Don’t turn your HR Tech into a Crystal Ball!

This is the first video in my Behaviour technology Vlog. Maintaining the ethical upper hand with AI technology is important, but we can so easily be misled by advanced technologies. Enjoy the story 🙂

Behavioural Technology series

Very happy to announce the release of a new Video series on Behavioural Technology – the intersection of Human Behaviour and Technology.

This is an exciting space, and one that is becoming increasingly important for HR professional. But as we begin to understand what Digital Transformation really is, Behavioural Technology understanding is becoming an important aspect of project Management, SaaS system configuration and technical integration.

I’ll be releasing a new video once or twice a month and I would be keen hear from you on specific topics of interest.

I often take many of my topic leads from Cognitive Biases and apply them to the work environment where people are interacting with technology. A cognitive bias is a systematic error in thinking that occurs when people are processing and interpreting information in the world around them and affects the decisions and judgments that we make. Cognitive biases are often a result of our brain’s attempt to simplify information processing.

Introduction video on new blog series on Behaviour Technology

Drag & Drop using Squirrel: Tips & Tricks

“Just an illusion”…. (a great 80’s song too)

Squirrel doesn’t provide drag & drop capability on its standard objects. There are some minor exclusions to this, but generally, it’s expected that you dynamically hide or show objects rather than moving them around the screen.

But hey, you’re different right!

and have a great idea that requires the ability to drag and drop an item around the screen. Well, there is an (illusionary) way to do it, using standard objects in a sneaky way. It’s not perfect, and it has some limitations, but it will get you close to your objective until the Squirrel developers have time to add it to their ‘to-do” list.

Have fun and enjoy!

THE ILLUSION OF DRAG AND DROP

Rob

Tips & Tricks for Squirrel Developers

If you are new to Squirrel (the next-best software since Business Objects), you will know how easy it is to use. However, Squirrel really comes to life with a combination of structured thinking and a good dose of visual creativity!

As a previous Business object developer for over 7 years, I often had great ideas but spent a lot of time figuring out how to ( read: manipulating the standard objects) create the output I wanted. Having a community that shared ideas was really helpful, and I hope to be of help to those starting out.

The good news is generally there is always a way to create what you want, so don’t give up. Squirrel is a new product, so it will keep growing in terms of functionality, but even with the current objects you have extensive possibility to explore becuuse almost every aspect of the objects are variable.

In this video, you’ll see how easy it is to build ‘creative counters‘.

Enjoy.

Rob

3 steps to maximising employee engagement through analytics

Written by Rob Scott for InsideHR on November 25, 2019

HR professionals and data analysts should work closely together in developing employee engagement programmes in order to drive stronger and more sustainable outcomes, writes Rob Scott

We all know that data analytics and employee engagement are two of the hottest topics of discussion among HR and business leaders. And for good reason. Many organisations are transforming operations into digitally-enabled businesses, which is ushering in significant changes to the way we work, how we remain an attractive employer, and how we keep the workforce engaged, motivated and productive.

There is also a growing acceptance that the so-called ‘soft-science’ label associated with human behaviour and the accompanying mystique of psychology are no longer valid reasons to dismiss the powerful role data and analytics play in improving people-related decision-making.

When used appropriately to understand business problems and expose opportunities in HR, analytics enhance trust, allow executive teams to position HR functions strategically and builds credibility and fact-based support for programmes such as employee engagement.

In many of my client interactions, analytics is an afterthought for employee engagement custodians. It’s often seen as a simple means to report their programme’s progress, and success or failure is often based on simple point-in-time survey results.

“Rather than guessing, your data analyst can work with you to determine the most effective length of time for your engagement interventions”

But in many respects, this is short-sighted. The data analyst should be part of the conceptual planning, because data outcomes can inform and shape the design of the employee engagement initiatives and help facilitate its continuous improvement. Your data analyst can credibly test outcomes on existing HR datasets or run pre-design trials to determine the best options or recommend changes or tweaks to an existing programme based on analytical results.

