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  • 16 Jan 2020 5:42 PM | Anonymous member (Administrator)

    In his second look at diversity issues, Eric Shepherd reveals how you can make a more diverse work environment work for everybody

    The case for workplace diversity is compelling. Organizations that encourage a more diverse workforce enjoy higher employee retention rates, innovation, and profitability. No wonder forward-looking organizations that embrace diversity with genuine enthusiasm.

    Sadly, it is one of those goals which is easier than it sounds. Recruiting a diverse workforce representing various ethnicities and worldviews sets the stage for developing a competitive edge. The secret is to get people from disparate backgrounds to work together efficiently. Diversity and inclusion is a balancing act, where respect for diversity and embracing inclusion are equally important.


    Organizations may find it takes time and effort to create a diverse culture where people are motivated to give their best. Right from initial recruitment and induction, business leaders may benefit by setting the tone that inclusiveness is a core value. With digital technology transforming the landscape, the HR function has to champion designing resources and processes to promote diversity and inclusion.

    Organizations are broadly aware that diversity has to be prioritized at the very outset by designing recruitment processes that produce objective results. To do this, organizations must eliminate bias from job descriptions and create a fairer interview experience. These would be useful steps towards implementing diversity by keeping pace with expectations. Once a diverse team is in place, they can acknowledge that every workplace situation comes with its own challenges. In a fast-paced world, the decision to work across cultures and borders only magnifies these challenges.

    Opportunities bring challenges. It would be worth considering some of the common issues facing a diverse workforce and how best to deal with them:


    • Empower voices: Colleagues from different cultures can be hesitant in voicing opinions. Some cultures are more hierarchical than others. Individuals from these cultures might not feel comfortable speaking up in front of their supervisors without being asked. On the other hand, staff from countries, where flatter hierarchical structures are the norm, might be comparatively more outspoken. By providing safe surroundings that empower all team members to weigh in will pay real dividends.
    • Confront negative stereotyping by discouraging non-diverse silos. Negative stereotyping may instigate prejudice, and make some employees disinclined to work with colleagues from certain cultures. This is a double whammy, lowering both morale and productivity. To prevent colleagues from different backgrounds working in silos, activities that promote team integration should be encouraged. For example, a major airline chose to address the negative stereotypes that more mature employees held about their younger colleagues. A task force was established to embark on a reverse mentoring program that promoted intergenerational alliances.

    • Don’t get lost in translation. Greater diversity means there is a greater risk of messages between multicultural staff getting lost in translation. Apart from language barriers, multiracial colleagues may have widely different accents. Body language and non-verbal communication can also be an essential part of the message but can be easily misinterpreted or missed completely. Gestures and greetings that may be considered normal in one culture could be deemed offensive to others. Organizations can arrange for employees to be familiarized with these aspects in advance using communication aids such as infographics or videos.
    • Accommodate religious needs and cultural holidays. Accommodating a culturally diverse workforce might pose additional business and logistical costs. But that need not always be the case because there are cost-effective ways of making the workplace more welcoming. Existing space can be converted into a meditation or prayer room for employees belonging to different faiths. Cultural holidays can be marked with a symbolic observance or even more flexibility with time off granted for faith observance.


    • Respect formality differences, styles and values. Working styles that vary across different cultures can compound differences. Sometimes different values can be compounded by the different degrees of formality that is expected. Divergent expectations around dealing with conflict, confrontation, and the number of hours worked can all become issues. How much group consensus is valued over independent individual contributions also depends on the individual’s values in play. To avoid misunderstandings, organizations can devise an enriching professional atmosphere with cultural sensitivity exercises. This can be formally incorporated into employee training programs.

    To understand and collaborate with people from different backgrounds, we need to prioritize diversity and inclusion as a top-to-bottom strategy. If an organization is serious about this goal, it will provide training on unconscious bias which will improve engagement. Unconscious bias is a difficult-to-deal-with pre-conceived notion that can interfere with impartial decision-making. When these notions are understood, they can be examined critically so that inclusive behaviors can be adopted. Training has been proved to be especially successful when coupled with action-oriented approaches.

    A prime example of an action-oriented item is fostering inclusion during meetings. Our technology-driven world has made it simpler to reach out across the globe and time zones. Remote employees in distant time zones can be accommodated by alternating meeting times to accommodate their normal working hours. If there are employees who speak English as a second language schedule to attend a meeting they could be provided with meeting materials beforehand to allow for review before the meeting.

    Leaders and managers can champion diversity and inclusion by making sure that workers feel safe about expressing their concerns. Employees should learn and be held responsible for results by linking goals related to integration into their appraisals. Concerns of underrepresented groups can be identified through an anonymous online survey.

    The best way to start diversity and inclusion initiatives is to benchmark current values and beliefs before investing in changing them. Dealing with the challenges and opportunities offered by a diverse workforce cannot always be a linear process.

  • 12 Jan 2020 9:33 AM | Anonymous member (Administrator)

    Few would dare to argue against the view that diversity in the workplace is a good thing. But if you were in any doubt, Eric Shepherd gives you eight reasons why your organization needs to take the subject seriously.


    Advances in technology have revolutionized how we work and interact. Conferencing tools enable us to work with colleagues, customers, and vendors all over the world without ever leaving our office. Demographic shifts have made teamwork increasingly multicultural. Research by the consulting firm McKinsey found correlations between financial performance and diversity in teams. That is why cultivating a diverse employee base is essential. It allows organizations to reflect their market and evolve ideas to cater to our changing world.

    A diverse workplace defined


    Before we discuss the real benefits, it is worth defining what we mean by diversity. In its simplest terms, it refers to those characteristics that set us apart. These traits range from the apparent to the less visible. They include our ethnicity, gender, age, education, and capabilities. Diversity is not an end in itself, but a means of creating an environment where everyone can feel respected and involved regardless of their differences. Although diversity and inclusion have become buzzwords in the Boardroom, they are more than just a fad. They have tangible advantages that can help organizations overtake their competitors and become more profitable.

