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Cloud demo turns tons of work into a couple clicks
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This GROW with SAP demo moves as fast as finance changes. And in three minutes, you’ll see just how much time and effort the latest forms of finance automation can save you. Think about it:
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How can companies make the most of generative AI?
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The next big arenas of competition
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Greeting from Cara and GLA family. Trust you are doing great.
I sincerely invite you to join GLA platform and cover the increasing request from/to Saudi Arabia from our GLA members.
Above 75% of GLA Members are first-class agents with wide range of primary resources. GLA fulfills all your needs for your business development and resources integration, in terms of finding reliable agents and getting huge volume of inquiries from/to your area.
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company shall cease to be a member of GLA if:
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Is your organization productive? A leader’s guide
Leading Off
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Brought to you by Alex Panas, global leader of industries, & Axel Karlsson, global leader of functional practices and growth platforms
Welcome to the latest edition of Leading Off. We hope you find our insights useful. Let us know what you think at Alex_Panas@McKinsey.com and Axel_Karlsson@McKinsey.com.
—Alex and Axel
An individual may feel “productive” after finishing a difficult task at work. But evaluating the productivity of entire organizations is much more complex. At its simplest level, productivity measures output relative to input. But the rise of factors such as automation, generative AI (gen AI), and remote and hybrid work makes the ratio of inputs to outputs harder to calculate. With productivity levels slowing among advanced economies, amid a climate of geopolitical disruptions and environmental concerns, leaders may be facing increased urgency to boost productivity within their own organizations. This week, we examine some strategies to make the operational improvements that, taken together, could help companies become more productive.
New technologies hold out the promise of improving productivity, but they may not be effective without a commitment to operational excellence, according to McKinsey senior partner Richard Sellschop and colleagues. Our research over the past 20 years has shown that high-performing companies score highly on five essential components of operational excellence and are better able to realize value from advanced technologies. For example, one of these five elements is building a management system that reinforces innovation. Yet few organizations put this into practice by encouraging innovative behaviors, such as frequent contact with managers that enables workers to continually improve a company’s operations. In a recent survey on operational excellence, only 21 percent of employees say they have check-ins with their leaders at least once a week.
That’s the number of questions that we suggest leaders ask as they evaluate their organizations’ productivity. For example, one question concerns how to drive productivity in services. Despite advances in some subsectors, “services tend to be harder to transform and can be a drag on an economy’s productivity growth,” observe McKinsey senior partners Chris Bradley, Olivia White, and Sven Smit and their colleagues in a recent report. As manufacturing becomes more automated, reweighting economic activity toward services may be critical to growth in many countries. “Making services more productive is a more reliable and sustainable way to raise the aggregate productivity of the economy than other approaches,” note the authors.
That’s economist and Stanford University professor Erik Brynjolfsson in an episode of McKinsey’s At the Edge podcast. Speaking with McKinsey senior partner Lareina Yee, Brynjolfsson explains how gen AI can spark that rethinking—and reignite productivity. “Generative AI is, frankly, one of the biggest, most effective technologies for changing the way work is done that’s ever been invented,” he says. While the automation that may result from gen AI could alter some occupations and jobs, “we’re already seeing it complement a lot of human activity, allowing people to do their jobs more effectively than they could before,” adds Brynjolfsson. “So in most cases, it’s really not a replacement but more of an amplification.”
“At the micro level, if you’re a company, productivity is one of the best predictors of the fortunes of your business,” says University of Chicago professor and economist Chad Syverson in an episode of McKinsey’s Forward Thinking podcast. “The more productive businesses are much more likely to survive.” He adds that AI may be able to reverse the productivity slowdown in many advanced economies. Between its potential applications in a variety of situations and sectors and its ability to complement other technology investments—including intangible assets, such as managerial skills, talent, and processes—AI could be “the best candidate for a new general-purpose technology we’ve had in decades,” says Syverson. “It’s made me more optimistic that we will end the productivity growth slowdown than anything else that’s happened since I started looking deeply at the slowdown ten years ago.”
Measuring personal productivity can be a tricky business. Some workers may feel more productive by following their own “ultradian” rhythms (that is, adjusting work to periods of high and low alertness during the day), focusing on high-priority projects exclusively, or choosing the operating model—remote, hybrid, or always in-person—that works best for them and their teams. Some employees may feel obligated to fill their downtime with meaningless tasks that managers assign just to keep their teams looking busy. According to research led by McKinsey senior partner Patrick Simon and colleagues, employers could address six modifiable factors of health to improve employee well-being—and increase productivity as a result. “One of the top contributors to productivity at work is an individual’s sense of self-efficacy—an employee’s belief that they can cope with difficult or changing situations,” note the McKinsey experts. “Self-efficacy can be improved through interventions, suggesting that employers can target self-efficacy to improve employee productivity.”
Lead productively.
— Edited by Rama Ramaswami, senior editor, New York
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by "McKinsey Leading Off" <publishing@email.mckinsey.com> - 02:08 - 28 Oct 2024 -
How might using AI speed the development of life-saving cancer medicines?
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Brought to you by Alex Panas, global leader of industries, & Axel Karlsson, global leader of functional practices and growth platforms
Welcome to the latest edition of Only McKinsey Perspectives. We hope you find our insights useful. Let us know what you think at Alex_Panas@McKinsey.com and Axel_Karlsson@McKinsey.com.
—Alex and Axel
•
Accelerating drug discovery. “Cancer is fast. Developing a new cancer medicine is not,” observes McKinsey senior partner Dr. Björn Albrecht. It takes about a decade to discover a new medicine, but through the potential for AI to speed drug discovery and development, the world is at the beginning of what will be a big change, he says. One of the biggest opportunities for AI in finding medicines is in designing clinical trials, according to McKinsey partner Alex Devereson, who has worked with QuantumBlack, AI by McKinsey, on pharma projects.