For example, how would you develop or modify your engagement programme if you knew the following:

• The effectiveness of most engagement programmes is generally marginal
• That engagement effectiveness decreases over time
• Your intervention method impacts success, and
• The length of the intervention is critical

These are findings from recent investigations by the University of Timişoara, Romania and offer some important guidance and examples for both design of the engagement programme and key points of measurement and analytical assessment.

For example, rather than guessing, your data analyst can work with you to determine the most effective length of time for your engagement interventions. There are constant battles in most companies fighting for an employee’s attention. A two-week engagement programme may be far more successful that one that runs over six months.

“Analysts can help you figure out which soft skills are the best intervention method to apply within the programme to give you maximum effect”

Analysts can figure out how many ‘nudges’ or ‘refreshers/reminder sessions’ are best in your work environment to mitigate the ‘decrease of effectiveness over time’ risk. If you knew without reminders, the engagement effects all but disappear after three months, you could build in appropriate actions, tests and measures.

Analysts can help you figure out which soft skills are the best intervention method to apply within the programme to give you maximum effect. This could be pre-tested and analysed based on existing LMS (learning management system), training and performance management datasets.

Using analytics appropriately in HR is critical and we need to get comfortable applying it in order to remain effective in our HR leadership roles. Al Adamsen, a global people analytics thought leader has this great saying: “Effective analytics is like a great football player, they don’t run to the ball, they run to where the ball is going to be”. That’s how we need to see the value of data.

3 steps to maximising employee engagement through analytics

1. Engage your analytics team or service early in employee engagement programme design. Their input is likely to change how you develop the interventions.
2. As an HR leader, building the right level of understanding of analytics and its application. This is an HR leadership risk mitigation factor.
3. Using people analytics appropriately, empowers HR and managers, builds credibility and trust through evidence, without having to lose your human-centric style

Hitching a Ride on AI

As humans, we’re not too keen to be knocked off the top rung of the proverbial intelligence ladder – that all-powerful position we collectively hold which allows us to make the rules!

But as we look down upon our underlings, there is a growing sense of uncertainty that a species of Artificial Intelligence (AI) is gaining momentum, and in due course will launch an attack for the primary position. And if this happens, what will become of us, and will we cope with being second-in-charge?

Of course i’m being a little dramatic in sketching a future scenario, but let’s not underestimate the speed at which Artificial Intelligence is moving towards Artificial General Intelligence (AGI). Just recently the Allan Institute announced one of its robots had completed and passed a Grade 8 science exam set for human students, scoring a remarkable 90%. This only took 4 years to get right, and with exponential growth in computing power, quantum computing advancement and AI capabilities, we would be naive to think highly capable AI is decades away.

But we don’t need to panic, we need to be clever. Thinking outside the box, creativity and innovation are core strengths of humans – we need to see AI differently. Not as something to fight against but to augment our own intelligence with.

AI can also stand for Augmented Intelligence

There are three key reasons why we need to augment our own intellectual capability:

• The speed of DNA (biological) evolution is too slow. Very little has changed in our DNA for the last 10 000 years. We can’t rely on natural evolution to retain our top spot.
• Human progress comes from learning, but the volume and speed of new material creation far exceeds our collective ability to consume, digest, review, examine, hypothesis and research. We need help!
• AI and machine learning has the capability to learn significantly faster than humans and is increasing this capability exponentially.

It’s critical that we ensure AI works for the benefit of human intellect improvement, not just human progress. We are already seeing significant advancements in Brain/Machine interfaces or Neuro-technology. There are some great examples in areas such as Neuro-prosthetics and Neuro-stimulation. These are blurring the lines between biological and technological improvements and is giving us a glimpse of our co-existence.

I’m not necessarily promoting implantable devices, I personally don’t fancy that, but there is exciting research taking place around non-invasive augmentation as well as neuro-plasticity that is showing how our brains can be adapted and used more productively intervention. I think this is an area of research that holds a lot of promise. If you are interested in some amazing stories around brain plasticity, I recommend you read “The Brain that can Change Itself” by Norman Doidge. We humans are nothing short of amazing!

