Josh Bersin人工智能实施越来越像传统IT项目Josh Bersin的文章《人工智能实施越来越像传统IT项目》提出了五个主要发现：
数据管理：强调数据质量、治理和架构在AI项目中的重要性，类似于IT项目。
安全和访问管理：突出AI实施中强大的安全措施和访问控制的重要性。
工程和监控：讨论了持续工程支持和监控的需求，类似于IT基础设施管理。
供应商管理：指出了AI项目中彻底的供应商评估和选择的重要性。
变更管理和培训：强调了有效变更管理和培训的必要性，这对AI和IT项目都至关重要。
原文如下，我们一起来看看：
As we learn more and more about corporate implementations of AI, I’m struck by how they feel more like traditional IT projects every day.
Yes, Generative AI systems have many special characteristics: they’re intelligent, we need to train them, and they have radical and transformational impact on users. And the back-end processing is expensive.
But despite the talk about advanced models and life-like behavior, these projects have traditional aspects. I’ve talked with more than a dozen large companies about their various AI strategies and I want to encourage buyers to think about the basics.
Finding 1: Corporate AI projects are all about the data.
Unlike the implementation of a new ERP system, payroll system, recruiting, or learning platform, an AI platform is completely data dependent. Regardless of the product you’re buying (an intelligent agent like Galileo™, an intelligent recruiting system like Eightfold, or an AI-enabling platform to provide sales productivity), success depends on your data strategy. If your enterprise data is a mess, the AI won’t suddenly make sense of it.
This week I read a story about Microsoft’s Copilot promoting election lies and conspiracy theories. While I can’t tell how widespread this may be, it simply points out that “you own the data quality, training, and data security” of your AI systems.
Walmart’s My Assistant AI for employees already proved itself to be 2-3x more accurate at handling employee inquiries about benefits, for example. But in order to do this the company took advantage of an amazing IT architecture that brings all employee information into a single profile, a mobile experience with years of development, and a strong architecture for global security.
One of our clients, a large defense contractor, is exploring the use of AI to revolutionize its massive knowledge management environment. While we know that Gen AI can add tremendous value here, the big question is “what data should we load” and how do we segment the data so the right people access the right information? They’re now working on that project.
During our design of Galileo we spent almost a year combing through the information we’ve amassed for 25 years to build a corpus that delivers meaningful answers. Luckily we had been focused on data management from the beginning, but if we didn’t have a solid data architecture (with consistent metadata and information types), the project would have been difficult.
So core to these projects is a data management team who understands data sources, metadata, and data integration tools. And once the new AI system is working, we have to train it, update it, and remove bias and errors on a regular basis.
Finding 2: Corporate AI projects need heavy focus on security and access management.
Let’s suppose you find a tool, platform, or application that delivers a groundbreaking solution to your employees. It could be a sales automation system, an AI-powered recruiting system, or an AI application to help call center agents handle problems.
Who gets access to what? How do you “layer” the corpus to make sure the right people see what they need? This kind of exercise is the same thing we did at IBM in the 1980s, when we implemented this complex but critically important system called RACF. I hate to promote my age, but RACF designers thought through these issues of data security and access management many years ago.
AI systems need a similar set of tools, and since the LLM has a tendency to “consolidate and aggregate” everything into the model, we may need multiple models for different users.
In the case of HR, if build a talent intelligence database using Eightfold, Seekout, or Gloat which includes job titles, skills, levels, and details about credentials and job history, and then we decide to add “salary” … oops.. well all of a sudden we have a data privacy problem.
I just finished an in-depth discussion with SAP-SuccessFactors going through the AI architecture, and what you see is a set of “mini AI apps” developed to operate in Joule (SAP’s copilot) for various use cases. SAP has spent years building workflows, access patterns, and various levels of user security. They designed the system to handle confidential data securely.
Remember also that tools like ChatGPT, which access the internet, can possibly import or leak data in a harmful way. And users may accidentally use the Gen AI tools to create unacceptable content, dangerous communications, and invoke other “jailbreak” behaviors.
In your talent intelligence strategy, how will you manage payroll data and other private information? If the LLM uses this data for analysis we have to make sure that only appropriate users can see it.
Finding 3: Corporate AI projects need focus on “prompt engineering” and system monitoring.
In a typical IT project we spend a lot of time on the user experience. We design portals, screens, mobile apps, and experiences with the help of UI designers, artists, and craftsmen. But in Gen AI systems we want the user to “tell us what they’re looking for.” How do we train or support the user in prompting the system well?
If you’ve ever tried to use a support chatbot from a company like Paypal you know how difficult this can be. I spent weeks trying to get Paypal’s bot to tell me how to shut down my account, but it never came close to giving me the right answer. (Eventually I figured it out, even though I still get invoices from a contractor who has since deceased!)
We have to think about these issues. In our case, we’ve built a “prompt library” and series of workflows to help HR professionals get the most out of Galileo to make the system easy to use. And vendors like Paradox, Visier (Vee), and SAP are building sophisticated workflows that let users ask a simple question (“what candidates are at stage 3 of the pipeline”) and get a well formatted answer.
If you ask a recruiting bot something like “who are the top candidates for this position” and plug it into the ATS, will it give you a good answer? I’m not sure, to be honest – so the vendors (or you) have to train it and build workflows to predict what users will ask.
This means we’ll be monitoring these systems, looking at interactions that don’t work, and constantly tuning them to get better.
A few years ago I interviewed the VP of Digital Transformation at DBS (Digital Bank of Singapore), one of the most sophisticated digital banks in the world. He told me they built an entire team to watch every click on the website so they could constantly move buttons, simplify interfaces, and make information easier to find. We’re going to need to do the same thing with AI, since we can’t really predict what questions people will ask.
Finding 4: Vendors will need to be vetted.
The next “traditional IT” topic is going to be the vetting of vendors. If I were a large bank or insurance company and I was looking at advanced AI systems, I would scrutinize the vendor’s reputation and experience in detail. Just because a firm like OpenAI has built a great LLM doesn’t mean that they, as a vendor, are capable of meeting your needs.
Does the vendor have the resources, expertise, and enterprise feature set you require? I recently talked with a large enterprise in the middle east who has major facilities in Saudi Arabia, Dubai, and other countries in the region. They do not and will not let user information, queries, or generated data leave their jurisdiction. Does the vendor you select have the ability to handle this requirement? Small AI vendors will struggle with these issues, leading IT to do risk assessment in a new way.
There are also consultants popping up who specialize in “bias detection” or testing of AI systems. Large companies can do this themselves, but I expect that over time there will be consulting firms who help you evaluate the accuracy and quality of these systems. If the system is trained on your data, how well have you tested it? In many cases the vendor-provided AI uses data from the outside world: what data is it using and how safe is it for your application?
Finding 5: Change management, training, and organization design are critical.
Finally, as with all technology projects, we have to think about change management and communication. What is this system designed to do? How will it impact your job? What should you do if the answers are not clear or correct? All these issues are important.
