You can't build enterprise AI if you suck at data & analytics
Saying you use “AI” at your company may give you bragging rights at your industry meetups and even fool the media, but actually implementing enterprise-wide transformation is much harder than just claiming you have.
Before you beg management for an eye-popping AI budget, be aware: not all companies are ready for artificial intelligence.
Unlike flash drives and mobile apps, enterprise-scale AI is not standalone plug-and-play technology. The quality of your data and analytics infrastructure, as well as your organization’s engineering and business culture, are critical foundations for any AI initiative. Even tech-savvy companies like Google have made embarrassing faux-pas, such as mistakenly auto-labeling black people as gorillas.
If you don’t want to end up on lists of top AI fails, keep these implementation principles and practices in mind:
Practice 1: Start With Goals And Hypotheses, Not With Solutions
Shiny new technologies aren’t necessarily better for your specific organization. If you’re only working with less than a few TB of data, you don’t have big data and don’t need to incur the operational headache of implementing a Hadoop architecture. If you’re doing static analysis and don’t need real-time predictions from your machine learning algorithms, you probably don’t need the speed advantages of Spark. Deep learning may be in vogue, but many enterprises find that ensemble approaches combining older machine learning and statistical methods actually outperform modern neural network approaches for specific problems and tasks.
Start with the problem, not with the technology. Clearly articulate business goals and metrics of success, then apply the scientific method of testing various hypotheses to gain knowledge and expertise about the limitations of different solutions. Understanding where technologies fail is as important as understanding where they succeed.
Practice 2: Get The Right Data, Not Just More Data
There’s a common myth that “more data is better” and that “AI needs vast amounts of data to work”. The truth is more nuanced. When asked about the biggest limitation to AI systems today, executives at leading technology firms unanimously agreed that data quality is the key bottleneck.
“AI is like a human, incorrect or bad data will produce bad results,” states Sanjeev Katariya, Chief Architect at eBay. “If you’re not careful and you select data and features that don’t really help with learning, you can wind up with some really erratic behaviors.” Serving more than 160 million active users, eBay reportedly employs thousands of data analysts to ensure the company’s machine learning algorithms are fed the right data with the right quality, a process which takes expertise, time, and patience.
Deepak Agarwal, VP of Engineering and Head of Relevance and AI at LinkedIn corrects a common misconception: “We see a lot of media misreporting about AI taking over human roles. Most AI actually requires more human time either in engineering or in reviewing to ensure that the information the algorithms come up with are unbiased, accurate, offensive or misleading.”
Practice 3: Enforce Data Standards & Enable Broad Access
Business leaders often think they have good data when in fact their data is inconsistent, incomplete, erroneous, sparse, biased, and spread across distributed systems that only specialized engineers understand how to work. Massimo Mascaro, Director of Data Engineering and Data Science at Intuit, explains why his company mandates data cleanliness and organization: “As a financial services firm, we work in a complex, regulatory context that is constantly in flux, resulting in long tails of data across a variety of different use cases.”
Even if you’re not in finance, creating and enforcing company-wide standards and access to data is essential to streamline analytics and machine learning. Consolidate a single source of truth, apply clear labeling and metadata, document religiously to mitigate employee confusion, and built the requisite tools and technologies to enable enterprise-wide access.
Lack of access to critical data causes political challenges and unnecessary delays in large enterprises. Companies we work with who are the most successful at adopting new AI techniques have virtually all encapsulated core business functionality in the form of well-documented internal APIs and interfaces that make cross-department and cross-team technical collaboration easy. Many also deploy business intelligence (BI), analytics dashboards, and visualization tools to help non-technical leaders and employees engage with important insights.
Practice 4: Make Sure Data Owners (Business) Talk To Data Stewards (Tech)
Rare is the enterprise where data owners, business leaders responsible for the information and insights, sit next to data stewards, the engineers implementing and managing data capture, storage, and handling, and actually learn from each other. “For non-technical leaders, there is a misconception that AI can be applied generally,” says Chris Curran, Chief Technologist at PwC. “One skill that remains to be scarcely found is the ability to map a particular business problem to a specific AI technique; there are many techniques and they don't all work equally well.”
The lack of technical literacy in business leaders negatively impacts AI projects. “We often close a sale with a business person who says they have all the requisite data ready to go,” says Robbie Allen, Founder of Automated Insights, an enterprise natural language processing & generation (NLP / NLG) platform. “Then we find out they have no idea how the data is stored, that it’s distributed across a number of systems, and the technical talent required to get the data out properly is booked on other projects for months. That’s how a 3 month project easily blows out to 6 months or more.”