I’m looking forward to keeping our spot on top of the ladder, I’m even more exciting that we have the opportunity to extend the ladder upwards and carry on climbing as a species, using our AI resources to achieve it.

Don’t trust AI? How to allay fears and build trust in AI tools

Originally written for Inside HR

AI is changing the way businesses operate, however, effective design and consumption frameworks need to be created and implemented in order to allay fears and build trust in AI tools.

You don’t have to venture too far into the realm of HR technology to discover the rapid growth of AI tools silently influencing decision making, providing newly discovered insights and simply making things easier to do. Whether this is analysing candidate facial expressions or voice tones during an interview, examining individual network and collaboration habits for leadership potential, monitoring employee fatigue signals or spotting who is likely to exit your company, AI is changing the way we operate.

But do we trust AI outcomes? And I mean the collective ‘we’, both HR professionals administering these tools as well as applicants and employees who are the AI subjects.

In July 2019, I ran a snap poll via LinkedIn to test general perceptions. Let me at the outset declare this would likely not pass academic requirements of a well-designed and administered survey, but LinkedIn is a global business-focused platform and the results provide a reasonable reflection of this cohort.

The initial question on trusting AI shows 61 per cent of respondents have partial to serious concerns trusting AI outcomes. A further 25 per cent of respondents registered complete or strong disagreement, and there was nobody who completely trusted AI outcomes.

Of course, one could argue that trust is like pregnancy, you can’t be half-pregnant, so if you don’t fully trust something, you essentially distrust it. We should, however, look past this binary perspective and understand that respondents are expressing their uncertainty towards something that is largely an unknown entity. People are concerned, but not necessarily against it.

As an HR or business professional, when 3 out of 5 people are not supportive of AI, it’s not something you should likely ignore. From an HR perspective, you could be losing good candidates and alienating top talent. There is plenty of newsworthy evidence about AI bias, AI decision failure and even fake AI results to warrant concern.

One of the fundamental criticisms of AI outcomes is the inability to explain the answer.

In the same poll, we asked respondents if they would trust AI outcomes more if the reasoning was visible. A whopping 92 per cent agreed or strongly agreed. While this is good news, the reality for most HR professionals is they will be unable to do this. Most HR tools using AI are commercial off-the-shelf products, producing commoditised AI answers. If it’s a true AI tool, it needs lots of data, more than you probably have of your own. The algorithms sit in a ‘black box’ and even if you could access the code, understanding how the answer is reached is complex.

“One could argue that trust is like pregnancy, you can’t be half-pregnant, so if you don’t fully trust something, you essentially distrust it”

This is why the third question in the survey – having an AI code of ethics, is so important. Close to 50 per cent of respondents scored at top scale on this question. There is a significant amount of good work evolving in this space. Many governments, technology giants and private companies are discussing and developing important principles. Some of the key focus areas include concepts such as ‘transparent AI’ and ‘white-box’ development which will increase credibility by allowing answers to be explained. Other areas are independent algorithm auditing, validated unbiased training data and developers using open-source methods and code.

AI will become a powerful solution to many of our business problems. But while it’s in its infancy, we need to build effective design and consumption frameworks in order to allay fear and build trust in these tools.

Key takeaways: HR and AI

• Three out of five people don’t trust AI outcomes. As HR professionals we need to look for ways to address applicants and employee concerns.
• Most AI tools used in the HR space are commercial off-the-shelf products. They may use some of your data, but the results are based on other data that you know little about.
• If you are using AI tools in HR, ensure you declare this to users and find ways to explain how the tools got to an answer
• In the future, applicants your suppliers and government agencies will ask you to show them your AI code of ethics. If you use AI, you should start working on this.