There’s a need for user training. Our experience shows that users adopt these systems quickly, but they may not understand how to ask a question or how to interpret an answer. You may need to create prompt libraries (like Galileo), or interactive conversation journeys. And then offer support so users can resolve answers which are wrong, unclear, or inconsistent.
And most importantly of all, there’s the issue of roles and org design. Suppose we offer an intelligent system to let sales people quickly find answers to product questions, pricing, and customer history. What is the new role of sales ops? Do we have staff to update and maintain the quality of the data? Should we reorganize our sales team as a result?
We’ve already discovered that Galileo really breaks down barriers within HR, for example, showing business partners or HR leaders how to handle issues that may be in another person’s domain. These are wonderful outcomes which should encourage leaders to rethink how the roles are defined.
In our company, as we use AI for our research, I see our research team operating at a higher level. People are sharing information, analyzing cross-domain information more quickly, and taking advantage of interviews and external data at high speed. They’re writing articles more quickly and can now translate material into multiple languages.
Our member support and advisory team, who often rely on analysts for expertise, are quickly becoming consultants. And as we release Galileo to clients, the level of questions and inquiries will become more sophisticated.
This process will happen in every sales organization, customer service organization, engineering team, finance, and HR team. Imagine the “new questions” people will ask.
Bottom Line: Corporate AI Systems Become IT Projects
At the end of the day the AI technology revolution will require lots of traditional IT practices. While AI applications are groundbreaking powerful, the implementation issues are more traditional than you think.
I will never forget the failed implementation of Siebel during my days at Sybase. The company was enamored with the platform, bought, and forced us to use it. Yet the company never told us why they bought it, explained how to use it, or built workflows and job roles to embed it into the company. In only a year Sybase dumped the system after the sales organization simply rejected it. Nobody wants an outcome like that with something as important as AI.
As you learn and become more enamored with the power of AI, I encourage you to think about the other tech projects you’ve worked on. It’s time to move beyond the hype and excitement and think about real-world success.
专栏
2023年12月17日
专栏
人工智能正在以比我预期更快的速度改变企业学习AI Is Transforming Corporate Learning Even Faster Than I Expected在《AI正在比我预想的更快地改变企业学习AI Is Transforming Corporate Learning Even Faster Than I Expected》这一文中，Josh Bersin强调了AI对企业学习和发展（L&D）领域的革命性影响。L&D市场价值高达3400亿美元，涵盖了从员工入职到操作程序等一系列活动。传统模型正在随着像Galileo™这样的生成性AI技术的发展而演变，这改变了内容的创建、个性化和传递方式。本文探讨了AI在L&D中的主要用例，包括内容生成、个性化学习体验、技能发展，以及用AI驱动的知识工具替代传统培训。举例包括Arist的AI内容创作、Uplimit的个性化AI辅导，以及沃尔玛实施AI进行即时培训。这种转型是深刻的，呈现了一个AI不仅增强而且重新定义L&D策略的未来。
在受人工智能影响的所有领域中，最大的变革也许发生在企业学习中。经过一年的实验，现在很明显人工智能将彻底改变这个领域。
让我们讨论一下 L&D 到底是什么。企业培训无处不在，这就是为什么它是一个价值 3400 亿美元的市场。工作中发生的一切（从入职到填写费用账户再到复杂的操作程序）在某种程度上都需要培训。即使在经济衰退期间，企业在 L&D 上的支出仍稳定在人均 1200-1500 美元。
然而，正如研发专业人士所知，这个问题非常复杂。有数百种培训平台、工具、内容库和方法。我估计 L&D 技术空间的规模超过 140 亿美元，这甚至不包括搜索引擎、知识管理工具以及 Zoom、Teams 和 Webex 等平台等系统。多年来，我们经历了许多演变：电子学习、混合学习、微型学习，以及现在的工作流程中的学习。
生成式人工智能即将永远改变这一切。
考虑一下我们面临的问题。企业培训并不是真正的教学，而是创造一个学习的环境。传统的教学设计以教师为主导，以过程为中心，但在工作中常常表现不佳。人们通过多种方式学习，通常没有老师，他们寻找参考资料，复制别人正在做的事情，并依靠经理、同事和专家的帮助。因此，必须扩展传统的教学设计模型，以帮助人们学习他们需要的东西。
输入生成人工智能，这是一种旨在合成信息的技术。像Galileo™这样的生成式人工智能工具 可以以传统教学设计师无法做到的方式理解、整合、重组和传递来自大型语料库的信息。这种人工智能驱动的学习方法不仅效率更高，而且效果更好，能够在工作流程中进行学习。
早期，在工作流程中学习意味着搜索信息并希望找到相关的东西。这个过程非常耗时，而且常常没有结果。生成式人工智能通过其神经网络的魔力，现在已经准备好解决这些问题，就像 L&D 的瑞士军刀一样。
这是一个简单的例子。我问Galileo™（该公司经过 25 年的研究和案例研究提供支持）：“我该如何应对总是迟到的员工？请给我一个叙述来帮助我？” 它没有带我去参加管理课程或给我看一堆视频，而是简单地回答了问题。这种类型的互动是企业学习的大部分内容。
让我总结一下人工智能在学习与发展中的四个主要用例：
生成内容：人工智能可以大大减少内容创建所涉及的时间和复杂性。例如，移动学习工具Arist拥有AI生成功能Sidekick，可以将综合的操作信息转化为一系列的教学活动。这个过程可能需要几周甚至几个月的时间，现在可以在几天甚至几小时内完成。
我们在Josh Bersin 学院使用 Arist ，我们的新移动课程现在几乎每月都会推出。Sana、Docebo Shape和以用户为中心的学习平台 360 Learning 等其他工具也同样令人兴奋。
个性化学习者体验：人工智能可以帮助根据个人需求定制学习路径，改进根据工作角色分配学习路径的传统模型。人工智能可以理解内容的细节，并使用该信息来个性化学习体验。这种方法比杂乱的学习体验平台（LXP）有效得多，因为LXP通常无法真正理解内容的细节。
Uplimit是一家致力于构建人工智能平台来帮助教授人工智能的初创公司，它正在使用其Cobot和其他工具为学习人工智能的技术专业人员提供个性化的指导和技巧。Cornerstone 的新 AI 结构按技能推荐课程，Sana 平台将 Galileo 等工具与学习连接起来，SuccessFactors 中的新 AI 功能还为用户提供了基于角色和活动的精选学习视图。
识别和发展技能：人工智能可以帮助识别内容中的技能并推断个人的技能。这有助于提供正确的培训并确定其有效性。虽然许多公司正在研究高级技能分类策略，但真正的价值在于可以通过人工智能识别和开发的细粒度、特定领域的技能。
人才情报领域的先驱者Eightfold、Gloat和SeekOut可以推断员工技能并立即推荐学习解决方案。实际上，我们正在使用这项技术来推出我们的人力资源职业导航器，该导航器将于明年初推出。
用知识工具取代培训：人工智能在学习与发展中最具颠覆性的用例也许是完全取代某些类型培训的潜力。人工智能可以创建提供信息和解决问题的智能代理或聊天机器人，从而可能消除对某些类型培训的需求。这种方法不仅效率更高，而且效果更好，因为它可以在个人需要时为他们提供所需的信息。
沃尔玛今天正在实施这一举措，我们的新平台 Galileo 正在帮助万事达卡和劳斯莱斯等公司在无需培训的情况下按需查找人力资源信息和政策信息。LinkedIn Learning 正在向 Gen AI 搜索开放其软技能内容，很快 Microsoft Copilot 将通过 Viva Learning 找到培训。
这里潜力巨大
在我作为分析师的这些年里，我从未见过一种技术具有如此大的潜力。人工智能将彻底改变 L&D 格局，重塑我们的工作方式，以便 L&D 专业人员可以花时间为企业提供咨询。
L&D 专业人员应该做什么？花一些时间来了解这项技术，或者参加Josh Bersin 学院的一些新的人工智能课程以了解更多信息。
随着我们继续推出像伽利略这样的工具，我知道你们每个人都会对未来的机会感到惊讶。L&D 的未来已经到来，而这一切都由人工智能驱动。
专栏
2023年12月13日
专栏
Josh Bersin：Introducing Galileo™, The World’s First AI-Powered Expert Assistant For HRAs many of you know, HR professionals play a vital, complex, and constantly changing role in business. These 30 million professionals hold more than 250 job roles and leverage over 400 skills to help companies with all aspects of management: recruiting, development, leadership, coaching, diversity, pay, benefits, hybrid work, and more. And they must also select and implement a wide array of technologies and tools to help their companies grow.