On the flip side, the engineers and data scientists working directly with a company’s data might not be domain experts on the business use cases. Automated Insights, which enables a company to turn quantitative data such as sports scores and earnings reports into computer-generated articles, requires domain expertise to produce the best results. Allen explains: “Text output is not the hard part of NLG. The hard part is determining what is interesting and worth talking about in a story. Sports reporting may seem easy, for example, but many concepts such as leagues, teams, players, coaches, and playoffs don’t exist in other industries. The relationships between all the entities is also constantly in flux.”
Practice 5: Improve Your Executive Culture & Data Literacy
HiPPO is an acronym for “highest paid person’s opinion” and reflects the antithesis of what you want at a data-driven organization. None of us are perfectly free from bias, but an executive culture that is driven by HiPPOs rather than data, objective experimentation, and collaborative thinking will invariably thwart rational thinking and AI implementation across your organization. If your company culture isn’t open to challenging assumptions and adapting to new learnings, you might fall prey to the common practice of cherry-picking data sets to force-engineer insights that jive well with your tilted assumptions and desired conclusions. Refusing to recognize reality typically takes you further, not closer, to your goals.
“Using data as a basis for all decisions, rather than opinions, is a primary reason why we have been successful integrating AI throughout the company,” claims Agarwal of LinkedIn.
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The Cross-Training Secrets of Ultrarunner Sally McRae
If ultrarunner Sally McRae's name isn't familiar to you now, it will be soon. The 34-year-old, Orange County-based ultrarunner finished sixth at last year's Lake Sonoma 50, one of the most competitive ultras in the country, and took second at the Sean O'Brien 50 Mile, in February, earning a slot at this year's illustrious Western States 100.
A mother of two children, ages six and eight, Sally also runs a part-time coaching business for ultrarunners and triathletes; maintains a rigorous, round-the-clock training schedule; and can cram more into a single day than even the most zealous overachievers (her email signature says it all: Sent while running).
I caught a glimpse of Sally at The North Face 50 Mile Championships in December, when she passed me at mile 42: a blur of pink, a beaming smile, and a long, easy gait that made her look like she was just out for a short jog. While I plodded along on wooden legs, she glided by, seemingly chased by an entourage of fans shouting "Sally!" Even from the dark depths of my pain cave, I could tell that she was someone who radiated joy and ease on the trail. So I tracked her down to find out how she gets it done. The answer? Tons of trail time, high-intensity strength work, and the ultimate cross-training regimen of all: parenthood.
How do you fit in all your training?Early on in motherhood, I learned that if I wanted to maintain peace in my daily schedule, I would have to learn the art of balancing discipline with flexibility. This is the reality of life, especially with children. Sometimes you can't plan for the flu, meltdowns, how long homework will take, sports, social events, and family emergencies.
When my kids were babies, I ran with a jogging stroller, and when they were a little older, I took them to the kids' club at the gym and did all my runs on a treadmill (close to 80 percent of my training for my first ultra was on a treadmill). As the kids get older, I've remained committed to using my entire 24 hours. I'll plan out a day's schedule down to the hour the night before, but with full awareness that something unexpected will come up. It's actually great training. Similar to a 50- or 100-mile race, the chance of a race going as planned is a rare gift. If you've trained properly, then you have trained your mind to not break down when things start going wayward.
Give us your secret to balancing trail running and parenthood without losing your mind.Stop using parenthood as your excuse to not run or workout. I hear this on a weekly basis, and it is a poor excuse. It is also a horrible message to send to our children. And I say this with great understanding and compassion for all parents. I know what it feels like to be sleep deprived, overwhelmed, pulled in all directions, busy, frustrated, and utterly drained.
But being a good parent doesn't mean you throw your health out the window; it also doesn't mean you teach your children that when they, too, become parents, that their goals and dreams are no longer important. It's taken me almost a decade to figure how to balance training and motherhood, and I can confidently say that I never will have it down perfectly—because, like life, we're not supposed to have everything perfectly figured out. I enjoy the adventure that comes with being a mother. My kids keep me grounded, balanced, and challenged. Ultimately, they make me stronger and more disciplined.