    Most job seekers prioritize salary package, career progression, and work-life balance. But increasingly job seekers and employees look to associate with an employer who values diversity and inclusion. They, like employers, know that it will have a positive impact on their careers.

    Benefits of Diversity


    Employers who actively promote diversity and inclusion seem to stay ahead of market trends and technological change. They empower their employees to follow suit by offering them an inspiring workplace. Let's take a closer look at the benefits that flow in this new world of work:

    1. Employees hailing from different backgrounds bring a wider range of experiences and perceptions to the table. And when a more comprehensive range of views are considered and adopted, the chances that they will reflect shifting client needs are brighter. Teams of broadly diverse employees are more likely to capture a new market.
    2. Diversity promotes creativity by allowing different perspectives to fuse together. Individuals with varying views on a single issue will create a melting pot of new ideas. This opens the door to innovation and greater originality in the execution of organizational strategies.
    3. Employees from different age groups can create a win-win scenario. Fresh graduates can be paired with more mature colleagues to make them conversant with new technology. In turn, the younger groups can learn the ropes from their older co-workers and their accumulated wealth of experience.
    4. A more diverse workforce tends to display faster problem-solving abilities than their cognitively similar counterparts. Studies suggest that people holding distinctive views not only come up with inventive solutions but also arrive at decisions faster. Diverse teams outperform individuals and make better and more informed decisions.
    5. Diversity is more likely to lead to higher profits. By not restricting their hiring to a particular group of people, employers gain access to a broader range of talented and qualified candidates. This translates into a real advantage that drives improved KPIs.
    6. Effective diversity and inclusion policies cause employees to feel more engaged. Engaged employees are more likely to align their agenda with the organization's vision. This can reduce turnover rates as employees experience greater satisfaction and empathy with their organization.
    7. Workplace diversity appeals to top talent. High-caliber employees already understand the benefits of stimulating teams. Alongside raising the organization's status as a socially responsible enterprise, it can create opportunities for new partnerships.
    8. Employees who work for organizations that are respectful of diversity develop and use their soft skills. Frequent exposure to different ideas and opinions helps refine interpersonal skills and instills a sense of curiosity. Individuals that adapt to divergent ways of thinking can be encouraged to learn new expertise from colleagues. This facilitates the transfer of knowledge throughout the organization.

    For organizations to remain competitive in a globalized economy, it is no longer viable to recruit only those who can relate to a particular way of thinking, culture, geography, or market segment. Organizations will miss out on many insights and worldviews that could help them connect with a varied customer base. But, if diversity is present in a group, a creative tension arises from the different perspectives at play resulting in better problem-solving.


    To keep pace with changes, organizations will need more creativity in their teams. Our future will require that we use technology that is yet to be invented. Works need to constantly up-skill to remain relevant and flourish. By putting together global teams that encompass diverse talents, growth mindsets, and professional experiences, organizations will develop employee pools that can transcend borders and enhance performance.

    A recent survey found that over half of American workers are anxious that automation might take their jobs instead of creating new ones. In reality, it is not jobs that are being replaced but monotonous and mundane tasks. Future jobs will be more absorbing, nuanced, team-based, and internationally oriented than previously. As artificial intelligence becomes more pervasive, there will be a greater need for people with diversified skill sets and, thus, more diverse backgrounds. It is up to business leaders to ensure that they have a diverse set of employees that can take on this new world of work.

  • 6 Jan 2020 6:56 AM | Anonymous member (Administrator)

    Predicting the future is a popular, especially at the start of the year. But how do we know which predictions might come true? And how can we get better at it? Eric Shepherd looks into his crystal ball.


    "Prediction is very difficult, especially if it's about the future!" said Niels Bohr, the Nobel laureate in Physics and father of the atomic model, and social scientists seemed to agree. As if to prove Bohr's point, the eminent physicist Stephen Hawking admitted in later years that some of his early predictions about the universe were not entirely correct.

    Despite the difficulties inherent in planning for the future, humans are the only species on the planet that make deliberate long-term plans. We’re strongly motivated by the desire to contain the risks that we associate with the uncertainties of future events.


    The impetus to enhance our ability to make reasonably accurate predictions is massive. Businesses operating in volatile economic environments are eager to anticipate changing customer tastes or technological breakthroughs. Likewise, governments have much to gain if their estimations about the repercussions of political alliances can be understood.

    One of the biggest hurdles to overcome for anyone in the prediction game is to overcome our cognitive biases, be they conscious or unconscious. But we can train ourselves to think more rationally while attempting to predict the future. Today, we have many more scientific tools at our disposal now than previous generations ever did. The accuracy of insights derived from reliable data is considered far superior to those arrived at through subjective methods.

    Researchers at Ivy League universities have devoted considerable time and effort to this challenge. In a prominent study aimed at improving geopolitical forecasting, they recruited experts from various fields. Sadly, they discovered that the predictions made by these forecasters, over several years, were only marginally better than chance and worse than even basic analytical algorithms.

    The research did, however, lend credence to the argument that a richer set of inputs yields better results. Individuals who took several viewpoints into account appeared to make better predictions than those who stuck to a single perspective. This is a clear call for decision-makers to pay heed to diverse voices that can prove valuable in avoiding blind spots.

    After scrutinizing hundreds of thousands of forecasts on events of worldwide significance by educated participants, the researchers generated some key takeaways. They concluded that if the underlying factors mentioned here are given due importance, then making predictions need not be a random process.

    Being smart helps


    The research participants with particularly high aptitudes displayed a tendency to be more precise in their predictions. However, raw brainpower seemed to provide a significant advantage at the early stages of the investigation. As the novelty of partaking in a new exercise wore off, higher intelligence levels seemed to matter less than before.