The Josh Bersin Company, through 25 years of research and interviews with thousands of companies and vendors, has amassed the most trusted library of best-practices, vendor information, benchmarks, case studies, and professional development tools for HR.
Last Spring we embarked on a project to build an “HR Copilot”, consolidating our content into a Generative AI platform. The results were amazing: using Gen AI we were able to build an amazing new experience: users can ask questions, compare vendors, dig into solutions, and generate implementation plans, RFP templates, and more.
Today, in our ongoing effort to help HR professionals drive value for their companies, we’re ready to launch this offering. I’m excited to introduce Galileo™, the world’s first AI-powered expert assistant for HR. (Join the waitlist.)
Every HR Question Answered
Just as Galileo mapped the heavens to explain the universe, our Galileo™ gives HR teams the ability to understand, learn, and seek out best-practices in every area of HR. Powered by Sana’s AI platform, Galileo™ gives users complete access to all of The Josh Bersin Company’s comprehensive research, articles, and tools. And unlike internet-based AI tools, Galileo is free of promotional material, giving you trusted, detailed, verifiable accurate information.
We designed Galileo™ to be the HR professional’s ‘always-on’ resource to learn, ask questions, and develop solutions.
Galileo™ can answer questions on hundreds of topics, provide detailed information on vendors and HR technology, draft RFPs and implementation plans, and give users guidance, case studies, and benchmarks. All of the Josh Bersin Company research is instantly available, with access to in-depth reports, podcasts, articles, and courses. This includes access to our maturity models, frameworks, case studies, and our new definition of terms, The Josh Bersin Company Lexicon™.
Galileo™ will revolutionize the way HR Professionals do their jobs. No longer will you have to guess how to develop a new program or understand a vendor – accurate information is available at your fingertips.
Galileo Is A Learning, Design, And Problem Solving Assistant
Many HR problems are complex. To make problem-solving easy, Galileo includes a library of more than 50 pre-defined “prompts” which help professionals with topics like hiring, onboarding, performance management, training, and multi-disciplinary topics like building a skills taxonomy, implementing pay equity, workforce planning, or designing a capability academy.
We designed these prompts in chains, so as you ask a question, Galileo will take you down a path to learn, explore, and further assist you in your query. (The Galileo Getting Started Guide shows you some of the solutions available.)
Enterprise Ready: Galileo Is Your Company’s Expert Assistant
And there’s more. As you use Galileo, you will want to put your own HR policies and internal information into the system. Thanks to the architecture of Sana, Galileo lets users and teams add your information to the corpus, turning Galileo into your company’s in-house HR and employee assistant. In this private workspace your data and privacy are protected: Galileo is an enterprise grade, secure platform that isolates your data from others, pre-trained by The Josh Bersin Company research.
And our partnership with Sana goes further. Not only does the Sana platform provide scale and speed, it lets us build multiple AI assistants. If you want an expert assistant tailored to specific HR disciplines, like Talent Acquisition, L&D, DEI, or line managers, we can create them without writing code.
“This is just the beginning,” said Josh Bersin, CEO and Founder of The Josh Bersin Company. “This paradigm-shattering offering will change the way companies run their HR organizations and manage their people, enabling any professional to operate like a world-class expert in a short period of time. Galileo is a supportive, developmental assistant, ready to give users detailed answers, real-world examples, and guidance at any time.”
Initially Galileo will be available to our corporate members and later next year we will roll out a version available to members of The Josh Bersin Academy.
We want to thank Sana for their partnership and look forward to evolving Galileo rapidly in the coming months. Anyone interested in experiencing Galileo can sign up for the wait list. We expect general availability in early 2024.
Questions:
What Topics Are Covered by Galileo?
Galileo stores more than 50,000 pages of Josh Bersin Company research, including podcasts, articles, and comprehensive data and analysis on a wide variety of topics. These include talent acquisition, talent management, corporate training, diversity and inclusion, organization design, rewards and recognition, pay and pay equity, performance management, leadership development, global HR operations, hybrid work, culture, change management, and every major area of HR technology.
More than 500 vendors are covered by Galileo and the database is growing and updated every week. Over time Galileo will also include real-time information on new vendor offerings, the labor market, skills and capabilities, and important regulatory changes in HR.
To get just a glimpse of what Galileo can do, review the “Galileo Getting Started Guide.”
Is Galileo Generative AI?
Yes, Galileo is an advanced Generative AI solution that lets users ask questions and prompt the system to compare vendors, list best practices, and even create implementation plans, historical perspectives, and in-depth analysis. This means an HR professional can ask any simple question and Galileo will not only answer the question but give the user follow-on prompts to help them learn more, find examples, or download detailed reports, articles, podcasts, or tools.
What Is The Research and Information Provided?
Over the last three decades The Josh Bersin Company has studied nearly every domain of HR, developing in-depth maturity models, frameworks, benchmarks, and case studies. We have also added all of Josh’s blogs, podcasts, and videos – and we will be adding much more. While Galileo does not include legal and regulatory guidelines (these can be discovered in local jurisdictional systems), it covers every major domain of HR, empowering any HR leader or professional to quickly learn, find examples, and solve a problem.