How do you include your children in your training and competing?Both my kids have been running with me since they were three (short distances at first) and now they compete in local races. They're also a part of their school's running club. If it's a short recovery, they'll join me for five or six miles on the trails. I also have home routines to get my body strong: quick, five- and ten-minute routines for my core, arms, and injury prevention, and sometimes they join me. My daughter, Makenzie, loves to run with me and I try to set aside one to two days a week where we run together and have girl talk. But I do remain mindful of the fact that they love doing other activities, too, so I don't push running on them. When we go on the trails my goal is to simply have fun.
Do they cheer you on at your races?Typically not; for most races I need to get on a plane, so it can get pretty pricey. They went to a couple of my very first trail races when they were babes, and it was hilarious and kind of sad because I'd come into the aid station for 60 seconds and then run away and they'd be standing there crying like, "Wait! Where are you going?" Or they couldn't understand why they couldn't eat the food at the aid stations. I remember the first 50-mile race I won, I likely would have had a better time had I not been bartering with the volunteers to give my crying son a piece of licorice!
You're also a coach. What are your top three favorite at-home cross-training exercises every ultrarunner needs to be doing now?First, single-leg stance exercises. They improve your balance, coordination, and speed. They are often overlooked. Also, make it a point to balance on one foot more. Stand up and balance while putting your shoes on. Stand on one foot while you brush your teeth, talk on the phone, cook eggs. When we run, we are continually in the single-leg stance so you should want to be strongest in this stance. Most runners have some type of weakness or imbalance that can be strengthened by doing these exercises.
Second, hip raises: Lie on your back, knees bent, feet flat, and push your hips to the ceiling and squeeze your butt. Hold for a few seconds and lower back down. Be careful not to arch your back or tense your shoulders as you do this. Do two to three sets of 15 to 20 reps. I think it's safe to say that most runners have weak hips and glutes, partly because we spend so much time sitting. This is an easy exercise. Do it daily!
Lastly, hold a 60-second plank. It's so easy to do, and it strengthens your core and upper body; you can also add donkey kicks to it and get creative with how you progress it. All you need is three minutes for three planks a day. And your kids can do them with you.
What's a typical training week like for you?This varies depending on the distance of the race. For a 100-mile race, my training will peak at a handful of 100-mile weeks. If it's a 50-mile race, I only need 70- to 85-mile weeks to get in tip-top racing shape. I am a huge believer in cross-training, especially for trail runners. When I transitioned from road marathoning, I learned quickly that trail races are not always won by the fastest athlete, but sometimes the strongest most enduring person.
I have a gym routine I do as many as three times a week. I lift heavy weights, do 40 minutes of non-stop core and functional exercises, and then I'll spend a solid 20 minutes stretching and rolling out any tight areas. I like hot yoga but I can only manage it in doses. The idea of staying on my little mat for 90 minutes is difficult for me and how I operate. Typically, I'll do yoga if I've discovered an imbalance or have an injury. Aside from that, the gym is quite enough inside time for me.
What's your favorite, go-to training run?A long run in the mountains that either starts with a sunrise or ends with a sunset (or both!). Since I was a child, I have had a deep love for the mountains. I relish the peacefulness that comes with disconnecting from electronics and the hustle and bustle of the city. I think many people feel the same way—just getting outside for an extended period to enjoy nature and all it entails: the sights, the smells, the sounds. It's raw and it's real and it makes you feel more alive.
Do we really need to be doing tempo runs and speed work?Runners should tailor their training in accordance with their goals. If your goal is to simply complete a race, that looks different than someone who's trying to get on the podium. In the past two years, the sport has gotten faster and faster. More elite road runners are taking to the trails and they're bringing their fine-tuned training with them. This is raising the bar in races. Although back-to-back long runs are necessary for the longer distances at certain stages in your training, they shouldn't trump the rest of your training schedule. The key is variety. Be purposeful every time you run and don't be shy to work an anaerobic or speed phase into your schedule. It will transform your fitness and racing results. Whatever your goals, whatever motivates you, match your training to that. If you want to be fast, you need to have a phase in your training where you're doing fast running, so suck it up and do the speed work!
What's your approach to nutrition?This is the million dollar question. I do not follow any type of plan, although I have experimented with just about everything out there from raw, vegan, Paleo, Atkins. I try to eat as much real food as possible and I pay attention to what makes me feel good. I feel best when I'm eating eggs, fish, veggies, and fruit. I love coffee but feel better when I stick to tea. I did not feel strong as a vegan. Do I splurge? Absolutely. I like pie and donuts after a solid race—they're definitely a treat!