    Specialized knowledge benefits

    Possessing specialized expertise in a particular discipline seems to improve the odds of making accurate projections. While initial research did not point to a direct correlation, specialized capabilities in a specific field do appear to have a positive effect on prediction results.

    Practice makes perfect


    It takes a certain amount of practice to excel at anything. Prediction abilities are no different. It is worth noting that 'superstar' forecasters, who came up with predictions that turned out to be mostly right, became that way over time.

    Teaming up works!


    Sharing information among team members rendered better accuracy. This was determined by placing forecasters in a group or asked to make individual predictions by themselves. A Forbes article claims that when recruits were placed in groups for forecasting, they outperformed individuals doing the same task.

    Talented individuals thrive together

    The quality of predictions was found by researchers to improve when ordinary participants were placed in teams. However, over time, the polarization in this group increased as members displayed an unwillingness to collaborate. On the other hand, the team of 'superstar' forecasters appeared to work well in unison with each other.


    Flexible mind-sets improve predictions

    Researchers also observed that people with the ability to look beyond their personal prejudices showed higher accuracy in their predictions. In contrast, individuals with rigid thinking displayed poorer performance. While authorities on human psychology consider these characteristics to be in-built, being able to keep an open mind primarily depends on the circumstances.

    Training avoids reasoning errors


    Even experts can miss the mark by a wide margin when predicting the future. This is because of the very human propensity to overstate just how different the future will look from the present. The good news is that we can be trained to consider alternate scenarios and avoid common biases and errors in thinking. In studies, forecasters who received probability training, on the statistics of past cases, achieved better results than those who don't.

    Haste lays predictions to waste

    Participants, who invested more time in reflecting before articulating their predictions, produced fairer outcomes. Abilities improved further when these individuals were placed within a synergistic group.

    Revisit beliefs to strengthen forecasts

    The participants who came up with the best predictions were those who possessed the intellectual humility to alter them when new information was offered. They updated their suppositions based on fresh evidence and had to make fewer course corrections going forward.

    Conclusions

    These findings bring us to an exciting frontier where we can realize how to get better at forecasting by taking genuine stock of our abilities and shortcomings. A central challenge encountered by researchers was that, despite being trained in probabilistic reasoning, the predictions people made were no better than those generated by algorithms. This led researchers to suggest that reliance on statistical models is a viable method of refining predictions.

    But in an era where many human functions have already been taken over by technology, a balance must be struck between humans and machines. Computers are not currently able to exercise the kind of judgment that individuals can. But surely, we are capable of fostering aggregation algorithms that can distill collective human wisdom. In due course, an optimal combination of data and brainpower will yield more than just the sum of its parts.

    Now, for our 2020 predictions, all we need is an algorithm to make that combination a reality. Or a new crystal ball.

  • 12 Dec 2019 4:51 PM | Anonymous member (Administrator)

    A trawl through Google reveals many messages warning us that robots are set to wipe out the human race. Eric Shepherd explains what's here, what's coming and the benefits for us. 


    It seems we are both suspicious and scared of what we imagine they may become. Never mind of the contributions of robotics already. Their abilities to diffuse bombs. Or the robot’s use in farming to increase crop yields. Or even their use in pharmacies improving on the accuracy of medical prescriptions. It’s therefore probably time to redress the balance and take a more realistic vision of what robotics can accomplish. Especially now that robots have landed in the workplace.

    Over the next few years, robots will expand their skill sets, revealing impressive performance and retention rates, and moving up the ladder. More than just machines, working diligently to manufacture devices, vehicles, and machines, now robots come in all shapes and sizes. Here is a sample of robot types that we'll be discussing here:

    • Collaborative Industrial Robots (Cobots) that work alongside humans
    • Warehouse robots operate autonomously to pick and pack goods for shipment
    • In-store robots to provide information and a seamless checkout experience
    • Chatbots are systems that can engage in text or verbal conversations
    • Robotic Process Automation (RPA) that provides
    • Industrial robots that work autonomously to manufacture goods

    Let's take a real look at how these robots are being deployed.

    Collaborative Industrial Bots (Cobots)

    Cobots are the latest model of robotic technologies that work alongside humans. The concept of collaboration is operating with people to create something. Tradition robots worked autonomously and in isolation relieving any safety concerns. Cobots collaborate with employees rather than as a substitute for them.

    Cobots are industrial robots according to the definition of The Industry Federation of Robotics. Although cobots may be the future workforce, they only represent a small part of the annual revenue of industrial robots every year. The number of deployed units is still minimal, with only 3.24% share. In 2018, total industrial robots installed were 42,000, and out of them only 14, 000 were cobots, and in 2017, only 11,100 cobots were installed.

    Warehouse Bots


    Many machines can now move around the warehouse autonomously. In 2016, the warehouse robotics industry was estimated at $2.28 billion. It is expected to increase at a CAGR of 11.8%, hitting around $6 billion in the value by 2022.

    Amazon contracted $775 million for the Kiva Systems in 2012, and after 6 years, 45,000 Kiva robots were installed at the fulfillment centers. During the Christmas season, these robots processed 306 items per second.

    Now several other stores are using these robots. Clothing Company Gap is using Kindred robots for processing, packing, and shipping the products.

    The main task is to make these robots available to other companies. The warehouse robots are inexpensive, easy to install, and will help the smaller companies to expand their business.

    Delivery Bots


    We will be seeing autonomous robots on the roads delivering packages in the upcoming years. Some organizations have been using them for home deliveries, but they are not yet in widespread use.

    Domino's Pizza has introduced its Robotic unit. It is the very first robot for home delivery and looks like a combination of R2-D2 and the overweight oven. Four-wheeled, 3-ft high robots have been launched in 10 countries, including Germany, France, and New Zealand. Domino's Robotic Unit (DRU) uses several sensors for navigation and temperature maintenance. It maintains the temperature for both cold and hot food efficiently.

