My Blog

First, we had “quiet quitting” and now, we have progressed to “loud quitting,” the latest buzzword in employee engagement. Quiet quitting describes employees who are not going above and beyond at work and are only meeting their job description. On the other hand, loud quitting has become the recent term that refers to employees who leave their jobs in very vocal and sometimes even public ways. Source: Loud or Quiet Quitting? Forget the Fad, Focus on the Human

Within organizations, taxonomies get complex very quickly — especially as we develop different functional viewpoints, adding industry terminology, process and technology terms, and even the words our customers use. I recently completed a taxonomy rationalization project where I uncovered over 2,700 words employees used to describe or label various products and activities. Only 3% were commonly used by more than one functional group. Source: Why You Shouldn’t Treat Your Taxonomy as an Afterthought

As more and more companies move toward automation, there is growing discussion around the impact AI could have on workers. According to SHRM, 52% of employees today believe they are easily replaceable in their jobs. Source: To Attract and Retain Employees, Invest in Them

For many of us today, work experiences such as applying for a job, requesting new equipment or booking work travel are entirely digital. The evolution toward digital employee experiences has been accelerated both by technology developments and also by the move to more distributed, remote and hybrid work over the last three years. Source: If Efficiency’s Your Only DEX Target You’re Missing the Mark

Many suggestions for what to do with ChatGPT or Bard revolve around prompts, but deeper discussions about prompt engineering deserve attention. While the word “engineering” conjures up the idea of technical expertise, prompt engineering gets into the methods for formulating questions when learning AI-based solutions. As such, prompt engineering serves as the guiding principle for understanding how to best leverage AI. Source: Prompt Engineering: How to Parse Value from Chatbots

The tone and complexion of business conversations have changed a great deal in just a few short months. The overriding theme of many discussions is now operational efficiency, reducing debt overhead and increasing revenue. At the same time, outside and perhaps unanticipated forces are weighing on organizations to revisit their digital efforts.Businesses  that rated their digital maturity highly at the end of last year received a jolt with the meteoric rise of conversational AI platforms like ChatGPT. The digital goalposts have shifted. All of a sudden, it became clear that no one was quite as advanced as they might have believed. Source: Automation Is Coming. Your Teams Should Be Prepared.

Managers have been put to the test over the past few years, and many would benefit from taking the time to turn inwards. To borrow the old adage, managers, manage thyself. Because before you can manage anyone successfully, you must first master the art of self-leadership. Source: Before Taking On Leadership Duties, Managers Should Learn to Manage Themselves

Amid current economic uncertainty and a looming recession, companies are looking for ways to control expenditures to shore up their budgets. For some, this means pausing certain niceties or delaying larger projects; for others, it calls for more drastic measures. Source: Upskilling on a Budget: Workforce Planning in Challenging Times

Digital transformation, of course, is a very general term for the integration of digital technologies into the workplace. And there are as many strategies as there are technologies. So, what’s happening now — and what’s coming next? Source: What’s Next for Digital Transformation

The most obvious impact of the pandemic on the workplace has probably been the widespread pivot to new work models. What has been less talked about, however, is companies’ push toward the deployment of new technologies that enable these models. Artificial Intelligence (AI) is among the most important of those technologies. Following PwC’s view of AI, we can divide the technology into four groups: Source: What Automation Means for Jobs