Any ideas for avoiding injury?Stop being stubborn. As soon as it hurts, take care of it. What seems like a slight nag will become magnified as your training enters more intense stages and especially if you are planning to run an ultra-distance. So get on your foam roller, or rub out your feet on a golf ball. Take the time to stretch or get a massage. Get physical therapy if you need it. I used to work at a PT clinic and learned very quickly that the majority of injuries that we saw could have easily been prevented with the most basic at-home care techniques. So stretch, roll, ice, and take rest when necessary. No magic formula there.
How do you keep from burning out?I have a genuine love for running. Although I'm a coach, I have never had a coach myself or even followed a rigid training plan from start to finish. I keep my runs fresh by changing up routes, exploring new trails, and running at various times of the day. Sometimes I run with music, sometimes I leave everything, including my watch, at home. I also make sure every run has a purpose and a goal. This makes every run feel different. One might be short and intense and focused on keeping a certain pace, whereas another is just about chasing a sunset and meditating. I'll go on long runs and pray for people. I remind myself daily to be thankful for the ability to run. Every day that I get to run is a gift.
What inspires you most about racing ultras?When I set a goal for a race, it's not just about getting on the podium. It's about communicating a message to the people around me. Go after your dreams, believe in yourself, never give up. I've toed the line next to runners in their 70s. Sure, we finish at different times, but we went the same distance, we crossed the same finish line, and it was hard. You must have courage to sign up for an ultra distance, and I have unrelenting respect for every single person who ventures to believe that he or she can go the distance. When was the last time you had a chance to stand among a mob of courageous, hopeful, strong individuals?
Lead Photo: Courtesy of Sally McRaeHR Technology in 2018: 10 Big Disruptions Ahead
HR TechWorld 2017
I’ve been an analyst following the HR Tech market for almost 20 years now, and this year things are changing faster than ever. In the report we just published, “HR Technology Disruptions for 2018,” I describe the details. In this article I’ll summarize the ten big changes going on.
1) A Massive shift from “automation” to “productivity.”
For many years the focus on HR technology was to automate and integrate HR practices. This meant online payroll, record-keeping, learning management, resume capture, interview and hiring, assessment, performance appraisals, compensation, management, resume capture, interview and hiring, assessment, performance appraisals, compensation, etc.
Well all that’s important, but it’s just “business as usual” now. A wide range of cloud-based HRMS and payroll vendors are now in the market, and you get very little credit for “automating” HR. (You do get penalized if you don’t of course). Our new High-Impact HR (HIHR) research shows that about 45% of companies are still focused on basic process automation, so I understand if this is still top on your list.
But beyond automation, as the HIHR article discusses, the big topic in business today is productivity. We are now working on agile, team-centric organizations, and we are overwhelmed with too much to do. Burnout, focus, and employee engagement are all issues, and we are now dealing with email, messaging from many different systems, and a plethora of communication tools that overwhelm most of us. Can we build HR software that really improves productivity and helps teams work better together? That’s the next challenge.
2) Acceleration of HRMS and HCM Cloud Solutions, But Not The Center Of Everything
In the last five years, cloud-based HR has become the rage. I could list more than two dozen highly successful vendors that offer HRMS, payroll, and many talent management services in the cloud. And in most cases they are offering financials and other ERP solutions as well. So the question for most companies is no longer “if” you go to the cloud, but rather “when” and “how.”
Well it’s harder than it looks. Despite these rapidly maturing solutions, only about 40% of companies today use cloud HCM solutions, and my experience with large companies is that the migration often takes 2–3 years or longer. (There is a lot of customized HR software out there.) So we are going to be “moving to the cloud” for a while yet, and the decision of which vendor to select looms large. In fact most companies ponder their vendor decision for months (or years), and feel the decision will have radical impact on their entire employee population.
Well despite strong marketing from the HCM companies, I believe this worry is misplaced. While the cloud HR and payroll system is a critical system for any business, it can be replaced. And the more important technology you buy (as I discuss in trend 1) is the talent and team management software. So your architecture looks more like a “set of services” all focused on making employees’ lives easier… not a single cloud vendor.
This topic will be the subject of another article, but let me just tease you with the slide below. This is what HCM architectures of today really look like. The most critical part might be that green layer in the middle, which we can probably call the “employee services” layer (which is looking more and more like chatbots every day).
Read more about this in the report, and stay tuned for more on this topic. My belief is that a new “breed” of HCM software is emerging, and as I describe above, I believe it looks more like “team management” and less like “talent management” every day.