    Starship Technologies have already a home delivery robot, and the company has confirmed its program to deploy thousands of its six-wheeled delivery robots. The robot contains GPS and camera, but the upcoming models will have also have speakers, microphones, and they will be able to communicate with clients. Starship has already delivered 50,000 robots in 100 countries.

    American company Kroger has been using the self-driving car to carry the cargo in Huston. A famous engineer of Google Jiajun Zhu, who founded Nuro, has developed this delivery robot. It can carry 12 bags of groceries. The new version of this delivery robot will carry 20 bags of groceries.

    Amazon tested its Prime Air delivery drones secretly in 2016 and announced to build the drones, which can fly up to 15 miles, and it can deliver the packages in just 30 minutes. Soon after that, 7-Eleven, Walmart, Alibaba, and Google have also started working on delivery drones.

    Head of the Federal Aviation Authority's drone integration department has said that they are working on drone deliveries and very soon will start the operations soon.

    In-Store Bots


    Apart from home delivery and warehousing, other robotic opportunities integrate artificial intelligence to enhance the efficiency of a company and improve customer experience. In-store robots have been there for those who prefer shopping personally.

    Softbank Company introduced a robot to interact with the human's tools and understand the emotions in 2010 and sold more than 12,000 to date. This robot is named Pepper, and it looks like the human body. This humanoid robot is 4 feet tall with a white plastic body and two black eyes.

    There's a touch screen across its chest, which helps in communication. Pepper is a cute and polite humanoid meant to be a companion at the house and assist clients in stores. It gesticulates, speaks, and always seems committed to making everyone smile.

    Pepper welcomes the visitors at Pizza Hut in Singapore and offers ice-cream in Japan. Pepper is the first intelligent machine that is making our lives easier and creating a fantastic new form of communication.

    Walmart has also been using in-store robots for inventory management. Electronics retailer Best Buy also uses robots as a cashier. Lowe's Home improvement has been using a robot that monitors the stock and helps the clients to find the products they need.

    Chatbots

    A chatbot is a system that can engage in text or verbal conversations. Chatbots are designed to provide help and a convincing simulation of a conversation with a human. This type of robot is used for customer service or information services. Early chatbots were based on rules that matched keywords with potential responses and could only engage in very narrowly defined conversations. Chatbots now use natural language processing to understand the meaning, sentiment, and context of questions that provide more useful responses.

    Chatbots are used for conversational commerce, education, entertainment, finance, health, news, and productivity. And chatbots are now more human in their conversations, albeit limited within a narrow domain. Examples of sophisticated chatbots are Google Assistant, Amazon's Alexa, and Apple's Siri, which are acting as virtual assistants.

    The more chatbots are used, the more data that they collect. By connecting the success of the interaction and subsequent interactions, chatbots can learn and improve their communication styles. Just as a child learn, these narrowly focused systems will learn and improve the service that they provide.

    Robotic Process Automation (RPA)


    RPA is a form of business process automation that uses software bots that are programmed to complete repetitive tasks that might have been previously completed by humans. RPA uses APIs to source data from and push data to different systems. RPA is being enhanced with natural language processing (NLP) and AI for such things as facial/voice recognition.

    RPA can be used to automate repetitive tasks such as completing expense forms, processing invoices received by email, producing proposals, etc. Data for these documents might exist in different systems, and some information might need to be harvested from a user. With these various inputs, RPA can quickly deliver a complete product in seconds rather than days or weeks.

    Although RPA is used in all industries, banking, insurance, and utilities are the largest adopters. RPA works well for organizations with numerous legacy systems, whereas newer organizations tend to product suites that are already integrated.

    RPA software revenue grew 63.1% in 2018 to $846 million and is forecasted to reach $1.3 Billion in 2019 making it the fastest-growing segment of the global enterprise software market

    Industrial Bots


    There's been a massive increase in the sales of industrial robots. According to the new World Robotics Report, yearly world sales were 16.5 billion USD in 2018. The Industry Federation of Robotics predicts deliveries in 2019 will drop from the record level in 2018, but they have predicted an annual average increase of 12% from 2020 to 2022. In 2018, 422,000 units were shipped worldwide, which is a rise of 6% compared with the previous year.

    In the automotive industry, car parts manufacturers and assembly operations are the primary users of robotics, and this sector managed to remain the biggest adopter of the robots worldwide in 2018, with a share of around 30% of the overall supply. The demands of robots have steadily increased due to investments in automation for new vehicle production.

    In five major markets, there have been already up to 79% of industrial robotic installations. These five markets are China, Germany, Japan, the United States, and the Republic of Korea. India is not on that list, which is probably due to low labor costs vs. the cost of using robots.

    In the electrical/electronics industry, the figures for 2018 show that there was a decline in robot installations up to 14% compared to the previous year. Three countries have installed 79% of the total robot installations in the electrical/electronics industry. China is leading with 43%, the Republic of Korea has 19%, and Japan has 17% of the total robots installed.

    Takeaways


    Robots were known to be useful for performing mechanical tasks repeatedly. Their precision, and being isolated from humans, meant that they could be deployed at scale within manufacturing plants. As new generations of technology, including AI, enable new types of robots, they will become increasingly used in the workplace. Some will be very visible, and some, like RPA, will be diligently working in the background. We will interact with instore bots and chatbots, and they will learn from our interactions.

    Robots will be working alongside us, physically and virtually, to enhance our capabilities to a new level. Over time, technological innovation and learning from data will mean that robots will increase the quality of service being provided.

    The potential contributions of robotics are too significant to be ignored!

  • 21 Nov 2019 3:48 AM | Anonymous member (Administrator)

    You can’t afford to be part of a faceless organization in the new world of work. That’s why tomorrow’s highflyers will use talent as their brand. Martin Belton reveals more.


    The world hates faceless organizations. If, for some reason, you at all doubt that, type the phrase into Google check out the comments. But if you’re keen for a reference it’s worth looking up the brilliant trend curator and keynote speaker Rohit Bhargava and his lectures on the very subject.

