Mon, 20 November 2017
Jenny Dearborn is the Chief Learning Officer and Senior Vice President at SAP, a global software company. Dearborn leads an internationally-acclaimed and award-winning team recognized as the #1 performing corporate learning department in the world by eLearning Magazine. As global Chief Learning Officer for the 67,000 employees at SAP, Dearborn is accountable to design, align and drive SAP’s overall learning activities to enable measurable business impact. She is also an author of a new book, The Data Driven Leader.
Before SAP, Dearborn began her professional career as a high school teacher. After a brief stint in that role, she moved into education in the business world. She was Chief Learning Officer at SuccessFactors for two years where she won numerous industry awards for the measurable business impact of her sales enablement initiatives. She was at Sun Microsystems for 6 years where she was the global Chief Learning Architect across all corporate content and was the Chief Learning Officer for the Americas. Dearborn was at Hewlett-Packard for 8 years where she started as an instructor and instructional designer and progressed to executive positions as the Learning & Development leader for Global Sales & Enterprise Marketing, Global Technology Services and Global Corporate Learning Strategy.
According to Dearborn, people analytics is crucial for leaders to use the data to understand the best way to use their time. First, look at the goals you are trying to achieve. From there you identify data that you need to assess properly.
Suggestions for a smaller company to use data to form change:
How does a person become a human leader in a world driven by data? Data allows you to be more human. It gives you the opportunity to focus on what people truly need to make a difference in their lives or performance. If we spend our time in a variety of programs or conversations that aren’t targeted – without knowing what will make the biggest difference in their lives then we aren’t being productive.
In 5 – 10 years Dearborn believes that organizations will have more tools to support productivity, more voice triggered support systems, more voice to text in our everyday environment and there will be more robots in our lives.
What You Will Learn In This Episode:
Mon, 13 November 2017
My conversation today is with Rebecca Chandler, the Chief Learning Officer and Global Director of the Learning Group at Steelcase. We are talking about real life examples of what Steelcase is doing to promote learning and development, how learning has evolved over the past few decades and how leaders and managers can role model the desired learning behavior in their organizations.
Rebecca Chandler is the Chief Learning Officer and Global Director of Learning and Development at Steelcase. Steelcase is a global organization that provides furniture solutions that reflect what they’ve learned about human behavior. It employs about 14,000 employees.
Chandler is charged with making Steelcase the pacesetter for learning organizations worldwide. Steelcase looks to her team for learning solutions that are linked to the needs of the business, and to progress in creating learning that is globally integrated and holistic in nature. Learning is embedded in the culture of their organization, Steelcase views it as just another way for their employees to "love the way they work".
A Chief Learning Officer is usually with tasked thinking about the learning infrastructure to support the local culture and goals. They look at the curriculum, what the organization is focused on, how people share learning and how to speed up learning.
Steelcase education is on an evolution. They offer a lot around active learning. They understand that people need to engage in a variety of ways. They have a “Think, Make, Share” program.
The ‘Think’ gives people a chance to do pre-work. This is often called a ‘flipped classroom’. This leverages the time when people are together.
‘Make’ includes the time together which provides opportunities of creating projects with feedback from an expert.
‘Share’ is about learners/employees going back and teaching others. This solidifies the knowledge they’ve gained. Other times they may be asked to do some sort of action project.
Steelcase’s learning programs fit into one of these 4 buckets:
Technology in education – learning systems push content to the organizations. There is a need to understand how people are using technology and then design from that perspective. Technology should enhance the learning.
Role of culture in learning- Culture and learning go hand and hand. We like to develop curriculum that aligns with culture
Role of physical space in learning – Providing opportunities for people to use space creatively. At Steelcase they consider the entire building a living laboratory.