How Do We Know Galileo Information Is Accurate?
Unlike public domain tools, Galileo is trained exclusively on The Josh Bersin Company’s large corpus of information and research. This means it does not suffer from the “AI drift” problem experienced by internet-sourced systems. In fact the opposite is true: as users query and use the system, it enables them to rate the generated answers and get smarter over time.
How Do I Know That Galileo Is Secure?
Galileo does not train any underlying language models on user input, thereby eliminating the risk of data leakage. Sana, which powers Galileo, is single tenant, ISO 27001 certified, and GDPR compliant. All data is encrypted at rest with AES 256 and in transit with TLS 1.2+. The platform follows data privacy regulations and guidelines to protect each individual user.
Can I Use Galileo To Create My Own HR Assistant?
Yes, Galileo is built on the highly configurable Sana platform, enabling users and teams to add their own content and create new AI assistants. We will offer these private workspace features to corporate clients and then roll them out to individual JBA members later in 2024.
How does Galileo Differ From Other AI Tools?
Many companies are experimenting with Generative AI through public internet tools. Galileo differs from these existing AI tools for the following reasons:
Enterprise Scale, Scope, and Security. Galileo is built on an enterprise scale AI platform capable of loading massive volumes of your own company information. This means you can build on the Josh Bersin Company corpus to safely add your own processes, training, compliance documents, and support material for HR professionals and other users throughout your company.
Depth of expertise. The answers and support you receive from Galileo are based on an extensive library from The Josh Bersin Company, one of the world’s leading advisory companies for corporate learning, talent management, and HR. The Josh Bersin Company has customized Galileo to answer and behave as if it were an expert consultant from their organization.
Source attribution. While other AI chat tools don’t consistently back up their answers, Galileo attributes sources to each answer with specific references and further learning content from The Josh Bersin Company library. And for corporate members, you can download and read the detailed sources.
Privacy. While other assistants may get trained on your data and usage, risking data leakage, Galileo lets you upload your own content without training any underlying large language models on your data.
Workflow support. Beyond answering questions and brainstorming ideas, Galileo helps you solve day-to-day tasks like drafting implementation plans because it can generate content based on both expert HR resources and your organization’s information.
How Does Galileo Get Smarter Over Time?
As we say, Galileo is smart and always getting smarter. It does this through many features.
First, Galileo integrates, tags, transcribes, and indexes all of The Josh Bersin Company’s content on an ongoing basis, making sure the system is always trained on the latest research, findings, and vendor information. Every day we add new information.
Second, answers to questions are generated with retrieval-augmented generation (RAG), identifying the semantically relevant videos, audio, and texts, ranking the sources, and attributing the generated answers to the underlying references. We monitor questions and continuously improve results to provide detail and actionable answers.
Third, we take advantage of user-generated feedback. When users upvote or downvote answers the system learns to provide more accurate answers. The Bersin team works with Sana to improve the detailed answers in commonly asked questions. During the 9-month pilot we already optimized hundreds of questions.
Finally, we have developed “prompt chains” of more than 100 known use-cases in HR and management. Galileo literally prompts you to dive into a problem to learn more, explore vendors, read case studies, and learn best-practices. We will accelerate these solutions over time.
The Josh Bersin Company uses Sana AI’s assistant builder to tailor Galileo’s instructions, specifically adapted to various HR roles and tuned with hundreds of archetypical HR scenarios.
Who Is Sana and What is Sana AI?
Sana is an AI company transforming how organizations learn and access knowledge. Their end-to-end learning platform is trusted by hundreds and thousands of users at leading enterprises like Kry/Livi, Merck, and Svea Solar. Backed by top-tier investors, operators, and founders, they have raised over $80m to date. The company’s headquarters are in Stockholm, Sweden, with offices in London and New York. Galileo is powered by Sana AI, the company’s newest product.
To learn more about Sana, go to https://www.sanalabs.com/galileo.
How Is Galileo Sold and Offered?
Initially Galileo is being offered to Josh Bersin Company Corporate Members, enabling these organizations to empower and support their HR teams in an exciting new way. These individuals can access all the information, download all materials, take courses, and share the tools and information with their teams.
In the coming months there will be a version of Galileo for members of The Josh Bersin Academy. We encourage anyone interested to register on our waitlist so that we can provide updates on availability.
How Do I Get Access To Galileo Now?
Please join our wait list, we are now rolling out Galileo to corporate members and look forward to supporting you.
David Green:The best HR & People Analytics articles of October 2023
HR is the CEO’s right-hand in enlightened organisations.
Those were the words of Barbara Lavernos, Deputy CEO at L’Oreal, while speaking as part of a panel of CEOs on the main stage at the recent UNLEASH World in Paris. The declaration captures one of my key takeaways from the show: HR has made significant progress in its journey from support function to strategic partner.
One of the key drivers enabling this journey is people analytics. Two of the findings in the 4th Annual Insight222 People Analytics Trends study, are: (1) 21% of people analytics leaders now report directly to the chief people officer (compared to 13% in 2020). (2) People analytics teams have grown by 43% since 2020. As Isabel Naidoo, chief people officer at Wise, said recently at the Insight222 Global Executive Retreat in Colorado:
People analytics is the fastest route to credibility as a chief people officer.
FIG 1
One of my highlights from October was hosting the Main Stage at the aforementioned UNLEASH World show in Paris. I've shared my key learnings from UNLEASH in a LinkedIn post, but would like to highlight what makes UNLEASH unique: a vibrant mix of content, learning, community, and innovation topped off with fabulous production. A huge thank you to Marc Coleman, Paige Richmond, Amelia Donovan, Zoltán Kőváry and Nidal Elfadil – it was a joy to work with you all again. See more on Day 1 and Day 2 at UNLEASH World.
UNLEASH World 2023
What’s in store for November?
The next few weeks are set to be busy. I’m currently in Chicago ahead of a Peer Meeting for North American members of the Insight222 People Analytics Program, hosted by Berube, Derek and his team at McDonalds. In mid-November, I’ll be speaking on the key findings of the Insight222 2023 People Analytics Trends at Workday Rising EMEA. On November 21 and 22, I’ll be in Copenhagen for another Insight222 Peer Meeting, this time for European members of the People Analytics Program. Finally, on November 30, I’ll be in Bangalore to speak at Indeed FutureWorks. If any of you are going to these events, I look forward to seeing you there.
Looking for a new role in people analytics or HR tech?
I’d like keep highlighting the wonderful resource created by Richard Rosenow and the One Model team of open roles in people analytics and HR technology, which now numbers over 450 roles, as well as now also including roles for interns.
Participate in a study on the Modern Work Experience
RedThread Research is collecting data to understand the Modern Work Experience and how it has changed over the last year. This study is for individuals employed full-time at organizations with more than 100 people and will remain open until Monday, November 13, 2023. As a thank you for every response collected, RedThread will:
Donate $10 to DonorsChoose to support students and classrooms
Provide respondents with a free copy of the final report, “2023 Performance Management Trends: The Rise of Employee Expectations”
Share a free copy of the new report summary once published
Take the survey!