•
Faster, more effective treatments. “Data is often difficult to work with,” acknowledges Alex. Analytical models must account for potential biases in the data and in the output. A successful effort, however, could help people get treated much more quickly and effectively across a wide variety of cancers. Discover the promise that AI holds to help cure disease in the Rewriting Cancer digital series—presented by UICC and produced by BBC StoryWorks—and visit the McKinsey Cancer Center to learn more.
—Edited by Belinda Yu, editor, Atlanta
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by "Only McKinsey Perspectives" <publishing@email.mckinsey.com> - 01:18 - 28 Oct 2024 -
Hi Md Abul, you tried our demo; how was your experience?
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by "Strapi" <demo@strapi.io> - 07:04 - 27 Oct 2024 -
The week in charts
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by "McKinsey Week in Charts" <publishing@email.mckinsey.com> - 03:53 - 26 Oct 2024 -
EP135: Big Data Pipeline Cheatsheet for AWS, Azure, and Google Cloud
EP135: Big Data Pipeline Cheatsheet for AWS, Azure, and Google Cloud
Forwarded this email? Subscribe here for moreThe Enterprise Ready Conference for engineering leaders (Sponsored)
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If you are a founder, exec, PM, or engineer tasked with the enterprise roadmap, this conference is for you. You’ll get detailed insights from industry leaders that have years of experience navigating the same challenges you face today. And best of all, it’s completely free since it’s hosted by WorkOS.This week’s system design interview:
Big Data Pipeline Cheatsheet for AWS, Azure, and Google Cloud
A Cheatsheet on Comparing API Architectural Styles
10 Key Data Structures We Use Every Day
A Cheatsheet to Build Secure APIs
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Big Data Pipeline Cheatsheet for AWS, Azure, and Google Cloud
Each platform offers a comprehensive suite of services that cover the entire lifecycle:
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GCP offers PubSub for data streaming, Cloud Storage for data lakes, DataProc and DataFlow for processing, BigQuery for warehousing, and Data Studio for visualization.
Over to you: What else would you add to the pipeline?A Cheatsheet on Comparing API Architectural Styles
It covers the 6 most popular API architectural styles:
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Over to you: Which other architectural style have you used?
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10 Key Data Structures We Use Every Day
list: keep your Twitter feeds
stack: support undo/redo of the word editor
queue: keep printer jobs, or send user actions in-game
hash table: cashing systems
Array: math operations
heap: task scheduling
tree: keep the HTML document, or for AI decision
suffix tree: for searching string in a document
graph: for tracking friendship, or path finding
r-tree: for finding the nearest neighbor
vertex buffer: for sending data to GPU for rendering
Over to you: Which additional data structures have we overlooked?
A Cheatsheet to Build Secure APIs
An insecure API can compromise your entire application. Follow these strategies to mitigate the risk:
Using HTTPS
Encrypts data in transit and protects against man-in-the-middle attacks.
This ensures that data hasn’t been tampered with during transmission.Rate Limiting and Throttling
Rate limiting prevents DoS attacks by limiting requests from a single IP or user.
The goal is to ensure fairness and prevent abuse.Validation of Inputs
Defends against injection attacks and unexpected data format.
Validate headers, inputs, and payloadAuthentication and Authorization
Don’t use basic auth for authentication. Instead, use a standard authentication approach like JWTs
Use a random key that is hard to guess as the JWT secret
Make token expiration short
For authorization, use OAuthUsing Role-based Access Control
RBAC simplifies access management for APIs and reduces the risk of unauthorized actions.
Granular control over user permission based on roles.Monitoring
Monitoring the APIs is the key to detecting issues and threats early.
Use tools like Kibana, Cloudwatch, Datadog, and Slack for monitoring
Don’t log sensitive data like credit card info, passwords, credentials, etc.
Over to you: What else would you do to build a secure API?
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Hi Md Abul, you tried our demo; how was your experience?
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by "Strapi" <demo@strapi.io> - 06:03 - 25 Oct 2024 -
Reinventing Rolls-Royce: A conversation with CEO Tufan Erginbilgiç
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by "McKinsey & Company" <publishing@email.mckinsey.com> - 01:47 - 25 Oct 2024 -
Malaysia Export Import Data with full details is now available with volza.com
Malaysia Export Import Data with full details is now available with volza.com
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Your Strapi evaluation
Your Strapi evaluation
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Either way, feel free to reach out if you have any questions or would like to schedule a tech call with one of our solution architects.
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by "Ray Keating" <ray.keating@strapi.io> - 06:33 - 25 Oct 2024 -
Your Strapi demo is over, what's next? 🙂
Your Strapi demo is over, what's next? 🙂
Hello Md Abul👋,
Your hosted Strapi demo is now over. Do you have any questions/feedback to share with us?
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by "Maxime Castres" <demo@strapi.io> - 06:33 - 25 Oct 2024 -
The art of 21st-century leadership, corporate venture building, arenas of competition, and more highlights
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Welcome to the latest edition of The Weekend Read. We hope you find our perspectives useful. Let us know what you think at Alex_Panas@McKinsey.com and Axel_Karlsson@McKinsey.com.
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McKinsey global managing partner Bob Sternfels, senior partners Daniel Pacthod and Kurt Strovink, and senior adviser Wyman Howard explore the art of 21st-century leadership and how organizations can build a leadership factory that shapes, develops, and mentors the next generation of managers.
6 traits Ready to unwind?
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by "McKinsey Weekend Read" <publishing@email.mckinsey.com> - 12:52 - 25 Oct 2024
