that’s the whole blog 🙂
that’s the whole blog 🙂
Original article published by Inside HR Magazine (Feb 2016)
Given a digital workplace is undeniably the future we are rapidly heading towards, the skills any future employee will need to be effective and remain market-competitive is an important consideration for HR and talent managers. HR functions have had first-hand experience of resistance from executives to hand over strategic accountability, mainly because their business skills and acumen have been lacking.
The HR function is not immune to the disruption of modern technology; in fact, the advent of Cloud and SaaS technologies in the HR space is ahead of many other business functions. It’s an advantage that HR leaders should capitalise on to secure the relevance of the function in a digitally minded work environment.
Being digitally literate for HR is a prerequisite for the next wave of business transformation. So what are the competencies, knowledge areas and behaviours required to ensure HR professionals can deliver optimised future service? I have identified five focus areas, each of which houses a number of different subsets.
1. Computer and platform literacy
This competency area is often mistaken as the equivalent of digital literacy. Rather, this skill set is a predecessor of digital and includes understanding how desktop PCs, laptops, smartphones and tablets work. This includes how these systems are best consumed and how they connect, and managing software applications. For many, these are skills associated with IT specialists. These skills are no longer an IT domain but have become general business skills which form a fundamental base to foster digital innovation and creativity.
2. Data design and ethics
These two components may seem like distant cousins, but how and what data we collect and derive is both a powerful business opportunity as well as one that borders on intrusion, invasion of privacy and manipulation. This skill set involves an understanding of other disciplines such as marketing and finance, as well as how things such as graphics, video, Internet of Things (IoT) feeds and other non-transactional data are integrated and designed to produce evidence-based outcomes.
Analytic skills are closely aligned with data design and ethics. It’s far more than producing quality outputs, which is increasingly becoming a science in itself, and has a strong emphasis on ensuring the right information is being analysed and interpreted to inform business- and people-related decisions. Just as HR faced rebuke by becoming pseudo psychologists with off-the-shelf psychometric assessments, this skill set is embedded in formal data-science education.
4. Social intelligence
Social tools are ubiquitous and increasingly straddle our private and work lives. Understanding how search, content and social media work together requires technical understanding such as SEO as well as strategic alignment and tactical execution skills. Creating, observing and responding activities are reliant on a creative mindset, communication, writing and PR skills.
5. Innovative mindset
SaaS solutions as well as hardware are continuously being updated and improved, to the extent that new features are being “dropped” by the vendors every few months. Ignoring new features and capabilities for extended time periods is not a good strategy; rather, HR should embrace an agile and continuous improvement approach to its operating model. Skills relevant to support innovation include novel, critical & adaptive thinking, problem solving and design concepts.
Most seasoned HR professionals won’t fall into the “digital native” category, meaning that many of these concepts will be foreign and confronting. However, upskilling and introducing new competencies into the HR function will ensure digital transformation initiatives are executed with insight and purpose.
The scope of digital HR literacy
Latest article published in InsideHR
Very few HR and talent professionals would refute the value that technology has brought to their operations. HR functions have leveraged these tools to become efficient, effective, collaborative, engaging and more accurate. But would HR professionals be as enthusiastic about HR technologies if they contained Artificial Intelligence (AI) capability that could predict more accurately and make better business decisions than the highly educated, people-focused HR practitioner?
At what point does software that is able to pick the best applicant, predict who is most likely to resign or identify the best mentor for a talented employee, become a legitimate replacement for a highly paid HR practitioner?
Most HR professionals I engage with don’t believe this will transpire, citing the complexities of human behaviour, personal choice and the absence of universal logic in managing people in the workplace. In the short term I agree with them, but not for the same reasons they mention. In fact, when I look at how most HR functions rely on standard processes to manage certain events, I have no doubt that near-future HR technology will do a better job than humans in executing these rule-based processes. Our flawed minds can never achieve the same level of efficiency.
“AI in HR is maturing; we are seeing interesting algorithm designs, predictive analytics and automation solutions coming to market”
This is not to say that our current HR technologies are anywhere close to being artificially intelligent. Right now there is a lot of hype-spinning by software vendors about the predictive prowess of their tools, but in reality these are immature tools. We should, however, be under no illusion that sophisticated AI for HR is heading our way. As it becomes more credible and capable, it will displace employees who are focused on maintaining standardised HR processes and mundane transactional work. There is, however, a far deeper and fundamental reason why I believe AI will, in the short term, find a home as a digital assistant rather than as a replacement for HR professionals. It goes to the heart of a human emotion – fear. Having artificially intelligent machines making sophisticated and important people-based decisions feels threatening and generates a level of anxiety about our status as human beings. We are not ready to lose our “superiority” to machines, no matter how intelligent they become.