3) Continuous Performance Management Is Here: And You Should Get With It
I wont belabor this topic (read “The Myth of the Bell Curve” for more), but the answer is now clear: continuous performance management is possible, it works, and it can transform your company. We are not talking about doing away with ratings, rather we are talking about building a new, ongoing process for goal setting, coaching, evaluation, and feedback.
The report discusses all the details (including vendors) but let me leave you with one big finding: despite the tremendous success of the cloud HCM vendors in the market, most do not have a total solution for this problem. So you are going to be buying new products to address this issue, and these new “team-centric” tools are likely to become the future leaders in the HCM market of the future.
4) Feedback, Engagement, and Analytics Tools Reign
Only a few years ago the engagement survey market was a robust but sleeply place. Today it has become a dynamic world of real-time survey systems, sentiment analysis software, organizational network analysis (ONA) tools, and products that actually automatically ask your peers for feedback to give you real-time coaching.
And open feedback tools are growing again, giving employees many new places to comment on the workplace. A new area of growth is the explosion of systems to offer pay transparency and are now crowdsourcing and providing benchmarking tools to help you “find your worth” (a phrase Glassdoor coined) through open feedback and benchmarking.
As I wrote about a few years ago in the article “Feedback is the Killer App,” I believe this explosion of transparency has been very healthy for business, and it has spawned a new set of pulse surveys, AI-based analysis and recommendation systems, and culture assessments throughout the marketplace. You can get this technology from startups, ERP vendors, talent management systems, and embedded in the new performance management systems. I think companies have to think about this as an overall architecture, but this is still a new world.
5) Reinvention of Corporate Learning Is Here
I’ve written about this extensively (read The 10 Disruptive Changes in Learning) but the simple message is this: a new breed of corporate learning tools has finally arrived, and companies are snapping them up quickly.
These include the “experience platforms,” a new breed of “micro-learning platforms,” modernized LMS systems, and new AI-based systems to recommend learning, find learning, and deliver learning. Virtual Reality-based learning is now alive and well, and I expect to see smarter and smarter technologies to help us find “just what we need” along the lines of performance support. And you can now buy systems that let employees publish and share content without any major effort on your part.
6) The Recruiting Market Is Thriving With Innovation
Recruitment is the largest marketplace in HR. Companies spend billions each year on recruiting and it has become an escalating war for employment brand, candidates, candidate experience, and strategic sourcing. High volume recruitment (hospitality, services, healthcare, retail) is being automated by chatbots and other new tools; skilled job recruitment is being revolutionized by open sourcing tools, more automated applicant tracking systems (now called recruitment management systems), and better assessments. And video assessment and culture assessment tools have matured so far that everyone can use them.
I find this part of HR technology the most dynamic and innovative, primarily because every major company has to buy a whole tapestry of tools to compete. I liken the recruitment technology market to the problem builders face in construction. You need an entire toolset of world-class machines to do the job, and each one has its own learning curve to use well. Recruiters are like the finished carpenters of the trade: they become better and better over time, and suddenly you find out your competition is stealing your people and you don’t know what hit you.
The market has gotten hotter than ever, with unemployment rate near record lows. We are back into the “war for talent” (a 15 year old phrase) and this time “the talent is leading the charge.” In other words, all the new technologies are making recruiters smarter about candidates, just as candidates are getting smarter about your companies.
Remember also that the old fashioned “job description” is really going the way of the dinosaur. More and more jobs are “hybrid” and rapidly changing, so the new world of tools has to help us find people with the right capabilities and learning skills, not just technical or cognitive abilities. And diversity is now a core part of recruiting, with new technology to help remove bias from job descriptions and reduce bias in interviewing (even VR can help with this). Lots to read about here.
7) The Wellbeing Market Is Exploding
I probably don’t need to mention that HR technology, content, and tools for wellbeing may likely be the next “big thing” in business. Not only do we need tools to improve productivity and reduce cognitive overload, but we also need “nudges” and data to help us exercise, stay mindful, and learn how to sleep and eat better. In the report I tried to describe some of the most innovative new solutions in the market. My experience with these vendors is that most of them are driving tremendous value for their customers, and the clients I talk with are seeing rapid adoption of these tools (especially among younger workers) and great improvements in engagement, health, and mental wellbeing.