Share the love!
Enjoy reading the collection of resources for October and, if you do, please share some data driven HR love with your colleagues and networks. Thanks to the many of you who liked, shared and/or commented on September’s compendium including those highlighted in the comments below.
If you enjoy a weekly dose of curated learning (and the Digital HR Leaders podcast), the Insight222 newsletter: Digital HR Leaders newsletter is published every Tuesday – subscribe here.
GENERATIVE AI AND THE FUTURE OF WORK AND HR
DIANE GHERSON – The New Deal of Work | DAVID ROCK – Irreconcilable Differences | JOSH BERSIN - The Pixelated Workforce Has Arrived ... Are We Ready? | RJ MILNOR – Fractional Work and Your Talent Strategy | JUDITH WIESE – Growth Talks
I can’t recommend the Fall edition of SHRM’s People + Strategy on Rethinking Work and the Workplace highly enough. The guest editor is Diane Gherson, one of the deepest and most original thinkers about the future role of HR. As Diane articulates in her editor’s preface: “New work models, new business requirements and new employee expectations are coming together at full speed, putting at risk our status quo arrangements in the organization—and even the role and scope of HR.” These themes flow through all of the articles in the edition – all of which I happily recommend, they include. (1) David Rock highlights what neuroscience can teach us about the tug of war between employers and employees particularly with regards to the return to office debate. (2) Josh Bersin examines the implications for organisations of the “blowing up” of the traditional model for full-time long-term employees (FIG 2). (3) RJ Milnor highlights four questions for CHROs about the growth of fractional work and its impact on talent strategy. (4) Judith Wiese explains how Siemens replaced performance reviews with a new concept built on dialogues focused on growth.
New work models, new business requirements and new employee expectations are coming together at full speed, putting at risk our status quo arrangements in the organization—and even the role and scope of HR
FIG 2
FRANÇOIS CANDELON, LISA KRAYER, SARAN RAJENDRAN, AND DAVID ZULUAGA MARTÍNEZ - How People Can Create—and Destroy—Value with Generative AI
Together with a group of scholars from Harvard, MIT, Wharton, and the University of Warwick, BCG conducted an experiment on 750 of its own consultants around the globe to test the use of generative AI (GAI). The results, as documented in the article by François Candelon, Lisa Krayer, Saran Rajendran, and David Zuluaga Martínezfind that people mistrust GAI in areas where it can contribute tremendous value and trust it too much where the technology isn’t competent. For example, 90% of participants improved their performance when using GenAI for creative ideation. However, on the flip side, when the consultants participating in the study where focused on business problem solving, a task outside the tool’s current competence, many participants took GPT-4's misleading output at face value. Their performance was 23% worse than those who didn’t use the tool at all. The article also examines some key guidance on related topics including data strategy, roles and workflows, strategic workforce planning and experimentation.
FIG 3
FIG 4
OTHER RESOURCES ON GENERATIVE AI AND THE WORLD OF WORK
LYNDA GRATTON - Want More Clarity on Generative AI? Experiment Widely | LIZ GRENNAN, ANDREAS KREMER, ALEX SINGLA, AND PETER ZIPPARO - Why businesses need explainable AI—and how to deliver it | DONNA SCAROLA - What Most People Get Wrong about AI & Bias | FANGFANG ZHANG AND SHARON K. PARKER - How ChatGPT Can and Can’t Help Managers Design Better Job Roles | KEVIN OAKES - Is HR Already Behind in the AI Revolution?
Many of the topics discussed at Unleash World were related to the remarkable acceleration of AI tools and technologies, and their impact on work, organisations and workers. I recommend digging into these five resources: (1) Lynda Gratton shares insights from a webinar she recently ran with 260 global executives, which highlighted that: “Figuring out the right approaches to generative AI is a process replete with ambiguity, experiments, and changes of mind.” Lynda also provides details on what companies are already using generative AI for in HR with the top two areas being internal knowledge management and recruitment. (2) Writing for McKinsey, Liz Grennan, Andreas Kremer, Alex Singla, and Peter Zipparo break down explainable AI (see FIG 5), and why it is important Including to enhance productivity, build trust and deliver value. (3) Donna Scarola provides a helpful primer providing guidance on how to prevent bias – including the creation of an ethics committee. (4) Fangfang Zhang and Sharon Parker unveil their research, pros and cons, and guidance for using ChatGPT for work design and job roles (see FIG 6). (5) Finally, Kevin Oakes summarises the key findings from i4CP’s recent study: Is HR Already Behind in the AI Revolution? Thanks Erik Samdahl for the heads up.
People use what they understand and trust. This is especially true of AI
FIG 5
FIG 6
THE EVOLUTION OF HR AND DATA DRIVEN CULTURE
DAVE ULRICH AND NORM SMALLWOOD - Six Actions for HR to Create More Stakeholder Value
How can HR create more value for all stakeholders? This is the exam question Dave Ulrich and Norm Smallwood seek to answer in their article. The article highlights six specific actions and questions that enable organisations to create more value from HR (see FIG 7). The six actions are: (1) Articulate a point-of-view. (2) Define, seek, and track outcomes more than activities. (3) Prioritise what matters most. (4) Apply innovative and relevant methodology. (5) Translate to stakeholder value. (6) Scale, leverage and improve work.
FIG 7:
ROB BRINER - Aligning HR with the business through the evidence-based HR process
Rob Briner makes the case for evidence-based practice and how it applies to HR, explaining what it is and why it is effective. Rob breaks down six key steps in the evidence-based HR process (see FIG 8). He then applies the evidence-based approach to a case study to understand and solve high employee turnover.
FIG 8
PEOPLE ANALYTICS
NAOMI VERGHESE - The Growing Influence of People Analytics in Strategic Business Decisions
In a taster from the Insight222 People Analytics Trends report, Naomi Verghese digs into one of the key findings from the study: developing relationships with C-suite and senior stakeholders. The article focuses on four key elements of influence. (1) What ‘influence’ means in the context of people analytics. (2) Data on how people analytics as a field has grown in influence (including FIG 9, which highlights the growing number of people analytics leaders reporting directly to the CHRO). (3) How a people analytics leader can gain access to senior business stakeholders. (4) Why it is important that a people analytics leader has executive-level influence in organisations today.
FIG 9
THOMAS RASMUSSEN, MIKE ULRICH, AND DAVE ULRICH - Moving People Analytics From Insight to Impact
While I wouldn’t normally include a resource that isn’t open access in this compendium, I’m making an exception for this must-read paper by Thomas Hedegaard Rasmussen, Mike Ulrich and Dave Ulrich, which can be accessed for a fee of a very worthwhile £29.00. The abstract to the paper (see below), which can be considered a follow up to the seminal paper, authored by Thomas and Dave, which was published in 2015: How HR analytics avoids being a management fad, provides a compelling narrative.