As an example, Microsoft recently released a small tool which guessed one’s age based on a picture you uploaded. The results were mostly wrong, however, the tool went viral. Why? The reasons lie in the notion that while the technology is inaccurate, we feel less threatened by it and are able to maintain our dignity and humanness.
This is a powerful lesson and opportunity for HR software developers. Building AI software that is too accurate and human-like is likely to be rejected or underutilised, not because its outcomes are incorrect, but because it pushes human beings down the proverbial pecking order of importance and insinuates that the work they are doing is demeaning and unnecessary.
“Building AI software that is too accurate and human-like is likely to be rejected or underutilised”
Of course, we shouldn’t forget that technology enhancements have been at the heart of mankind’s industrial revolutions and progress. New machines with capabilities that outshine human ability have typically been met with resistance from those affected, at least until new work opportunities borne from the new technology become evident. AI in HR is maturing; we are seeing interesting algorithm designs, predictive analytics and automation solutions coming to market, but future job clarity in a digital and AI age is still blurry. Until then, AI tools for HR will develop into great digital assistants under control of HR professionals. At least for now the role of the HR professional remains in demand.
5 key takeways for HR
Image source: iStock
It isn’t a new idea that computers, mobile phones, websites and wearable technologies can be built in ways which influence your behaviour or causes you to think in a new way over time. While one could argue that this is akin to brainwashing, when used appropriately it can be very beneficial to end users as well as system owners. Just think how your smart-phone or Fitbit health band has altered your behaviour without you realizing it.
The idea of “persuasive computing” was first coined around 1990 by Standford University researcher Dr BJ Fogg. Much of his current work centres on teaching technology developers the psychology of behavioural change, and how to facilitate behaviour change via their technologies. Hello, isn’t this what HR people are supposed to be good at given that Psychology is the foundation of most HR professionals education? It begs the question as to why HR software vendors have not built their solutions with more “persuasive computing” thinking which could motivate end users to behave in a way that would benefit themself, HR and the organization.
Most HRIS vendors have developed visual dashboards, alerts and many use gamification techniques to encourage end users to do things, but in my view these are largely fear based design principles rather than motivational ones. These vendors are wedded to the “principle of standardization” ~ that a system process should be applied consistently to all users irrespective of their current habits, behaviours or motivation level. We need HR software that takes an individual’s current state as a base-line and uniquely “shapes” the HR software to suit that user. In the process of “shaping”, the end user is more likely to react in a particular way, do things suitable to their current state of behaviour & motivation level all while providing HR with a platform to influencing future behaviour of that individual.
BJ Fogg makes a great point that we cannot do complex things when our motivation level is low. Likewise we have windows of opportunity to do hard and complex things when our motivation level is high. SaaS HR tools in particular gather a lot of important Meta data that could quite easily be used to measure a users’ current state of motivation or other states of mind. When a users motivation is low for example, the HR system should “reshape” to encourage easy activities, while taking advantage of times when the end user has high motivation to get more difficult and perhaps more things done, while at the same time facilitating behaviour change so that these hard tasks become easy over time and can be done when motivation is at a lower level.
As HR people, our goal must be to think outside our rigid and standardisation boxes. To much of what HR achieves in our organizations are “feats of compliance” rather than value adding benefits. This is because we are standardisation-centric rather than employee centric. I would much rather a line manager do HR tasks that he or she is motivated to do, which add real business value and develop correct habits which facilitate personal growth in effective people management than forcing a person to comply to something because “HR says so!” – technology can help us achieve this.
There’s a greater role for HR software than simple process and transactional efficiency. For a tool that has so many components linked to people behaviour, we need vendors who understand persuasion and behaviour change though technology to come to the party.
You wouldn’t be wrong if the first words that sprung to mind as you read the title were “analytics” or “big data”, as they represent two of the three main components that drive HR system intelligence. Big data is really just a term that represents the massive amounts of information we create and collect in a myriad of digital systems such as email, collaboration tools, HR transactional, talent and payroll systems as well as our online social media activity using tools like LinkedIn, Twitter, Facebook and others.
Nobody really knows exactly how much data we collectively create. Whatever the volume or source, it’s really irrelevant, save to say that every individual in the workplace is creating a significant amount of data on a daily basis that could be extremely useful and valuable in the delivery of business- and people-related goals.
The data, however, is largely meaningless unless we firstly recognise what it is, know what value it will offer our organisations, and are able to apply analytical robustness in a creative and strategic manner to the raw data. Many will be familiar with the movie Moneyball, which highlights the power of using data and analytics to make business decisions regarding sportsmen. It’s now pretty common for top sports teams to measure a specific series of data points for each of their team members. They do this to ensure they invest in the right players from a hiring perspective, through to performance optimisation, risk (injury) management and termination.