How complexity & simplicity come together in the art of future HR design

written for insideHR August 2019

Simplexity is an emerging theory that proposes a possible complementary relationship between complexity and simplicity, and it has important ramifications for HR professionals looking to improve both the mechanics and dynamics of the workplace, writes Rob Scott

Many organisations are moving towards a digitised work environment. And while there are many facets to this transformation agenda, the one overriding message from many human capital thought-leaders around the world is the need for increased simplicity. Reducing complexity in HR processes and activities is seen as an elixir for Josh Bersin’s overwhelmed employee who is suffering from low engagement and negative trending productivity levels.

But does the adoption of a simplicity mantra just mean problem-solving and innovating by making things more logical and easier? That would be nice, but it’s a little more complex than that, it’s what we call simplexity, a term which describes a complementary relationship between complexity and simplicity.

Firstly, why do we have complexity in our HR processes? Well, we don’t typically aim to build complex outcomes, but over time we make modifications, often in a reactionary way to ensure continuity, to align with new technology, include a process owner’s ‘great ideas’ or to rectify ‘minor’ problems.

In many respects we don’t notice the ‘complexity accumulation’, just as we don’t realise our own weight gain until we’re confronted with a Facebook ‘Memories’ notification of our slimmer-self three years earlier.

“Trying to resolve processes which have evolved into complex problems is likely to result in a confusing mess”

Over time organisations spend a lot of effort and money trying to patch and rectify problems we can’t really solve. But at least the problem temporarily disappears right? This may last for a while, but eventually we reach an infliction point, where we move beyond a point of ‘functional complexity’, in other words a level of complexity which is still acceptable, but not optimal. We all know what the ‘chaos zone’ feels like and we often react with statements like “How on earth did we land up like this?”.

When we attempt to resolve problems within the ‘chaos zone’, often using simple logic and keeping other inputs or outputs constant, we end up with a confusing mess. Ownership, involvement and role clarity in understanding the problem becomes blurred. Re-imagining is often the best way forward in these cases. Painful, but gets you back in the right zone.

What we really mean by simplicity is the end-user experience, not the back-end design. It’s a dichotomous situation, which is why we refer to it as “simplexity”.

It’s a reality that if we want our organisations and people to adapt, grow, be agile and leverage new technologies such as AI, automation and Blockchain, then complexity by definition will increase. However, if we want efficiency and improved people productivity, then complexity from an experience perspective must decrease.

2 steps to simplexity
So, what do you need to do to manage this contradiction?

“Organisations spend a lot of effort and money trying to patch and rectify problems we can’t really solve”

Firstly, accept that effective simplexity is a function of our understanding, not our personal desire to solve a problem or introduce something new. This means we should engage the right skills who recognise the subtleties and nature of the complexity and who can unpack the problem in ways which allow others to give appropriate input and direction. Including the right design-skills can ensure you build the bridge between complex creations and simple experiences.

Secondly, ensure you don’t land up in the ‘chaos zone’. Make sure you constantly evolve within the ‘functional complexity zone’ and purposelessly block any silent creep into the chaos zone. Actions such as process effectiveness alerts, engagement results and continuous improvement cultures can serve as ‘chaos zone’ mitigation solutions.

Bottom line – simplicity is an experience, not necessarily the design.

Simplexity in a nutshell

• While we all want process simplicity, it’s a reflection of the output or experience rather than the back-end design.
• Simplexity is a dichotomous term because it simultaneously requires the adoption of more complex tools such as AI in order to progress, but at the same time needs the end user experience to seem simple.
• Trying to resolve processes which have evolved into complex problems is likely to result in a confusing mess.
• Achieving simplexity is a function of our understanding. We need to step back from what we don’t know and introduce the appropriate skills.

9 Exciting Trends and Opportunities in HR for 2019

Grateful to  Orlando Imperatore : Flickr 2018

Toss away the crystal ball!  Of course there is no rational way to ‘predict’ what will be important for HR leaders and business execs in 2019. In almost every case, each organisation is on a unique journey of people transformation, technical empowerment, culture mind-shift or simple operational improvements.