    Traditionally, the way to overcome that facelessness was to create a strong organizational brand. Marketing experts have long wrestled with the subject. But only more recently have they recognized that an organization’s talent is also a key constituent of that brand.

    With the advent of the new world of work and the increasing use of AI and robotics, I’m betting that this focus will ramp up. It is already widely accepted that AI and Robotics will offer amazing benefits and savings. But those effects will be wider. Those very efficiencies will erode the differences between organizations. By using more automated tools, operating on matching algorithms, based on industry wide KPI’s, we can assume the organizations themselves will become more similar. So, it is to the talent within them that we must turn to express those differences.


    Talent branding is not a new subject in HR. It has been defined as being ‘the voice of your employees’. In short, it’s how they act, think, feel, and operate within your business. Your talent brand will match your organization’s mission and values to the experiences of your employees. That is, how your team talks about your organization to friends and family and the way they express what it means to work for your business. All of these are aspects that live within your talent brand.

    Connecting your talent brand directly to your organization’s public face engenders trust and understanding. These connections become touch points and references for talent pipelines, marketing campaigns, customer buying journeys to providing customer service.

    Developing talent as a brand requires leadership and HR to understand and explain how talent helps to create and support the brand. There are several issues inherent in doing this:

    • Defining your talent brand. Are you a technically advanced organization? Are you a caring sharing type of organization? Are you all about better value? How does that represent itself with your employees?
    • Defining what that talent brand is in relation to competitors, both terms of product and services, is also important. This is true for both local and national markets if you are to source the ‘best fit’ employees.
    • Importantly, applying the understanding of your talent brand when recruiting and upskilling your workforce. That means understanding how your talent brand effects the organization internally and externally.
    • Discover how you can measure the success of your talent branding can be a challenge but useful if you are to maintain its effectiveness in the long term.
    • Working with existing employees to support and educate them into the organizational brand goals becomes more important when the focus is on your talent brand.

    Of all those aspects, it is recognizing and defining the first of these – what your brand is – that has the most power to influence your future directions. This is about more than just understanding individuals’ capabilities. Talent as a brand means getting to grips with areas traditionally seen as more challenging to manage as part of the recruitment and development mix. Aspects such as behaviors, emotional intelligence and personality traits. This is of course one of the key reasons why the Talent Transformation Guild is so attached to the Talent Transformation Pyramid. This new model is specifically designed to embrace these broader measures of talent and provide HR and C-suite executives with the data that can make these critical decisions in the future.

    Finally, if you are in doubt whether talent can really be the key constituent of your brand, think of this. In a world which increasingly values real corporate responsibility over facelessness monoliths, real faces – your employees’ faces – and their comments and attitudes will be the most honest and powerful way to express who you are and what you represent. And that is branding.


  • 6 Nov 2019 3:48 AM | Anonymous member (Administrator)

    AI is presenting amazing new opportunities for organizations. But it also adding new layers of complication to planning, managing and engaging workforces. Eric Shepherd suggests employee engagement centers can be the answer.


    For organizations to stay competitive and relevant in the 4th industrial revolution, they will have to automate to catch up and get ahead. In the age of advanced analytics, data analysis, robotic process automation, IoT, and other technological advancements, AI (artificial intelligence) has now become a must-have tool. Leadership is critical to make the most of this opportunity to maximize its full potential. To achieve this, in-house capability building, and reskilling programs are the best ways to prepare the workforce.

    There are of course real obstacles to adopting AI. Not the least of these are the changes to the organization’s thought process and work culture. Leaders, managers, sales teams, manufacturing teams and more all have to think in new ways. Instead the new watch words are interdisciplinary, data exploration, analytics and agile development if we want to deploy AI.

    In the long run, organizations must transform to be successful. History shows us that this cannot be achieved with ad-hoc solutions. Hiring capable employees will give the newly formed AI practice a necessary boost. But for organizations to keep up, AI capabilities must be built across all practices encompassing all employees. And this is where training existing employees come in. Third-party training courses and knowledge bases may deliver an overview of the subject, but they cannot provide organization-specific learning experiences that allow for rapid scaling, lasting cultural changes, cross-functional collaboration, and agile development.

    Adoption strategies

    In-house training is one of the most powerful tools an organization can use to encourage this change. It enables you to build on repeatable, cohesive practices to allow employees to dive deep into the subject matter, learn from others, and achieve the organization’s objectives. Some organizations have incubated new styles of training centers to provide learning environments as part of their adoption strategies. We can think of these new training centers as ‘AI Employee Engagement Centers’ – an environment designed to provide forums for discussion, collaboration, learning, and training. The advantage of this approach is that it can be baked into the organization’s structure, work culture, and needs. Such training centers might soon become one of the core elements of an organization-wide AI transformation.

    One of the primary responsibilities of these engagement centers is to bring AI to scale as rapidly as possible. This requires engaging and reskilling employees who are impacted by the transformation. As AI becomes widely accepted, a critical challenge will be to provide job security for employees whose tasks will be automated.

    For an AI deployment to be successful, three critical building blocks must be developed. An AI Engagement Center can educate employees regarding AI and create the means to support these building blocks.

    Shared Vision


    All training and reskilling efforts must align with a shared vision, common objectives, protocol, and language. This enables everyone to be in sync when it comes to the core elements. It also helps everyone understand each other’s roles and responsibilities and utilize the same methodology while looking for and implementing a solution.

    This alignment across the organization paves the path for a successful AI deployment. This process also facilitates retrospectives from previous AI deployments and curating this knowledge for the organization. This cross-fertilization of ideas and alignment gives leaders more information on the business, talent, and training needs, which enables them to deploy the right people into the correct positions.

    AI Employee Engagement Centers


    In-house employee engagement centers can customize content based on the organization’s objectives, starting position, industry context, cultural roadblocks, and skill gaps. Learning programs can be designed to align with the organization’s transformation road map. Engagement programs can layout the required skills to achieve the transformation and provide the means to learn these skills.