This brings me to the third component which drives HR system intelligence – the human factor. While modern HR systems can be set up to provide historic, trending and predictive answers in a quick and consistent way, it takes people to ask the right questions, apply rigorous and causal measurement standards and to interpret the results correctly. System intelligence is far more than a set of logical technology sequences with a sexy user interface; it is a reflection of how the human aspect is applied to data interrogation.
What Moneyball also underscores is the need for absolute focus, commitment and trust in the analysed data. The real-life success of the Oakland Athletics baseball team, which the movie is based around, would not have happened if the right person, who loved and understood the data, was not part of the equation. This is important for HR functional and technology leaders to understand – HR analytics is not an activity you can simply add into your HR generalist’s job description. It’s a contributing factor to why HR departments have not been overly successful with their foray into the world of data analytics.
It’s good to see many HR system vendors actively embracing analytics directly in their HR software. Some provide fairly basic historic and trend analysis through online graphical reporting. Others are providing instant or embedded analytics that display results in a dashboard or by simply hovering your mouse pointer over an icon. More recently, we’re seeing diverse data and complex analysis engines being integrated into HR systems. These offer statistically valid predictions related to employee risk such as likelihood of resignation, best career move and ways to improve engagement.
The provision of complex analytic functionality by HR vendors is important; however, the HR system will not appear intelligent without the right human interest, creativity and skill. As tough as this may sound, your HR system’s perceived intelligence is a reflection of your HR leaderships’ views of data and analytics rather than the system-specific functionality. As we edge towards a completely digital work environment, HR leaders must address their role in future decision making through data intelligence.
HR system intelligence & HR implications
Rob Scott is global lead: HR strategy & innovation for Presence of IT, a leading consultancy in HR, talent, payroll and workforce management solutions.
Most of the time, if you ask any HR leader to explain how HR technology is contributing to the achievement of business goals you get a somewhat perplexed expression, supported by an eloquent explanation which suggests it’s being conveniently ignored because it’s too difficult or not practical. Alternatively they reference the vendors marketing rhetoric which promise share-price improvements that would get Warren Buffett excited!
It’s moving out of the administrative and transactional mould that has defined it for decades, and whilst the transition is often very slow and painful to watch, there are many organisations whose executives are maturing in their understanding of the unique value that HR functions can offer, and their direct contribution to business goals and strategy achievement. HR professionals can’t hide behind the mystique of psychology anymore; they need to show direct linkage from what they do and the outcomes it creates, including the role of HR Technology.
HR leaders are far more business savvy too, they will rattle off their business goals, they are succinct in articulating the meaning of value for their organisations, they understand cost, growth, quality and risk drivers, and they are familiar with industry and global issues, opportunities and constraints. So what’s the problem – why are so many HR leaders resistant to show how the performance of HR Technology has or could advance the business objectives and strategies?
Some of the answer to this question may lie in previous bad experiences with “template” measurement frameworks such as the Balanced Scorecard. These tools are often introduced as off-the-shelf “best practice” which generally lead to disappointing outcomes. It’s the one reason that I loathe HRM software vendors pushing a “best practice” mantra. HR leaders wrongly believe the hard work related to measuring their HR Tech value contribution has been done for them. It can never be true – your objectives, environment and how you want to achieve your business outcomes using HR Technology are absolutely unique. You need to do the hard, detailed work yourself.
Another reason is simply lack of know-how and practice. Most HR professionals have a social science background which engenders greater qualitative rather than quantitative focus. That’s not an excuse of course, learning how to build a causal-effect model which shows where HR Technology is leveraged, is not difficult~ it just takes some practice and adherence to some basic principles such as:
By way of a simplified graphical example, I recently had the opportunity to help a client think through a cause-effect model for “Innovation” – one of their strategic business objectives. The HR director wanted to explain how their HR technology was directly contributing and supporting this objective. When we finished the model, it became very easy to explain how this would be achieved. A key learning for the client was to link the HR Technology to “drivers” rather than the performance areas.
I’ll point out again that proving the “cause-effect” (performance areas in graphic below) is critical to establishing credibility. For example, my client had to validate that “Empathy for client’s needs” really did cause “Enthusiasm & Engagement” in their environment. Once that was established the drivers for performance were identified and agreed, and HR was able to determine which HR Technology was required and how it would be used to deliver measurable outcomes.
Of course there is a lot more work and involvement from other business functions behind this simple graphic, but hopefully it’s apparent that with some careful thought and focus, the real value of HR Technology can be measured and explained. Your next business case for HR Technology funding should be much easier to achieve if you have this in place!