So my list is a collection of stuff which I’ve happened to engaged HR and other leaders about in the last 12 months and which was being considered for future plans. Perhaps only 1 is of interest to you, maybe all 9 – It doesn’t really matter. 

Here we go! and in no particular order

1. PA – Personal Analytics 
   • HR Analytics has become an important tool for supporting organisational decision making around people. But it tends to support the employer more than the employee. As we see Employee Engagement, Happiness and changes in the Workforce and Workplace take center stage, there is a gaping hole around providing individuals with Personal Analytics in order for them to make better personal and business related decision within a continually fast-paced and constantly changing work environment.
2. Trust
   • As we see new technologies such as Chat-bots, Robotic Process Automation, Machine learning Algorithms, Personal data-sharing and Tracking cozying up next to  human workers, the trust relationship which underpins so many things in our organisations is being diluted. The need is not just about building trust in technologies which are performing ‘human-like’ tasks or gathering our data, but effectively managing the implications for functions such as HR who have custodianship over some of these new-age tools. 
3. Non-Exec Talent Coach 
   • Executive coaching is a mature offering, but as the nature of work and the variety of relationships between an organisation and a worker develop  ( I don’t want to say employee, because many are not technically that), the need for Independent Development Coaches at  lower levels, and which is not funded by the employer is being sought. Some of this demand exists because younger talented individuals do not want to mirror the behavior of current leaders (Think about many current Bank Leaders…. not a good model to follow), but want to become the best version of themselves without company influence.
4. Beyond Engagement
   •  I’ve never been a fan of culture or engagement surveys – statistically they are full of errors and often based on pop-psychology. However listening with ‘Data Ears’ is becoming more relevant. In other words understand the mood of the company, or Engagement levels (Customer or Employee) or Happiness levels by analyzing the data trail left by employees, customers, your supply chain seems far more reliable and less prone to typical survey inaccuracies. 
5. Personal Data Repository
   • One of my favorites. I’ve been engaging on this topic for a number of years. But with the changing workforce landscape, the growing contingent and gig enthronements, workers want the ability to store their own work history (think mini HR system), including Learning records, Pay and Benefit data, Performance scores, basic biographics, Job and Position history. They want control over their own data, and the ability to share it and withdraw it easily with an employer. This is not your typical Linkedin profile BTW. Big opportunity for HR Software vendors.
6. Communication
   • Not necessarily new, but becoming an area of focus again as organisations get lost if their digital and technology transformation activities. Humans are irrational, make mistakes and are not perfect. Technology, with all its benefits, has the ability to create sterile and perfect environments, which are not conducive to human productivity or happiness. Making sure we don’t capitulate our responsibility to communicate to machines/technology is important. 
7. The Science of HR 
   •  HR is actually a lot more complex that most people realize. Often the individual HR activities are not complex (some can be though), but ensuring there is alignment across a multitude of interrelated HR activities is where the real complexity lies, and where things often go wrong. Underpinning all HR decisions is the level of HR Maturity. When HR activities are not executed based on the Maturity level, you typically get Executive despondency towards HR or frustrated HR leadership. 
     
8. Instant answers to HR Tech
   • The fast-paced and continuously changing work environments are demanding HR and IT leaders make quick, but informed HR Technology buying decisions. Gone of the days that it takes 4-8 months to do a traditional RFP, only to discover the new SaaS tools you were considering have significantly changed. There are some great services, analysts and tools available to speed up these decisions.
9. HR Operating Model Change 
   • Many organisations are realizing the traditional Dave Ulrich HR operating model needs some adaptation. Not a radical change (as it is mostly still working), but a focus change to ensure the operating model can support ‘speed and agility’ needs of modern organisations. Changes include the ‘Business Partner’ reaching into the customer and supply chain world, the ‘Centre of Excellence’ (CoE) becoming a Networking Management Function and the ‘Shared Service Centre’ transforming into a Digital Data Centre.