    Employees are provided with technical know how to achieve what the leadership has envisioned. Engineers, data scientists, and analytics experts hone their skills via collaboration to work alongside other business teams. This allows stakeholders to focus on actual business problems and create value for the organization. Employees whose jobs become AI-driven learn how to make the transition from older practices to new AI-based work practices.

    Hands-On Experience


    AI Engagement Centers also provides a forum for employees to mix their classroom knowledge with real-time hands-on expertise. This allows them to transition from being a learner to a practitioner who can deliver capabilities and ultimately develop into an expert who can lead a function.

    Factors to Consider to Build an AI Employee Engagement Center

    AI Engagement Centers will differ in structure based on the organization’s vision, objective, and their phase of AI transformation. While there are differences, the successful centers will have things in common:

    • Building relationships and improving the organizational design, not just learning new skills.
    • Synchronizing the academy’s activities with the strategic objectives of the organization.
    • Providing learning experiences for all stakeholders for the board room to the workroom.
    • Engaging employees in the benefits of digital and talent transformations in the context of their role.

    To extract the best value from AI-driven analytics, some new practices need to be developed. Without them, the speed, scale, and depth of value derived from analytics are bound to suffer. Organizations that plan in terms of engagement rather than training tend to fair better.

    Without coordination, the organization may not be able to identify the right mix of learning materials, group activities, and real-world problem-solving.

    Transformation Centric

    AI Engagement Centers must integrate their programs with the AI transformation road map of the organization. This will ensure the right people, skills, and talents are engaged to prioritize the critical activities for AI adoption.

    Once the leaders are armed with an understanding of AI and the opportunities, they can drive better support for use cases aligned with their organization’s goals. Analytics teams can get a broader and more in-depth understanding of the business challenges that enables them to look at the scenario from a holistic perspective rather than a technical viewpoint. Leadership must understand AI concepts so they can lead efforts in the right direction.

    It's important that all stakeholders are engaged: An effective engagement center focuses on educating the organization’s stakeholders irrespective of their designations, seniority, and role. AI Engagement Centers should plan to engage executives, managers, business analysts, translators, technical developers, business teams, and business functions.

    Going Beyond the Technology


    An AI Engagement Center is more than a technical training center. Training centers will surely cover AI foundational courses, and how to adapt to the technology changes. Employee engagement centers may also focus on the cultural and organizational changes needed to build the AI solution to scale. These centers help create a knowledge repository and introduce best practices that allow the re-engineering of critical use cases.

    Here are some elements of a successful AI Employee Engagement Center:

    • Leaders learn how to drive value, restructure the organization, and ensure a shift towards a data-driven culture.
    • Developing best practices helping everyone identify opportunities, test the readiness of teams, implement the use cases, and codify the learnings.
    • Soft skills enable effective communication, which is critical for interdisciplinary teams. Business processes and challenges have to be explained to AI experts for them define and prioritize the automation.
    • Interdisciplinary collaboration is key to implementing and creating automation necessary for success.
    • Effective change, program and project management are essential for successful AI adoption.
    • Leaders learn to converse with each stakeholder to ease use case adoption.

    Combining Training with Real-world Experience: Successful AI Engagement Centers combine classroom learning, e-learning, and workshops to brainstorm, define, and prioritize solutions. These centers can oversee the successful transition of a learner to an expert. In the classroom, learners might be provided with real-world business challenges. They are required to come up with business initiatives to combat these challenges. By learning in this way, trainees are more likely to adopt the solution that will create the highest business value.

    Introducing currently active use cases and guiding how to solve them, and learners grow through problem-solving. Learning is taken to the next level via social and community engagement.

    AI Engagement Center Keep Evolving

    AI as a technology is still far away from realizing its full potential. AI-driven solutions are changing and evolving at rapid rates. As graduates handle real-time challenges, new talents are hired, and interdisciplinary collaboration improves, more and more knowledge is gathered within the organization. It is important to feed this knowledge back into the AI Engagement Center. Centers put into place the following:

    Top performers from the first batch of learners become faculty. As learners mature and gain more experience, they can lead to learning sessions and workshops. Based on their experience working and teaching, these performers are given more and more responsibilities, eventually becoming senior facilitators.


    AI Centers create a team of individuals to continually monitor and improve the curricula and activities based on real-world experiences and changes in AI technology.

    Involving the C-Suite to visit. When executives visit, it creates unprecedented excitement and highlights the importance of learning.

    As the implementation of AI becomes a necessity, capability building has emerged as the prime requirement. Many organizations have understood that merely building the technical platform, leveraging opportunities, and hiring data scientists is not a surefire way to success. Instead, upskilling and reskilling all stakeholders, starting from seasoned managers to fresh-faced end-users, is critical for bringing AI-driven automation to scale. AI Engagement Centers will not be static enters of training but dynamic organizations that will evolve with the change in technology, use cases, organization culture, and feedback from real work experiences that will be the cornerstone for AI implementation success.


  • 31 Oct 2019 4:51 AM | Anonymous member (Administrator)

    Halloween is an ancient festival and supposed to be frightening. But scarier things are coming in the shape of artificial intelligence. Martin Belton tries not to be alarmed.


    Halloween is meant to be a bit scary. But fun as well. Some believe the festival originated from ancient Celtic harvest festivals and has pagan roots. Still, others believe that Halloween began solely as a Christian holiday, separate from any ancient rites.

    But little on Halloween this year will match the scariness of the article recently featured in the UK national newspaper, the Sunday Times. With dextrous timing, the newspaper published a piece entitled ‘The End of Humanity?’. It pointed out that artificial intelligence is already taking over our jobs, asking if it will free us, enslave us - or exterminate us. After many a scary fact, including the assertion that that autonomous weapons are more dangerous than nuclear weapons, it concludes by suggesting ‘we all better watch out because we don't know what we're playing with when it comes to AI.