What you will learn in this episode:
Sun, 5 November 2017
Marc Goodman is one of the world’s leading authorities on global security and the New York Times Bestselling author of Future Crimes: Inside the Digital Underground and the Battle for Our Connected World —selected by the Washington Post as one of the 10 Best Books of 2015 and by Amazon.com as the best book of 2015 in Business & Investing. Goodman founded the Future Crimes Institute to inspire and educate others on the security and risk implications of newly emerging technologies. He also serves as the Global Security Advisor and Chair for Policy and Law at Silicon Valley’s Singularity University, a NASA and Google sponsored educational venture dedicated to using advanced science and technology to address humanity’s biggest challenges.
Beginning his career as a police officer, over the past twenty years Marc Goodman has built his expertise in next generation security threats such as cyber crime, cyber terrorism and information warfare through work with INTERPOL, the United Nations, NATO, the Los Angeles Police Department and the U.S. Government. For over a decade, Goodman trained numerous expert working groups on technological security threats while serving as a Senior Advisor to INTERPOL’s Steering Committee on Information Technology Crime. He has worked with various UN entities and was asked by the Secretary General of the United Nations International Telecommunications Union (ITU) to join his High Level Experts Group on Global Cybersecurity.
Crime has changed drastically over the last few decades. One major change is the ‘location’ factor. Previously, crime was local – a bank robber or a car thief who lived locally, committed the crime locally. Now, the internet has changed that and the location of the crime can happen anywhere. For example, someone in Russia can attack someone in San Francisco. This requires law enforcement to work very differently. “You no longer have co-location of victim, criminal and evidence.” This factor has broken the criminal enforcement system.
How does hacking work? Cyber attacks are automated. This is another thing that is different than the past. Previously someone had to do the crime. Now it’s automated. There is ‘crimeware’. It can be programmed to do identify theft, attack data, etc. Only a small percentage is customized. Those are often the state sponsored attacks.
Identity theft is more serious than credit card theft. A person takes over your credit cards but also mortgage, Facebook, medical records and so on. This can take years to clear up.
Additionally, there is the hacking of video cameras – for instance through baby cameras. Perhaps you take your cell phone into the bathroom – you don’t want someone to hack into that while you are there. Every computer is hackable. Your phone, your camera, your car are all ‘computers’ and, therefore, hackable.
Ninety-five percent of all data breaches can be linked back to human error. If employees are not aware of ways this can occur they are putting their company at risk of being hacked. Companies are being proactive training their employees. For instance, they are sending out fake phishing emails to assist with knowing which employees might click on a bad email and then using it as a teachable moment.
A few things people can do to protect themselves:
· Increase laws, public policy and regulation. Regulation could be useful. For example, CA first to have mandatory data breech hack notifications. As the result everyone in CA was notified. People in the other states were not notified. Good data breech notification is important and strong penalties. · Check out to see if your accounts have been hacked @ haveibeenpwned.com · Go to Goodman’s website: futurecrimes.com – tips
· Be careful what you ‘click on’
· Consider changing the account in your computer that you are using in the ‘administrator role’ to a ‘user’ role.
What you will learn in this episode:
· How crime has evolved over the last few decades
· Steps you can take to reduce your risk of being hacked
· Find out how your online dating site might give away more info that you want it to
· How the Equifax hack happened
· The connection between terrorism and technology
Mon, 30 October 2017
Susan Steele is the former CHRO at Millward Brown, the former CHRO at Deloitte Consulting and currently she is an Executive Partner of Global Talent & Engagement at IBM. Steele has had repeated success at building and turning around the HR function, driving new sources of revenue, enhancing client care and improving business results.
With IBM’s more than 350,000 employees around the globe, there is a great deal of innovation in HR. For example, when a candidate is using a cognitive tool called Watson – a job finder or candidate fit tool - it can assist them in the application process. In fact, anyone can use Watson, just go to IBM.com and look for the career site. Watson is part of the career page.