KEVIN METHERELL - Intentionality Matters - a GER2023 review | JAY DORIO - How to Get Remote and Hybrid Working Right | HEIDI BINDER-MATSUO - From People Analytics to Chief People Officer: How to Effectively Influence the C-suite JASDEEP KAREER - Why is Adaptive Teaming and Intentional Collaboration Important in a New World of Work?
Perhaps the highlight so far of my year was the recent Insight222 Global Executive Retreat in Colorado. It has already inspired several articles, which are collected here. (1) Kevin Metherell, one of the people analytics leaders present, summarises his takeaways from the three days with the linking thread being the “need for intentionality in everything we do” (2) Jay Dorio explores ways to get remote and hybrid working right through intentionally co-ordinating in-person days, encouraging collaboration by scheduling in-person meetings, and setting the standard that attendance on anchor days is mandatory. (3) Heidi Binder-Matsuo provides insights on what CEOs and CHROs are looking for from their people analytics leaders. (4) Jasdeep Kareer, PhD (née Bhambra) breaks down the role of collaboration modes (see FIG 10) and provides ten steps people analytics professionals can take to gain a deeper understanding of collaboration within their organisations.
FIG 10
LYDIA WU - Seven Lessons I Learned About People Analytics | ADAM TOMBOR – People Analytics Hands-On | ANKIT SAXENA - How does a Global Head of People Insights create a people analytics roadmap? | JACKSON ROATCH - The Lindy Effect in People Analytics | JENNA EAGLESON - R Toolkit for People Analytics: Telling Your Headcount Story JAEJIN LEE - What Career and Academic Backgrounds Do People Analytics Leaders Possess? (Analysis of 279 Global People Analytics Leaders)
October has seen a number of people analytics leaders publishing articles, which is always to be encouraged as insights from practitioners really help the field advance. Six leaders are featured here. (1) As part of her excellent 'Oops, did I think that out loud' series of articles, Lydia Wu documents seven lessons she has learned from working in the people analytics field – my favourite is: “Stakeholders are more important than numbers”. (2) Adam Tombor (Wojciechowski), Global Head of People Analytics at Julius Baer, shares how the three key ingredients of the right technology, the right process and the right skills have helped reshape people analytics at Julius Baer. (3) Ankit Saxena, MBA shares his methodology for developing a progressive people analytics roadmap. (4) Jackson Roatch breaks down The Lindy Effect by using a powerful example using turnover (look at FIG 11 – and decide which worker has the highest turnover risk before reading Jackson’s article). (5) Jenna Eagleson provides a step-by-step tutorial on how to tackle a common people analytics challenge: telling the story of company headcount entirely in R. (6) Jaejin Lee analyses the career and academic backgrounds of 279 people analytics leaders.
FIG 11
MAX BLUMBERG - What to Avoid When Choosing a People Analytics Operating Model
A short but instructive article by Max Blumberg (JA) ?? on the key areas to consider when evaluating whether to implement a people analytics model including trust, investment and the extent of change management required.
Regulations continue to evolve - models that appear compliant today may not be tomorrow.
EMPLOYEE LISTENING, EMPLOYEE EXPERIENCE, AND EMPLOYEE WELLBEING
STEPHANIE DENINO, ANDRÉ FORTANGE, TIMO TISCHER, AND MARIS GARCIA - The APEX model: How organizations can systemically improve employee experience Website | Summary Report
I always learn from TI PEOPLE’s research and analysis on employee experience ever since the company was formed by Volker Jacobs in 2016. In their new study, the team of Stephanie Denino, André Fortange, Timo Tischer and Maris García, present the APEX (Activities driving the Practice of EX) model, which is comprised of 3 focus areas, 6 goals and 28 activities (see FIG 12) which uncovers what it takes to improve EX in ways that are sustainable and replicable. This model, based on research with dozens of global EX leaders and vast client experience, highlights two important threads that run through the model: being data-driven and human-centered. The report also covers big questions like “Is an EX leader essential?” and explains that guided by this model, EX leaders can bring about an EX-centric operating system in their organisations.
FIG 12
BASTIAAN STARINK AND JAN WILLEM VELTHUIJSEN - What every HR leader needs to show the CFO | The benefits of investing in People Where should companies invest to improve the employee experience?
I was drawn to this study, authored by Bastiaan Starink and Jan Willem Velthuijsen for PwC, by one of the key findings: Making investments in 11 key areas of employee experience can yield savings equivalent to 12.6% of revenues (see FIG 13) encompassing reducing absenteeism, reducing employee turnover and boosting productivity. Two additional findings are: (1) Out of the eleven employee experience drivers analysed in the study, well-being, developmental opportunities, and training lead to the best outcomes in terms of benefits. (2) Companies will always have to analyse their own employee experience - effective interventions can only be made on that basis.
FIG 13:
WORKFORCE PLANNING, ORG DESIGN, AND SKILLS-BASED ORGANISATIONS
KATHI ENDERES - Building the Dynamic Organization: Critical for the Post-Industrial Era | ANN ANN LOW - Unlocking Talent Agility to Future-Proof Organizations
Kathi Enderes breaks down the recent research she and Josh Bersin have conducted with Gloat. It highlights that instead of designing a company around jobs, Dynamic Organizations instead organise around people and skills. Kathi’s article provides a framework (see FIG 14), a maturity model, and data on the impact of Dynamic Organizations. Agility is also a key feature of Ann Ann Low’s article, which summarises the recent talk by Amy Schultz of Canva at LinkedIn Talent Connect including their 5Bs Framework (see FIG 15).
FIG 14
FIG 15
LEADERSHIP AND CULTURE
JONATHAN KNOWLES, B. TOM HUNSAKER, AND MELANIE HUGHES – The Role of Culture in Enabling Change
While culture is often described as “how we do things around here”, Jonathan Knowles, Dr. Tom Hunsaker, and Melanie Hughes argue in their article that “It’s more helpful to think of culture as the nervous system of an organization.” They highlight that one of the most important responsibilities of HR is to analyse the aspects of culture that are enabling or hindering performance. They proceed to explain that the first step is to investigate the type of change the team, business unit or organisation requires, and then document three approaches to making such changes: (1) Reinforce magnitude. (2) Reimagine activity. (3) Rethink direction (see also FIG 16)
FIG 16
FRANCES X. FREI AND ANNE MORRISS - Storytelling That Drives Bold Change
“Research has shown that storytelling has a remarkable ability to connect people and inspire them to take action,” write Frances Frei and Anne Morriss, in the cover article of the current issue of Harvard Business Review. In the article, which is a taster from their new book, Move Fast and Fix Things, the duo outline an effective way to leverage the power of storytelling, through four key steps: (1) Understand your story so well that you can describe it in simple terms, (2) honour the past, (3) articulate a persuasive mandate for change, and (4) lay out a rigorous and optimistic path forward. Then they explain how emotions can bring your story to life and help drive stakeholder commitment to change, and highlight ten underrated emotions in change narratives (see FIG 17).