    Social Unrest

    One thing is certain about AI; it is already playing a part in our lives and it will only increase going forward. For organizations, it brings many new opportunities. But that also that our HR function will be wrapped in an array of challenges. Almost every month, new reports predict more unemployment and social unrest as machines replace humans. Our article in the Sunday Times cites a PWC prediction which says that nearly a third of UK jobs could be automated away in just 15 years. A further new report from Mercer revealed that executives believed that AI and automation will replace one in five of an organization’s current jobs. 73% of executives predict significant industry disruption in the next three years. On the plus side, the World Economic Forum believes that there will be 58 million new jobs created by 2022.

    Of course, automation has been with us for centuries. But now, more and more jobs are falling under its remit. This is bound to create higher levels of change and uncertainty. And it’s the HR departments that will bear the brunt of this. The challenge is to understand and stay on top of these changes. Not so easy when the experts advise is so at variance.

    Build, buy borrow or bot?


    AI has already affected those components needed to build and extend an organization’s talent capabilities. Traditionally you could define them as “build, buy or borrow. Build, as in take inexperience and develop and train it. Buy as in recruit great but expensive talent. Borrow as in using consultants and harvesting their expertise instead. But the new world of work means we must add ‘bot’ to those options as well. We now, increasingly, have the choice of automating tasks instead of using humans.

    Support organizations such as the Talent Transformation Guild have been established to support executives to get to grips with these challenges. Challenges that may be hard to imagine, but need to be faced if we are to optimize organizations' workforce. Those challenges will demand a better understanding of the contribution of talent so this is no simple ‘one size fits all’ solution. Being part of such a support organization gives you access to the latest, fast-developing thinking on these subjects. Not to mention the opportunity to contribute to the development of the solutions themselves. And that would benefit everybody. Then nobody will need to be scared. Except on Halloween of course…


  • 16 Oct 2019 5:03 AM | Anonymous member (Administrator)

    by Eric Shepherd


    The history of humankind is one of continuous technological improvement. Ever since the first tool was crafted from stone and the first wheel was rolled, there have been innumerable technological breakthroughs to land us in this age of smartphones and the internet of things (IoT). However, real industrial and technological progress began in the mid-eighteenth century, and it is still in procession. Experts and historians divide this period of roughly 250 years into four industrial revolutions.

    With the advent of each new industrial revolution, the anticipation of better lives and the fear of diminishing jobs ran parallel. History has shown us that the concerns were unfounded as the revolutions created numerous new jobs and changed every societal factor for the better. So what would the story of the current 4th industrial revolution, the age of automation be? Will history repeat itself, or will our worst fears finally come true?

    The predictors of doom often quote a McKinsey report that predicts a job loss for over 800 million people, roughly a third of the world’s workforce, across 42 countries. While the report may be another one of those fearful cries that followed the onset of each industrial revolution, it cannot be denied that the 4th industrial revolution is much different from its predecessors.


    With technologies such as 3D printing, robotic process automation, blockchain, AI, robotics, and cloud-based computing, there are entire economic, political, and social systems being transformed, at some places, slowly and at other places at a rapid rate. The nature of this technology is unpredictable and challenging to measure in terms of growth and coverage. As more and more repetitive low-skill jobs get automated, there are job losses for sure. And the trend is significant in developed countries. However, even developing countries have begun to adapt to the new age of automation.

    3D printer automating the task.

    Depending on how sophisticated the technology becomes, even high-skill jobs are not safe from the grasp of automation. But there are, thankfully, limits. At the fundamental level, a job is nothing but a group of tasks to be performed based on many factors. As long it is technologically and economically nonviable to automate certain tasks, those jobs shall remain safe. And thankfully, a large number of such jobs exist even if the situation seems dire prima facie.

    A salient example could be the job of a chef. Scientists might be able to feed a robot with recipes, but the correct movement of the skillet, skillful whisking, and an appetizing presentation is still beyond the grasp of machines and is likely to remain so for a long time to come. Hence we can safely assert that the job of a cook or a chef remains safe.

    This is just one example amongst numerous. One caveat of these job predictors is focusing on the gross job number instead of the net number of jobs. The introduction of automation shall require a higher amount of supervision and quality control. These are tasks that require humans to be at the helm. If the employment of more supervisors does not exceed the savings made from automating part of the production, there will be a reduction in the price of the product due to a cost cut. A lower price may increase demand requiring more production, which in turn shall require more supervision. Hence even though there were some jobs lost when part of the production was automated, new jobs were created. Based on the demand for the product, the final job count may be higher than before.

    There are other dimensions of job creation to be noted as well. With higher inter-industry collaboration today than ever, the adaptation of automation in one industry might lessen the cost of raw material in another. This, in turn, reduces the cost of production when it comes to the end product. Such input-output linkage can lower prices and increase demand resulting in the creation of more jobs.

    Reasons Behind the Naysaying:

    One of the prime reasons behind the negative press the 4th industrial revolution is getting is the inability to see the bigger picture. We have already discussed the gross vs. net job scenario. Often it is easy to take stock of the events happening right now rather than which the current trend might lead to in the future. While some experts take into account the jobs being lost right now, they are unable to identify the emerging job market as a direct result of this.

    Another reason could be the media’s tendency to sensationalize negative information. That and the fact that most of the jobs being lost in the preliminary stages of the 4th industrial revolution will be at the lowest skilled levels. Most of the people losing jobs belong to the low-skilled spectrum of the population. This often creates a significant wave of protest towards the current trend.

    Finally, while there are possibly more jobs to be had in the future, experts at times feel safer overstating a risk rather than understating. All of these factors combine to create a more pessimistic view of the situation. But the light shining through the crack is visible. The most significant change this industrial revolution might bring about is a paradigm shift in terms of the nature of the jobs and the skills required to perform them.