Most recruiters are working on filling 10 -15 roles at any one time. Using Watson to prioritize the candidates is very useful. Recruiters also use Watson to use to see which candidates will be successful. Even with all the Watson technology, it is still only making recommendations to humans. It isn’t handing over all the decisions on a cognitive tool, people can overrule or go beyond it. “The tool makes recommendations rather than taking over the recruiting function.”
Once people are employed by IBM, internal mobility is encouraged. They use a tool called Blue Matching. It is a cognitive tool to assist locating different roles that might be a good fit for current employees. It is great for lateral or other internal moves and might include positions they haven’t thought of. It is widely used. However, this isn’t a matter of just getting technology and plugging it in. It also needs the support and culture of leaders that believe that internal mobility as a positive, rather than the employee leaving the organization.
A current focus at IBM is learning agility. Every organization is challenged to develop new skills quickly, be able to pivot and address new opportunities and market disruption. So, taking Watson and transforming the learning opportunity has been very beneficial. Imagine using your phone to get personalized learning opportunities. Like podcast? It would know that and recommend some of those. Prefer books? Again, it would use those in ‘bit size’ pieces. If someone had 5 minutes to listen to the learning as they are waiting in airport, etc. then serving it up in a using a very user friendly format improves access to the learning. “IBM learning is through the roof”. Everyone is expected to have 40 hours per year and many are going beyond that because it is so engaging. “Learning is being turned on its head because of cognitive technology.”
One of the current challenges at IBM is finding the right talent with the right skills. To help solve this, they are taking a broader perspective. Their CEO is talking about a ‘new collar job’ – don’t need a college degree. This describes about 10 – 15 % of their employees in the US that they have recruited in the last few years. They have technical skills, coding, etc., but they not roles that require a full breadth of a college degree.
Things you will learn:
Links from the episode:
Mon, 23 October 2017
Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business” and “Big Data MBA: Driving Business Strategies with Data Science”, is responsible for setting strategy and defining the Big Data service offerings for Dell EMC’s Big Data Practice. As a CTO within Dell EMC’s 2,000+ person consulting organization, he works with organizations to identify where and how to start their big data journeys. He is a University of San Francisco School of Management (SOM) Executive Fellow where he teaches the “Big Data MBA” course.
Big Data is a term. The adjective ‘big’ has no meaning. Most companies are interested in looking at the ‘boat load of data’ they have but are not sure what to do with it. Right now, companies are only looking at the data to see ‘what happened’. “The biggest challenge from IT side and business side is to understand how they can understand data to effectively power their business model.”
Dell is using data to do predictive maintenance on their equipment. The goal is to fix devices before they break. They do this with employees and health care. “We try to drink our own champagne – use data internally, so we can be credible in the marketplace.”
Why have data if you aren’t going to use it? “Data by itself is a glob of nothing. You need to have an analytic strategy to tell what data is needed.”
Organizations need to know what problems they are trying to accomplish then can make analytics on those. If you know the problem to solve, you know the analytics and data you need. Then it becomes easy. Ask the questions first. Business has to drive IT. Data is a business conversation about economics. Then you can exploit the use of data.
There is a new position, the Chief Data Officer. It’s a good idea, but there has been poor execution. What has been happening is taking a CIO and giving them a
new title of CDO. However, it should be the Chief Data Monetization Officer. The job is to determine how to monetize the data you have available. This should be an economics person rather than IT person.
Schmarzo’s advice for people who are thinking about big data?
Business people: Read his book written for business people. Also, check out his blog as he frequently blogs about big data. He recently wrote about how to become intelligent like Netflix.
Everyday people: You need to understand the basics. Start reading, attending the free online classes, read blogs. Begin to understand what is machine learning and AI is all about. Don’t be afraid; just spend 15 minutes a day to become more familiar.