That’s it!. And why not 10 I hear you ask, no reason, I only had 9 to share. Whats the point of making stuff up 🙂  

In Search of Imperfection

written for InsideHR

People leaders need to get the balance between technology, environments and human irrationality right in an increasingly digital world, writes Rob Scott, who explains that there are a number of considerations in optimising employee performance in the process

I recently attended a presentation by Alexander Kjerulf, the Chief Happiness Officer at Danish company Woohoo Inc. He makes the point that we very often, but incorrectly assume employees are happy at work when they have job satisfaction. According to Kjerulf, job satisfaction is what we “think” about our jobs, while happiness is what we “feel” about our jobs and work environment.

The employee performance conundrum
This was timely as I have been engaging with several leading-edge clients who are struggling to find appropriate ways of improving their employee performance and engagement levels. These companies have all the great benefits and perks such as free food, zone-out pods, wellness programs and gym membership which attract talent, they have tier-1 HR technology and collaboration tools, use and explore automation, robotics and AI to augment employee capability and remove humans from work which is done better by machines. Wow, everyone should be happy, satisfied and engaged. But they’re not.

Josh Bersin, a leading global HR technology analyst cites challenges with engagement, productivity and employee experience as one of four forces disrupting organisations today. In his presentation A Wild New World of HR Technology, he alludes to the lack of employee performance and productivity improvement, overwhelmed employees and marginal improvements in employee engagement despite all the great technology we continually introduce into our lives and workplaces.

“Wow, everyone should be happy, satisfied and engaged. But they’re not”

Why leaders need to empower people to improve employee performance
For several years, I’ve been driving the point that effective digital work environments are not about throwing more technology at people and problems. Unless you empower people to do more with the technology in a modified human behavioural way, you are likely to create the challenges Josh Bersin highlights.

Furthermore, as people leaders, it’s important that we figuratively step back to see the broader technical environments we are busy creating – not just from a software and apps perspective, but inclusive of the steel, concrete, glass, noise, space and technical gadgetry we combine to form our “happy” work environments.

Often these environments are created to serve rationality and optimisation but can unintentionally become “technology concentration camps” – an environment which is perfectly rational, but dreadfully unliveable.

In my view, we have become singularly focused on building environments and supporting processes using modern and emerging technical assets in order to attract, retain, engage and develop people. But we have overlooked the potential mismatch between these creations and the fact that people are not perfectly rational and don’t operate well in sterile, passionless environments.

Don’t misunderstand me, I’m a technology fan – it underpins our human desire to constantly progress and improve. However, we should realise as human beings, we are at our happiest when we can be irrational, make mistakes, share emotions, be spontaneous, indulge in passions, seek out the mysterious and have faith.

Allowing employees to be human
It was the French writer Ellul who said “The eighteenth and nineteenth centuries made an enormous error in misunderstanding this aspect of human nature and presumed to exorcise all that was not rational.”

“As human beings, we are at our happiest when we can be irrational, make mistakes, share emotions, be spontaneous, indulge in passions, seek out the mysterious and have faith”

As we evolve our digital work environments, shifting tasks to robotics and AI away from human jobs which we are not good at, are less accurate at, or are slow to do in comparison to technology, we will be left with a ‘perfectly optimised’ human worker, but perhaps not a happy or engaged one. The ‘perfect’ technology environment may be producing the opposite effects of employee performance, happiness, engagement and productivity.

Our challenge as people leaders is to get the balance between technology, our environments and human irrationality right – building the perfect ‘imperfect’ environment is the goal. Those that succeed will be the attractive organisations of the future, sought out by talented people.

3 key insights: employee performance in the digital world

• Our digital work environments are increasingly becoming optimised and rational, driven by technology. But when we put humans, who are not perfectly rational, into these environments, we are impacting engagement and happiness.
• We have an abundance of technology in our personal and work lives, yet evidence suggests that employee performance, human productivity and engagement has only marginally improved.
• Our desire to remain competitive organisations has necessitated leveraging modern technologies and shifting human tasks to machines and AI. Organisations who understand how to optimise, but at the same time not dehumanise will be the successful companies of the future.