FIG 17
EMILY FIELD, BRYAN HANCOCK, MARC METAKIS, AND DONNIE STUART - Activating middle managers through capability building
As one of the best books I’ve read this year – Power to the Middle (by Bill Schaninger, Ph.D., Bryan Hancock and Emily Field) - outlines middle managers who are equipped with the skills and support they need to succeed can reduce friction, accelerate action, and ensure that an organisation achieves its vision. This article, by Emily and Bryan together with Marc Metakis and Donnie Stuart, provides examples of companies that have built the capabilities of their middle managers (including a global not-for-profit who broke the problem-solving process into seven actions and four distinct phases for their middle managers – see FIG 18), common hurdles to doing this successfully, and how these obstacles can be overcome.
Middle managers can accelerate the execution of a company’s strategy by translating ideas between layers of hierarchy and solving problems with data.
FIG 18:
MICHAEL ARENA - The Ripple Effect: Understanding organizational behavior contagion to cultivate culture at scale
Michael Arena summarises the findings of a study he undertook to investigate the impact of behaviour contagion (the notion that behaviours are akin to contagious viruses within social networks) on organisational culture. The study was based on a comprehensive360-degree review to assess individual behavioural strengths combined with organisational network analysis techniques. The results confirmed that all cultural attributes were contagious to some extent and transmitted among direct employee connections. Moreover, the contagion effect extends up to three degrees of separation in professional networks – ‘The Ripple Effect’. Michael also examines the implications for companies, and how they can harness The Ripple Effect to build a positive workplace culture including identifying key influencers and nurturing strong connections. FIG 19 provides an example of how ‘strong judgement’ spreads across the network.
FIG 19
DIVERSITY, EQUITY, INCLUSION, AND BELONGING
EMILY FIELD, ALEXIS KRIVKOVICH, SANDRA KÜGELE, NICOLE ROBINSON AND LAREINA YEE - Women in the Workplace 2023
The ninth edition of the annual Women in the Workplace report from McKinsey and LeanIn.Org is based on analysis from 276 participating companies employing ten million people between them, and a survey of 27,000 employees and 270 senior HR leaders. It finds that while there have been gains at the top, with women’s representation in the C-suite at the highest it has ever been, progress in the middle of the pipeline is lagging—and with a persistent underrepresentation of women of colour—true parity remains painfully out of reach. The article by Emily Field, Alexis Krivkovich, Sandra Kuegele, Nicole Hardy Robinson and Lareina Yee, focuses on four myths about women at work that the study debunks. (1) Myth: Women are becoming less ambitious. Reality: Women are more ambitious than before the pandemic—and flexibility is fuelling that ambition. (2) Myth: The biggest barrier to women’s advancement is the “glass ceiling.” Reality: The “broken rung” is the greatest obstacle women face on the path to senior leadership (see FIG 20). (3) Myth: Microaggressions have a ‘micro’ impact. Reality: Microaggressions have a large and lasting impact on women. (4): Myth: It’s mostly women who want—and benefit from—flexible work. Reality: Men and women see flexibility as a ‘top 3’ employee benefit and critical to their company’s success.
FIG 20
HR TECH VOICES
Much of the innovation in the field continues to be driven by the vendor community, and I’ve picked out a few resources from October that I recommend readers delve into:
VISIER - Top 50 HR Leaders to Watch in 2024 – This is clever marketing from Jake Sorofman and the team at Visier Inc. as they highlight 50 HR (mostly people analytics) leaders to watch in 2024, including many who are customers. It’s certainly good to see the likes of Adam McKinnon, PhD., Angela LE MATHON, Dawn Klinghoffer, Doug Shagam, Erik Otteson, Jaclyn Lee PhD and IHRP-MP, Jeremy Shapiro, Kai Wehmeyer, Kanella Salapatas, Julien Legret, Kevin Moore SWP, Lydia Wu, Lydia Low, Kunal Thakkar, MS, PMP, Mark Berry, Matthew Hamilton, Mei Kim, Michael Salva, Nicholas Garbis, Pam Malone, Peter Meyler, Ramesh Karpagavinayagam, Richmond Tan, Sally Smith, Scott Judd, Shakti Jauhar, Shannon Vallina, and Steven Piperno getting some deserved recognition.
ANDREW PITTS - Mapping the Unleash World Exhibitors Network Using LinkedIn Data – Andrew Pitts continues Polinode’s excellent series by using ONA to map the network of the 175 exhibitors at the recent Unleash World show in Paris, which delivers some fascinating insights, not least the influence of The HR Lab.
ANNA AIROLDI - Is the Workplace Undergoing a Mental Health Revolution? – The latest gem from the Workforce Insights newsletter from Revelio Labs sees Anna A. providing analysis to highlight that companies are increasingly offering mental health and wellbeing benefits (see FIG 21). Thanks to Ben Zweig for highlighting.
FIG 21:
PHIL ARKCOLL - The Importance of Passive Listening – An excellent piece by Philip Arkcoll of Worklytics extolling the virtues of combining active listening (via surveys) with passive listening tools that allow forward-thinking organisations utilising both to understand the real-time behavioural drivers of employee attitudes.
FIG 22
FRANCISCO MARIN - Unlocking the Potential of Organizational Network Analysis (ONA) for Hybrid Work Adoption – Francisco Marin of Cognitive Talent Solutions breaks down how ONA can be used to gain insights on hybrid work adoption including by identifying informal communication networks, optimising office space, and assessing collaboration patterns.
FIG 23
MARC RAMOS - Transitioning your learning team to generative AI: Become the exemplar for your enterprise - Marc Steven Ramos of Cornerstone OnDemand writes on how Learning and Development teams are in prime position to be both pioneers in generative AI adoption and to lead by example, helping to conceptualise and implement the holistic generative AI strategy of the organisation.
COLE NAPPER, LUKA BABIC, AND STEFAN VUCICEVIC - People Analytics Operating Model in the Age of AI – In this paper, the Orgnostic team of Cole Napper, Luka Babic, and Stefan Vučićević, outlines how to set up a Lean People Analytics Operating Model that “connects technology, impactful consultation, and strategic decision-making, ultimately enabling ecosystems.”
FIG 24
PODCASTS OF THE MONTH
In another month of high-quality podcasts, I’ve selected four gems for your aural pleasure: (you can also check out the latest episodes of the Digital HR Leaders Podcast – see ‘From My Desk’ below):
ADAM GRANT – Why Meetings Suck and How to Fix Them? Podcast | Transcript – Adam Grant’s WorkLife podcast is always insightful, and this episode where, together with Steven Rogelberg, Rebecca Hinds, PhD, and Francesca Gentile, Adam investigates the science of improving meetings is mandatory listening.