What you will learn in this episode:
● Why the term Big Data is a misnomer
● How Dell is using data
● The ‘mindset’ of data
● Why big data is about economics, not technology
● How much of a CIO’s background should be in technology vs. business and economics
● What role data plays in AI, wearables and machine learning
Links from the episode:
● Blogs: infocus.emc.com/author/william_schmarzo/ (Blog)
● LinkedIn: linkedin.com/in/schmarzo
Mon, 9 October 2017
Ep 155: Employee Experience, Preparing for the Future of Work, The Importance of Building a Human Company, and more
Jacob Morgan is an author, speaker and futurist living in the Bay Area. He recently started a new Facebook group called, The future if. This group is a global community of business leaders, authors, and futurists who explore what our future can look like IF certain technologies, ideas, approaches and trends actually happen.
Jacob is also working on a new course called The Future of Work Crash Course. This will go live in a few weeks. It is a companion course for his newest book, The Employee Experience Advantage.
He is looking at writing another book, sometime in the next few years. In addition, Jacob is looking at creating more interesting podcasts and interviewing new, fascinating guests.
What themes have stood out for Jacob from hosting this podcast?
First of all, Jacob says he’s learned a lot in the past 3 years and it turned out that a lot of people also enjoyed learning along with him. The podcast gets about 4000 – 5000 listens per episode, about 30,000 downloads per month.
One thing Jacob loves about the podcast is that the guests are honest. In conferences, events, etc. the information that comes across is often sanitized. The guests don’t get an advanced list of the questions, so it feels like it is a coffee shop conversation.
Jacob shares that he is amazed the future of work and the employee experience is getting so much traction. From HR to IT, a lot are paying attention to this. Jacob likes to think he had a hand in driving some of that. He is pleased that companies are thinking about this. Jacob is always amazed to hear how far companies have come along. From workspace design to corporate culture and where employees want to show up.
What is Jacob’s vision for the future of work? He believes that in 5 years – 10 years out, not much will be different. There will be some evolution but it won’t be unrecognizable. In 50 years, he feels there will be a heavy and strong emphasis on AI. Perhaps androids. Maybe.
What should Jacob encourage leadership to think about? First of all, remember it’s People 1st, Technology 2nd. There is no substitute for people. No company can exist without people
It is also important to build a company that people want to work for.
How do you create systems to prepare people for the future of work? Jacob says you have to start by understanding the purpose of schools; schools don’t do a good job of preparing people for the future of their work. The purpose of schools is changing.
What threats will companies face in the future around the subject of compliance and integrity? One thing is transparency – companies need to be aware that both positive and negative information is out there. Another threat is the pace of business (for example, Uber). And also putting the right people in positions of power
What does Jacob feel is hype and what is reality? He says the most hype is around augmented and virtual reality and AI. He doesn’t believe we will see massive job displacement. Wearables are cool but they are on the fringes.
There are some things that Jacob feels are likely to happen and the ideas and technology are there but we are the barriers to these changes. In 10 years or so out - Jacob expects scalable virtual assistants, autonomous vehicles (10 years or so out). Also, we will rely more on voice commands. But Jacob sees that there is a lack of discussion around timelines for these things.
What You Will Learn In This Episode:
Mon, 25 September 2017
Today’s guest is Seth Stephens-Davidowitz, author of Everybody Lies: Big Data, New Data and What the Internet Can Tell Us About Who We Really Are. During our conversation Seth talks about what it was like to work at Google and why he left, how he went about analyzing the data for his book, why he believes we are all liars, and what he learned about our true human nature.
Seth Stephens-Davidowitz has used data from the internet -- particularly Google searches -- to get new insights into the human psyche. A book summarizing his research, Everybody Lies, was published in May 2017.
He worked for one-and-a-half years as a data scientist at Google and is currently a contributing op-ed writer for the New York Times. He is a former visiting lecturer at the Wharton School at the University of Pennsylvania. Seth received his BA in philosophy from Stanford, and his PhD in economics from Harvard.