At Deloitte, following the path of most companies, the wellbeing initiative moved from a focus on “health” to a focus on “reducing burnout” to a new focus on “human performance.” This is the journey most HR departments are going through and the vendor market is moving fast.
We have been doing research on “energy at work” and I think this concept may best encompass the new world of “engagement, productivity, and wellbeing” in one simple concept. These new tools can help us measure energy, figure out why and where energy is low, and give us individual nudges and tips on how to improve our energy. Lots to read about on that topic.
8) People Analytics Matures And Grows
We will soon launch our new maturity model on People Analytics and what you’ll see is a tremendous shift from companies “playing with models” to companies “seriously investing in infrastructure” to bring all their people data together. As I’ve discussed many times, employee-related data (and all the aspects it includes) is just as important or more important than customer data, because it tells you the secrets of how to manage your business better.
The marketplace is now rich with embedded solutions (nearly every HCM vendor has embedded analytics, many with prediction engines), and all the new vendors are starting to apply AI to their offerings. While this market has been very long in coming, the growth of cloud platforms is now making it explode, and it’s easier than ever to build a manager-level dashboard that helps your teams understand what they can do to make the work experience better.
At the corporate level, the ONA software market is now growing (organizational network analytics) so a new world of “relationship analytics” is taking hold. We can now look at core HRMS data (turnover, tenure, performance rating), relationship data (who you know, who you spend time with, what teams you are part of), wellbeing data (your activity, location, energy, wellbeing), and your sentiment data (feedback, mood, and sense of belonging). All this data is falling into the laps of HR departments and they are now staring to grapple with the issues of ethics, privacy, and becoming more transparent about what analytics they are doing.
There is a fundamental shift away from “PhD People Analytics Projects” to more business-oriented programs that help study sales performance, team performance, and other business critical issues. And as I discuss in the report, companies at Level 4 in our new model are delivering real-time dashboards to managers to make this all actionable. I personally see People Analytics as the lynchpin of success for HR in the next few years, as all these other technologies throw off data at an ever-increasing rate.
9) Intelligent Self-Service Tools
If you’re a software person like me, you have to ask the question: how do we bring all this “stuff” together into a seamless employee experience to make work better? Do we build apps? Do we upgrade our employee portal? Do we hope AI and conversational systems will sit on top of everything? It’s quite a complicated issue.
In today’s HR technology environment perhaps the most important new market is the fast-growing need for self-service, employee experience platforms. As I describe in the report, these are fast-changing systems that bring case management, document management, employee communications, and help-desk interactions into one integrated architecture. They sit between employee apps and back end applications, and they serve as the lifeblood of your employee service centers (which are going to be more automated every day).
And AI is coming fast. We had Diane Gherson the CHRO of IBM come to our research conference this Spring and she showed off a cognitive manager coach, a cognitive career coach, and a cognitive recruitment coach. Most of these tools are now becoming products to buy, and I’ve seen and talked with vendors that offer smart chatbots (focused on a single domain), intelligent agents, and amazingly fun games that make training, expense reporting, time tracking, and almost every other HR function easy. One vendor showed off a voice application which lets you query the system for vacation balance, performance tips, and even compliance training.
I think this is a huge new market, and I”m not even sure what to call it yet.
10) Innovation Within HR Itself
The tenth disruption I’ve written about is the incredibly rapid growth in innovation projects within HR teams. We, as HR professionals, are now becoming the disruptors. It used to be we waited for tech companies to invent things — then we figured out how to use them and bought them. Now HR departments are experimenting with new performance management models, new learning strategies, new ways to reduce bias, and new techniques to recruit and coach people. Then they go into the market and see if vendors are available. This shift to me is a disruption itself — forcing the HR technology community to move even faster than ever.
I encourage you to read the whole report, it was quite an effort to get it finished. This is a rapidly changing market and one in hypergrowth mode this year. I hope our research helps you make some sense of all these changes and I look forward to your feedback.
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Josh Bersin is principal and founder of Bersin™, Deloitte Consulting LLP, delivering analytics, research, and tools that employers use as a foundation for day-to-day decision making. He has worked with hundreds of companies to help them deliver high-impact employee learning, leadership development, and talent management.
Do you want to understand the biggest human capital trends for 2018? Join our 2018 Global Human Capital Trends Study here — you will receive a special invitation to the findings next Spring! Click here!As used in this document,
“Deloitte” means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see www.deloitte.com/us/about for a detailed description of our legal structure. Certain services may not be available to attest clients under the rules and regulations of public accounting.
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