TOBY CULSHAW, COLE NAPPER, AND SCOTT HINES – Everything Talent Intelligence- Toby Culshaw joins Cole Napper and Scott Hines, PhD on the Directionally Correct podcast to discuss what talent intelligence is, what it isn’t, and how it can be effectively applied in organisations.
AMY WEBB AND MOLLY WOOD – The Most Plausible Outcomes for AI and Work – Futurist Amy Webb joins Molly Wood on Microsoft’s WorkLab podcast to discuss the most likely outcomes for how AI will impact humanity and what business leaders can do today to set up their organisations for success.
JOSH BERSIN - The HR Technology Trailblazers: How AI Is Disrupting This Market | Unleash Paris 2023: The Skills HR Tech Confusion. Trailblazers: Docebo, Arist, Cornerstone – Josh Bersin recently announced 15 ‘HR Tech Trailblazers’ who are successfully infusing AI into their products. In these two podcast episodes, he breaks down seven of them: Eightfold Paradox SAP SuccessFactors, Visier Inc. Docebo Arist & Cornerstone OnDemand.
VIDEO OF THE MONTH
ANNE-MARIE ANDRIC AND GARY MUNRO – Bounce. A place to go, know and do
One of the people I was glad to catch up with at Unleash was Katarina Berg, Chief People Officer at Spotify, who shared insights from the company’s Work from Anywhere program on the main stage. One of Katarina’s team – Gary Munro, the Head of People Analytics, is the brain behind Bounce, an ingenious new platform that brings together all relevant workplace content in one place and offers employees a personalised experience. Read Gary’s article on the Spotify HR Blog, and then watch his discussion with the brilliant Anne-Marie Andric on an episode of HR The Real Deal.
BOOK OF THE MONTH
ADAM GRANT – Hidden Potential: The Science of Achieving Greater Things
The new book by Adam Grant is brilliantly written, sprinkled with humour, and incredibly insightful. In Hidden Potential, “Grant explores how to build the character skills and motivational structures to realize our own potential, and how to design systems that create opportunities for those who have been underrated and overlooked.” The book is also immensely readable – I read over half of it on my flight to Chicago yesterday. I also listened to the highly insightful and at times hilarious podcast on the book, where Grant talks to his old sparring partner, Malcolm Gladwell: Unlocking Hidden Potential with Malcolm Gladwell. A must-read and a must-listen.
RESEARCH REPORT OF THE MONTH
YANQUI TAO, LONGAI YANG, SONIA JAFFE, FERESHTEH AMINI, PETER BERGEN, BRENT HECHT, AND FENGQI YOU - Climate mitigation potentials of teleworking are sensitive to changes in lifestyle and workplace rather than ICT usage
Nick Bloom highlighted this fascinating paper during his recent talk at the Insight222 Global Executive Retreat, and summarises some of the key findings in his LinkedIn post here. The main finding of the paper is that, in the United States, switching from working onsite to working from home can reduce up to 58% of carbon footprint of work. Indeed, it finds moving to two days working from home a week reduces carbon use by 11% (see FIG 25). An important paper that highlights how hybrid and remote working can contribute to efforts to reduce an organisation’s carbon footprint.
FIG 25
FROM MY DESK
October saw the final episode of Series 33 of the Digital HR Leaders podcast, sponsored by Visier Inc., and the first two episodes of Series 34, sponsored by our friends at eQ8. Thank you to Adedamola Adeleke at Visier, and Chris Hare, Alicia Roach and Angela Shori at eQ8.
KAT BOOGAARD AND DAVID GREEN - 5 common people analytics challenges (and how to overcome them) – An interview with Kat Boogaard for Culture Amp, on the challenges today’s HR teams face in leveraging people analytics – as well as how they can effectively overcome them.
WENDY CUNNINGHAM AND PETER MEYLER - How to Achieve Data-Driven HR Excellence in a Highly Regulated Environment – Wendy Cunningham and Peter Meyler join me on the Digital HR Leaders podcast to share the evolution of people analytics at the Phoenix Group, how it supports the people strategy, and the role of technology.
NICK DALTON – Seven Waves: The Past, Present and Future of HR – Nick Dalton, formerly EVP of HR at Unilever and co-author of The HR (R)Evolution: Change the Workplace, Change the World, takes us on a journey through the past, present and future of the human resources function.
PIYUSH MEHTA - How to Create Personalised Employee Experiences – Piyush Mehta, chief human resources officer at Genpact, describes how the company uses technology and analytics to enhance and personalise the employee experience for its 120.000 employees: “The role of the CHRO is to make sure that the organisation has top-quality talent at the right place and at the right time, and then find a way to enable that talent to be able to stay on in the company and continue to build that talent engine.”
JESS VON BANK AND DAVID GREEN – Now of Work: Learnings from Unleash – I had the pleasure of joining the Mercer | Leapgen Now of Work Digital MeetUp to discuss learnings from Unleash with JESS VON BANK. Thanks to Jess and Jason Averbook for inviting me.
DAVID GREEN - Influencing the World of Work: Key learnings from The Insight222 Global Executive Retreat 2023 – My round-up of the key learnings from the recent Insight222 Global Executive Retreat in Colorado, which was attended by 60 people analytics leaders and senior HR executives from global organisations.
THANK YOU
Finally, this month I’d like to thank:
Racheli Gabel Shemueli and the teams at Pacífico Business School and APERHU - Asociación Peruana de Recursos Humanos for inviting me to speak at the 29th Human Capital Congress On October 24, 2023
The team at Thinkers360 for including me in their list of Top Voices 2023
Antonio Di Benedetto (here) and Rodrigo Santos (here) for posting about and recommending Excellence in People Analytics
Raja Sengupta for creating a heatmap topic model overview of some of the key topics covered in the Digital HR Leaders podcast over the years.
ABOUT THE AUTHOR
David Green is a globally respected author, speaker, conference chair, and executive consultant on people analytics, data-driven HR and the future of work. As Managing Partner and Executive Director at Insight222, he has overall responsibility for the delivery of the Insight222 People Analytics Program, which supports the advancement of people analytics in over 90 global organisations. Prior to co-founding Insight222, David accumulated over 20 years experience in the human resources and people analytics fields, including as Global Director of People Analytics Solutions at IBM. As such, David has extensive experience in helping organisations increase value, impact and focus from the wise and ethical use of people analytics. David also hosts the Digital HR Leaders Podcast and is an instructor for Insight222's myHRfuture Academy. His book, co-authored with Jonathan Ferrar, Excellence in People Analytics: How to use Workforce Data to Create Business Value was published in the summer of 2021.
SEE ME AT THESE EVENTS
I'll be speaking about people analytics, the future of work, and data driven HR at a number of upcoming events in 2023:
30 October - 1st People Analytics Conference Korea (Seoul - Virtual)
14-16 November - Workday Rising EMEA (Barcelona)
30 November - Indeed FutureWorks (Bengaluru)
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