The area of big data that Seth researches is ‘social science questions about what people want and need’. It is very straightforward based on information that humans create. (Like from Google or Facebook)
Traditional social science experiments take months but today it is possible to experiment in minutes using such resources as Facebook.
When asked what a data scientist is, Seth said that it is someone who knows how to code and build models of human behavior to predict what people will do and what will work in the future.
For his book, Everybody Lies, Seth used Google searches to measure racism, self-induced abortion, depression, child abuse, hateful mobs, science of humor, sexual preference, anxiety, son preference, and sexual insecurity, among many other topics.
Just a few of the topics discussed in the book are sex, searches for sons vs. searches for daughters, anxiety, and insecurity.
When asked questions about these sensitive subjects, people may lie. But searches indicated a variety of areas people search - areas that people don’t talk about. Therefore, people seem to have more interest in these topics than they are willing to admit.
Searches with the term ‘daughter’ are most often asking about issues related to appearance. For example, ‘How can I get my daughter to lose weight?’ For the term ‘son’ it is often, ‘Is my son gifted?’ There seem to be marked differences between sons/daughters in the searches that use these two terms.
While common thinking may be that those living in large urban areas such as NYC or San Francisco are more anxious, Seth’s research showed that searches for these terms was higher in Kentucky, Rhode Island and Maine - and in rural areas, contrary to common thought.
Stereotypes are often wrong. It is often assumed that women have many more insecurities about their bodies. However, the data does not show an overwhelming number of women versus men searching about these topics. In fact, about 60% were women and 40% of searches are men – not a ‘blowout’ on the side of women - that might have been thought.
Seth’s advice for individuals living in this new data world is to understand that Google has a lot of incentive monetarily to keep our data private, so he is not worried. One thing he is concerned about is that we may enter a society where we put resources such as time and energy, towards how we present ‘on paper’, because we are worried that we might be penalized based upon our ‘paper trail’ - and that could become a problem.
His advice to organizations is to use A/B testing (analyzing what people click on) is highly effective and should be used even more.
What you will learn in this episode:
● Surprising most often searched terms in Google
● Advice for individuals living in this new data world ● Tips and discussion on Google Trends – website with data that is available to everyone
● What was it like working for Google and why he left
● How Seth analyzed the data for his book
● Why Seth believes we are all liars
Mon, 18 September 2017
Michael Bungay Stanier is the founder and senior partner of Box of Crayons, a company that works with organizations, ranging from AstraZeneca to Xerox, to help them do more great work. A Rhodes scholar who earned both arts and law degrees with highest honors from Australian National University and an Master’s degree from Oxford, he is a popular speaker at business and coaching conferences, and was named Canadian Coach of the Year in 2006
He is also the author of a number of books, his latest book, The Coaching Habit: Say Less, Ask More & Change the Way You Lead Forever, was published in February 2016 and is a bestseller.
Bungay Stanier talks about how it is possible, in 10 minutes or less, to ask strategic questions to drive changes in behavior, have a more engaged, smart, autonomous team that will allow you to work less hard and have more impact …if you stay curious.
The 7 essential coaching questions that he talks about in his book are:
To have authentic conversations, the culture needs to be one in which employees feel safe to share. Consider TERA when considering your work environment.
TERA stands for:
Tribe – make it feel like ‘you & me’, rather than ‘you versus me’
Expectation – how do I know what is about to happen
Rank – how do I feel the same as you rather than less than you
Autonomy – how do I get to make some of the choices, rather than you telling me everything I need to do
Bungay Stanier advises employees who want to be coached by their managers to be the change they want to see in the world. Practice being more coach like yourself. Ask your manager for what you want (and buy the book!).
His advice to managers who want to get started as coaches is to pick one thing and see if you can get some traction on that. Go to coaching.com and download the first few chapters. Pick a question, build a habit around it, practice it and when you fall off the wagon, start again.