    Low-skill repetitive jobs may soon be a part of history. High-skill, specialized job training will slowly become mandatory. Governments, educational institutes, and organizations need to change along with the time and ensure better preparation for potential workers. Such preemptive steps and awareness may help see through another industrial revolution without the employment doomsday that always seems to be lurking around the corner.

  • 14 Oct 2019 5:50 AM | Anonymous member (Administrator)

    Automation is replacing tasks previously performed by people, changing the workplace creating new ways of working for everyone” says Martin Belton.


    Organizations everywhere will benefit from embracing automation. The Executive Chairman of the World Economic Forum Professor Klaus Schwab believes the fourth industrial revolution will create new work opportunities and connect countless more people to the web. He says it will dramatically improve our efficiency as individuals and in business. These new technologies will impact all job roles, disciplines, and even challenge us about what it means to work.

    Inevitably, it will mean new challenges for leaders and executives. And huge changes for, HR and L&D teams as they reposition their workforce for the changes ahead. As with any future, we can only imagine the shape and structure of these changes. But there are good reasons to believe in at least five real changes:


    1. Automation will be embraced by organizations. Given the efficiencies that will be yielded from automation tasks previously performed by people will be performed by machines. The justification for automation is compelling. Initially this will require partnering between employees and machines which might be cause discomfort or even discontent if not managed effectively. Developing and communicating the plan to accommodate employees’ jobs post automation will be an important part of this communication.

    2. Finding training solutions for fast-changing processes: Clearly, employees will need to be trained on how to partner with machines and then learn how to operate new applications and machines. The challenge for HR will be keeping up with demands for these new training programs and sourcing the required subject matter experts when few exist.

    3. Supporting employees in a disruptive ‘agile business’: The rapid changes caused by automation will mean organizations will need to provide support to help employees embrace this constant disruption. History is littered with examples of upset employees, upset and disorientated by unfamiliar new tools, machines, and practices. That means new support processes will be needed that are focused on understanding change and adapting to it.

    4. Finding new and more diverse talent: Work will become ever more specialized. This will mean HR will need to find and attract specialized talent of all demographics from all over the world, developing and engaging new people. HR itself will need to build new networks and methods to find this expert talent.

    5. Managing the increasing use of external teams: With teams becoming diverse and specialized new systems of identifying and managing talent are going to be inevitable. Key team members will not necessarily be employees or work onsite. HR will need to invest in new forms of communication and collaboration to give the management the necessary tools to coordinate virtual teams.


    6. Understanding the robotics and systems versus employment equation: The increasing use of robots and robotic processes on the shop floor and office will mean new ways of evaluation will be needed. As machinery becomes more complex and capable, so the variables of a job roles’ requirements. This will make planning for staffing and employment needs more complicated. Leaders and HR executives will need new and smarter tools to plan and evaluate their success.

    Managing these transitions and new forms of talent will need new IT systems that engage with these new working arrangements. New HR roles will emerge. Functions will arise that we can’t imagine now but will be commonplace in a few years.

    Solutions such as the Talent Transformation Pyramid are shaped to help organizations understand these changes and react to them. Without this holistic view of talent we are going to find it difficult to understand and support the organization’s future needs.


    We have evolved today organizations with complex hierarchies and decades of legacy infrastructure. If they are to become tomorrow’s agile businesses, and bring about these seismic changes, then digital and talent transformation is key to achieving that. And that starts with the HR department.


  • 25 Sep 2019 10:41 AM | Anonymous member (Administrator)

    On the face of it, spotting rising talent and improving performance is easy.
    Yet for many organizations, this is a complex and elusive quest. Martin Belton thinks some of new business books may have hit upon why.


    “Knowing what we don’t know is better than thinking we know what we don’t,” says Philip Tetlock in Superforecasting: The Art and Science of Prediction. This book was first published a couple of years ago. But it is now enjoying a new round of publicity which led me to its contents. This was a timely thought for me while I’ve been working on establishing our new model, the Talent Transformation Pyramid. More on that later because it’s also worth looking at the book’s underlying theme. That is, while most of us are quite poor at forecasting the future, there exists a small merry band who fare so much better than the rest of us. That cohort is far and few between. But statistics show it exists. The book goes on to reveal how these ‘superforecasters’ manage this.


    Another popular business press read at present is Malcolm Gladwell’s latest, Talking to Strangers: what we should know about the People we don’t know. Interesting as always, Gladwell points out how bad we are at assessing strangers. In one observation, he cites the case of Judges assessing bail applicants in New York. They believed that face to face assessment was crucial. That was until a young researcher fed bare-bones information about applicants into a computer. It transpired the machine was superior to the judges at spotting re-offenders.

    Misleading subjective assessments


    I read them one after the other. I imagine that’s why I was struck by the similarities of their premises. The first similarity is hardly a revelation: both say that, when predicting future events, the more objective data you gather, the more chance you have of getting it right. But secondly, and more surprisingly, both point out how misleading subjective assessments can be and just how easy it is to be deceived and deceive oneself.

    Going back now to talent and performance measurement, it’s not hard to see how such issues matter. Gathering, applying and managing data for these functions can be onerous. But without it, we're relying on subjective judgments. The Talent Transformation Pyramid model was created to enable us to counteract this. It provides a solid view of what we know, and what we don't know. Designer Eric Shepherd set out to address these issues after hundreds of conversations with professionals in the sector. They revealed the lack of a recognizable model that could pull together all the relevant factors that enable us to identify and grow talent.

    12 separate factors

    The Talent Transformation Pyramid recognizes as many as 12 separate factors to enable us to do that. It clarifies the relationships between those factors. That enables us to document them within competencies and group them into a competency model. The model helps us describe what is needed to be ready to deliver performance. If we are to create an effective talent and performance system, it is to this kind of detail we must turn.


    Of course, the model also admits that it may not always be possible to gather all the data we would wish to. But as Tetlock noted ‘knowing what we don’t know’ can be useful as well. That alone can give us a far stronger platform to evaluate our Talent.

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