell and Kathryn are going LIVE in just a few hours!

It’s a FREE, LIVE training showing you how to step into one of the biggest online opportunities right now!

REGISTER FOR THE FREE SALES FUNNEL BUILDER TRAINING HERE >>

When: TODAY! Thursday June 5th @ 10AM PT / 1PM ET

Where: Live on Zoom

Every single day, we get flooded with people who need funnels… But don’t want to build them themselves.

And the number of certified funnel builders just can’t keep up.

WE NEED MORE!

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If you’re looking for a real skill that leads to real clients and real income… This is it!

REGISTER FOR THE FREE SALES FUNNEL BUILDER TRAINING HERE >>

See you in a few hours!

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We go LIVE in… (calling all funnel builders!)

No time to waste! We go LIVE in just a few hours!

Kathryn Jones Lish and I are hosting a FREE, LIVE training showing you how to step into one of the biggest online opportunities right now!

REGISTER FOR THE FREE SALES FUNNEL BUILDER TRAINING HERE >>

When: TODAY! Thursday June 5th @ 10AM PT / 1 PM ET

Where: Live on Zoom

Every single day, we get flooded with people who need funnels… But don’t want to build them themselves.

The demand is SKY HIGH!

And the number of professional and certified funnel builders out there? Still shockingly small!!

If you’re looking for a real skill that leads to real clients and real income… This is it!

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When: TODAY! Thursday June 5th @ 10AM PT / 1 PM ET

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See you in a few hours!

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P.S. – Don’t forget, you’re just ONE funnel away…

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by "Russell Brunson" <newsletter@marketingsecrets.com> - 11:11 - 5 Jun 2025

Problem solving: Make the most of your data

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How to make the most of your data

Welcome to "The McKinsey Publishing Guide to problem solving." In this first email, we'll dive into the importance of data and data analysis as an informative step of the problem-solving process. Read on to learn how to make the most of your data to solve even the most complex challenges.

Companies that harness the power of data have the upper hand when it comes to problem solving. Rather than defaulting to solving problems by developing lengthy—sometimes multiyear—road maps, they’re empowered to ask how innovative data techniques could resolve challenges in hours, days or weeks, write senior partner Kayvaun Rowshankish and coauthors.

But when organizations have more data than ever at their disposal, which data should they leverage? Before jumping in, it’s crucial to plan the analysis, decide which analytical tools to use, and ensure rigor. Uncover ways data can take your problem-solving techniques to the next level.

1. Be prepared for the evolution of data

Data will be embedded in every decision, interaction, and process. Today, many business problems still get solved through traditional approaches and take months or years to resolve. But by 2025, employees will be empowered to ask how innovative data techniques could resolve challenges in hours, days or weeks. Organizations will be capable of better decision making as well as automating basic day-to-day activities and regularly occurring decisions.

Read: The data-driven enterprise of 2025

2. Understand what data you have at your disposal

People think that you just have data, when actually, they’re produced. What we have and what we don’t have is constructed by the decisions that are made on what data to collect, and what data not to collect. To have a data-informed environment is incredibly important, but that requires us to make decisions about what we’re collecting, what we’re interpreting, and how we’re interpreting it.

Read: Author Talks: Think digital

3. Generative AI (gen AI) can help speed up analysis—if the right structures are in place

The lifeblood of gen AI is fluid access to data honed for a specific business context or problem. Companies that have not yet found ways to effectively harmonize and provide ready access to their data will be unable to fine-tune gen AI to unlock more of its potentially transformative uses. Equally important is to design a scalable data architecture that includes data governance and security procedures.

Read: What every CEO should know about generative AI -Test

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by "McKinsey Publishing Guides" <publishing@email.mckinsey.com> - 03:05 - 5 Jun 2025

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