What you will learn:
Mon, 11 September 2017
Cathy O’Neil is a mathematician who has worked as a professor, hedge-fund analyst and data scientist. Cathy founded ORCAA, an algorithmic auditing company, and is the author of Weapons of Math Destruction.
Cathy says she was always a math nerd. She loves the beauty of mathematics, and says it is almost an art – the cleanliness of it. One of her favorite things is that math is the same no matter what country you go to. She also had had an interest in the business world, which led her from academia to work as a hedge fund quantitative analyst.
Big Data is both a technical and marketing term. The technical term depends on the technology you are using. Big data used to mean that it was more data than you could fit on your computer – now it means more that you can perform in a simple way – that it needs to be put it into another form before it can be used.
The marketing term, ‘big data’ is misleading. However, it represents the belief that you can collect data for one thing but then the same data can be used for another purpose. “It is a technology that allows us to collect seemly innocuous data and use it for another purpose.”
One profession in which O’Neil has at looked at the use of big data and algorithms in detail – and discusses in her book – is teaching and their evaluations. She says there were teacher evaluation algorithms originally designed to eliminate the achievement gap between ‘rich kids and poor kids’. Eventually, a new system was devised entitled, ‘value added teacher model’.
The idea of this new system intended to offset the previous way of looking at assessing teachers - where they solely looked at the teacher’s students’ final test scores.
The ‘value added score’ system holds teachers accountable for the difference between students’ final score and what they were expected to achieve/receive.
O’Neil says that this method ‘sounds good’ and seems to ‘make sense’. However, with only 25 (or so) students in one teacher’s classroom, there is not enough data. Additionally, both the expected and actual scores have a lot of uncertainty around each of them. So this final number ‘ends up not much better than a random number’. With that, there is not enough credible data to base important decisions such as terminating a teacher’s job.
One of O’Neil’s main points in today’s discussion is that every algorithm is subjective. Whether it is used to evaluate teachers, hire or fire employees in a financial organization - people should know that they have the right to ask the algorithm explained to them. The 14th Amendment provides them ‘due process’ to ask why they are terminated, not promoted, etc. - other than just alluding to a algorithm result.
What you will learn in this episode:
Mon, 4 September 2017
Perez-Breva, PhD is an expert in the process of technology innovation, an entrepreneur, and the author of Innovating: A Doer’s Manifesto for Starting from a Hunch, Prototyping Problems, Scaling Up, and Learning to Be Productively Wrong. (MIT Press 2017).
Currently Perez-Breva directs the MIT Innovation Teams Program, MIT’s hands-on innovation program jointly operated between the Schools of Engineering and Management. During his tenure, i-Teams has shepherded over 170 MIT technologies to discover a path to impact. He has taught innovating as a skill worldwide to professionals and students from all disciplines; and has gotten them started innovating from pretty much anything: hunches, real-world problems, engineering problem sets, and research breakthroughs.
There is a lot of confusion around the term Artificial Intelligence – AI. What is it?
“Today AI is essentially an aspiration. What we do have is – a lot of – automation, machine learning, data learning and robotics.” The dream is to have a partner. Google show how you would operate with AI. You go into Google, use keyword and can get the information you need. We are all more powerful because we can so readily go onto Google to find answers. Siri and Uber are neither really ‘intelligence’. Intelligence is much harder than what we thought.
Does Perez-Breva think job displacement will happen? He believes we are confusing AI with automation. Automation has always made jobs ‘disappear’. For example, gas lights, now we have light bulbs. We have always had jobs be lost to automation. The question is to how do make sure we are training leaders so that they are creating those new jobs into the middle class.
Automation can create gateways to the middle class – such as Ford did 100 years ago. If you don’t find a new job, it is a lack of imagination.
Robots are in all of our local coffee shops – are they taking the jobs of humans?
Not as easy as it might seem…the number of robots that would need to be produced and maintained is massive. One robot in one coffee shop is an example of human endeavors but one in every coffee shop seems a bit of a reach.
What you will learn in this episode: