Navigating the new reality of HR with skills at the core

Business leaders continue to witness multi-fold organizational challenges due to ongoing disruption in the ways of working and the accelerated digitization, automation and  shift to remote/hybrid work. These changes have highlighted the role of flexibility as a way to meet the growing individual and organizational demands and no matter where you look, emerging technologies, mobilization of complementary competencies, innovation, governance, growth, net promoter score, value creation, delivery and more are all being introduced, dynamically exposed and evaluated.

Moving into the new paradigm

Unparalleled changes are a new normal and the related disruptions are exposing blind spots. To remain relevant, leaders can help if they maintain an agile approach to the workforce and shape and empower their businesses towards a new reality. When global leaders are in a volatile, uncertain, complex, and ambiguous (VUCA) state of dilemma it’s a perfect time to evaluate and determine effective areas of focus including:

◉ Defining and improving employee lifecycle and considering employee personas via empathy mapping

◉ Strategic workforce planning in the context of a gig economy

◉ Adoption of analytics/automation like bots and workforce analytics

◉ HR reinvention for new-age skills looking at skills frameworks for reskilling and upskilling and mapping talent to value

◉ Digital change/transformation dashboard-enabling technologies and digital HR platforms

To enable leaders to prioritize effectively and create an agenda for reinvention, they must have a clear and transparent view of HR priorities and interventions vis-a-vie their organization’s capabilities.

Demand and supply, a contextual perspective

Post pandemic the demand for a skilled workface has become directly proportional to supply. The new-age skills to drive a sustainable business model have increased the needs. And, learning and development (L&D) has also moved upwards in the “must-have” category. This shift has forced leaders to acquire dynamic capabilities to innovate their business model because it is perceived as a key driver for competitive advantage.

Qualitative findings and comparative analysis for HR leaders and chief experience officers (CXOs) aim to build a future-ready workforce and a workplace to support the successful execution of the organization’s strategies. The needs of tomorrow’s organization should also include identifying and defining priorities for HR leaders to address the ongoing business-as-usual changes.

A contemporary lens for HR transformation

Comprehensive analysis of leading consulting organizations who examine HR priorities helps identify the top priorities of HR leaders. It also aims to segment HR topics based on current capabilities and their future importance.

Key trends and actions in the sense-and-respond model indicate the following as upcoming opportunities to be tapped:

◉ Upskilling, reskilling and learning

◉ Employee experience and engagement

◉ Leadership behaviors and development

◉ Workforce planning and adjustment

◉ Organization restructuring and operating model

◉ Talent management

◉ Digital HR

◉ HR Reinvention

◉ Change management capabilities

◉ Workforce/HR analytics.

Transparency drives accountability in planning and introducing interventions to eliminate possible barriers leading to rapid expansion in organizational capacity. As we step into the new ways of working, retaining employees and creating a leadership bench in a remote/hybrid workplace post-pandemic would be one of the critical challenges to be addressed.

Building critical skills and competencies

Skills are the new currency. 72% of outperformers recognize the importance of skills and continually invest in them. Yet only 41% of organizations report they have the talent required to execute their business strategy. Skills are, and will remain, the golden thread across the employee lifecycle.

As per the recent global survey conducted by the IBM Institute for Business Value, employee experience and skill are at the core in HR 3.0 as HR helps drive a company’s overall enterprise transformation. Skill at the core has a 69% level of importance to the future of HR and 38% level of achievement today.

Bridging the gap between future vs. present

Organizations are eager to build a future-ready workforce equipped with the skills and capabilities to meet tomorrow’s challenges. Reskilling in the post-pandemic era has emerged as the top challenge for business leaders. Bridging the gap between future and current skills is an opportunity available to create competitive edge.

Enterprise skilling for the future is an approach to build the right skills —at scale— with existing talent to meet the needs of business and to stay ahead of the market. A compelling future skilling journey as a tool to identify skills gaps and build a cross-functional team in hot skills with a quick and efficient learning path to support employees as owners of their careers, managers as talent builders and strategic planning for business unit leaders.

Building a job taxonomy framework and a skills library that can be extended to specific industries would help in the creation of:

◉ Job descriptions and responsibilities

◉ Core competencies and behavioral-based proficiency statements

◉ Development goals

◉ Coaching tips

◉ Interview question

The call to action

It’s imperative to highlight that the involvement of leaders and employees is equally important in building the new-age organization. Reskilling the workforce through personally and professionally enhancing initiatives will remove the obstacles in meeting the unpredictable future challenges. And, it will not undermine the availability of critical skills for the organization. Businesses need to have the right people with the right skill sets and the HR agenda should focus on the key actions to reflect the new reality in the future and beyond.

Source: ibm.com

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The need for trusted AI: Advancing ethics and transparency

Artificial intelligence (AI) uses computers and machines to mimic the problem-solving and decision-making capabilities of the human mind. The technology is intended to foster logic-driven decisions but when human bias creeps into the system, it can have unintended negative results. However, when the work is done to implement AI in an ethical and transparent manner there are endless possibilities to extend knowledge and embrace the diversity of the of the hundreds of thousands of human dimensions. 

What we know

According to an IBM Institute for Business Value (IBV) survey of global executives, average spending on AI will likely more than double in the next three years1. And with heightened AI use, there is an elevated risk related to data responsibility, inclusion and algorithmic accountability. AI is powering critical workflows in financial services, human resources, customer management and healthcare and AI adoption continues to accelerate rapidly providing the opportunity for collaboration within and across organizations to put ethics and transparency at the forefront.  

Consumers are troubled about how companies use their personal information: 81% say they became more concerned over the prior year with how companies use their data and 75% are less likely to trust organizations with their personal information.1  As concerns about privacy, misuse and bias climb, companies must be vigilant in how they treat consumers’ data to build trust. 

AI’s socio-technical aspects are intended to unite humans and technology and a dedication to transparency can help companies advance this unity. It’s time for industries to wake up and do things in novel ways that shun black-box algorithms and instead foster data sets which are understandable to the end-user. We must be honest that insights gained from algorithms aren’t always accurate and instead work toward data that’s explainable, predictable and more accurate.  

Things to consider

Consider how AI is used in talent management. As every job seeker and hiring manager knows, matching a candidate’s skills and fit for a role goes well beyond an algorithm. While intended as an impartial method for organizations to narrow a pool of qualified applicants to advance to interviews, there is a threat AI may introduce bias. AI often lacks the human element required to match the right person with the right role and may adversely impact areas of judgment and have an impact on a person’s opportunity to advance or be considered. 

Across the globe, the AI regulatory environment is evolving. The European Union Commission recently proposed new regulations and a comprehensive framework for trustworthy AI, a move expected to affect companies around the world. 

In the quest for financial success enterprises may cut corners, inappropriately deploy AI and sacrifice strategic priorities — and even values — for temporary gains. To confront these potential pitfalls, a company may build a compliance apparatus to create guardrails and other reinforcement mechanisms to combat inadvertent or intentional lapses.  

The impact of AI

Ethical considerations surrounding AI have never been more critical than they are today. People around the world including business executives, front-line employees, government representatives and individual citizens face serious decisions they wouldn’t have imagined in the past. These can profoundly impact the lives of their colleagues, clients and communities. Many companies are forced to weigh difficult trade-offs between economic and health imperatives guided only by their ethics, morals and values. 

Given AI’s prevalence in many high-stakes decision-making applications, it’s essential that we build AI systems that are truly fair, explainable, accountable and robust. Methods that lead to trusted data include creating a clear data lineage and provenance, and embedding responsible ambassadors in the core development of AI processes and applications.  

Hard work with a payoff

It’s time for businesses to get serious about scaling AI in an enterprise environment. Organizations must take meaningful action and proactively address misuse and consumer concerns. The hard work will pay dividends when we begin to see humans in thousands of dimensions rather than commodities. The companies that act now have an opportunity to shape their competitive futures—and make AI more trustworthy and, ultimately, more trusted.

Source: ibm.com

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To help plan for a return to work, businesses should consider leveraging IoT insights at the edge

In the current climate, many businesses have pivoted to a remote workforce, but this option may not be equally accessible across industries. Organizations that operate by serving customers and citizens – like manufacturing, retail, healthcare, and government – are less likely to be able to maintain full operations remotely.

Businesses in these industries are likely to be eager to quickly and, above all else, safely plan for employees to return to the workplace following the guidance from national and local governments. In 2018, An estimated 12.7 million workers were employed in the US manufacturing sector, and, about 1.14M workers in the US warehouse & storage industry, with more employed across retail, healthcare, and government.

How can organizations support a return to the workplace given the COVID-19 crisis?

In addition to following the return to work guidelines issued by CDC and federal, state, and local governments, to help support a return to the workplace, businesses should consider leveraging technology solutions – like edge computing, 5G and IoT –  to gain insights that can help protect employee health and promote workplace safety. Edge computing can be a strong alternative to cloud processing for near real-time data access.

Employee Health

◉ Employers will need to rethink their strategy to help protect their employees’ health and safety while at work.  One option to consider is to leverage technology and systems, such as:

◉ Infra-red (IR) cameras set up at key entry points can screen individuals with higher basal body- temperature in order to quickly detect possible fevers.
Connected wearable devices can monitor employee health factors such as oxygen level, heart rate, blood pressure changes, and respiration rate.

Workplace Environment Safety

Operations-intensive areas such as manufacturing shop floor, warehouses, distribution centers, and commercial office spaces can often be congested, so leveraging technology to glean insights about the status of the work environment can be helpful.

◉ Optical cameras can help identify increases in the crowd density of certain areas, and notify if there is a breach of preset business rules such as the number of people limited to each zone.

◉ Bluetooth beacons can help detect proximity of employees to one another based on social distancing norms in the company premises.

◉ Leveraging the insights from multiple locations can help identify areas of needed focus as well as leverage best practices back across the enterprise.

Edge computing is a strong option

Real-time data access is key in order to quickly identify potential safety concerns in the workplace. In this scenario, edge computing can potentially be a stronger option than cloud processing. If data must be sent to a central cloud, analyzed there and returned to the edge, there can be a lag in data processing, high data cost, and need for always-on internet connection. If businesses utilize edge computing there can be potential advantages –

◉ Businesses can capture and analyze data locally

◉ Eliminates the need for storing a lot of data on cloud, which can potentially result in lower operating costs

◉ Reduces the need for huge real-time event processing on cloud

◉ Sensor data is continuously monitored, not stored, and the system triggers an alarm only if it detects an anomaly

For organizations where remote operations is not an option and are planning to bring workers back under the proper guidance, consider technology when developing your strategy.

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Six recommendations for launching or expanding your virtual agent in this crisis

As we work together to respond to our current crisis, artificial intelligence (AI) is a force multiplier, helping us effectively and efficiently navigate this overwhelming storm.

Artificial intelligence (AI) virtual agents are not new news. Today they are being reimagined to help citizens and workers access trusted data sources and to help get the answers they need. How many infectious cases are in my area? How do I get tested? What should I do if someone in my household is sick? When should I go to the hospital?

Both public sector agencies and private sector organizations are building on these capabilities to rapidly train AI on policy. What is my organization doing to respond to this crisis? What happens if I need to take an unscheduled day off? How much sick leave can I take? Organizational policy is rapidly evolving, each week is a new frontier as we learn, together, how to navigate an unprecedented global pandemic. As organizations amend their business policy, the AI can be quickly updated to reflect these new changes, becoming the single true source of data for an organization and its entire workforce.

AI virtual agents are simple yet powerful solutions. In early deployments around the world, we are seeing a significant decline in the volume inbound inquires to call centers, which means shorter waiting times for those critical cases. When workers get answers from AI, this means more time connecting with managers and colleagues on mission-critical initiatives. By analyzing the AI interactions, leaders have deeper insight into their workforce and use the data to help prioritize their crisis response strategy.

Whether you are launching a new virtual agent or expanding the capabilities an existing one, here are six recommendations:

1. Keep your employee personas at the heart of your design. Understand the needs of your employees and prioritize those when building AI capabilities.

2. Balance security requirements with access and leverage the cloud. Take a hard look at the need to access confidential information and balance that with the need for the AI to be available anytime, anywhere, on any device.

3. Start small and iterate quickly. Consider a prototype with limited functionality, deployed to a smaller group of users. Scale quickly to a broader set of users and expand the AI’s capabilities through frequent updates.

4. Consider integrating publicly available data from trusted sources. Public health organizations, government agencies, and educational institutions are making large amounts of information available. Train your AI to use these data sources or provide links to additional sources of information.

5. Make one of your senior leaders the solution owner. Your chatbot team needs near-real-time insight into the changing organizational policies, in order to adapt quickly. Select someone who is a focal part of the leadership team as solution owner, helping minimize the real-time between policy decisions and training the virtual agent.

6. Use the AI data. Take your cues from your workforce. The questions asked are the topics of most interest or concern. Adjust your crisis response strategy accordingly.

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With a focus on supply chain modernization comes the need for embracing change management

As the world looks forward and enterprises focus on the new normal, the COVID-19 pandemic has revealed the vulnerabilities and fragilities in global supply chains across most, if not all, sectors and industries. Leaders are now analyzing the current pain points to better prepare for tomorrow. To avoid perpetual reaction to future “black swan” situations, leaders need to evaluate how they can proactively get ready for future unpredictable, yet inevitable, disruptions. While no one can foresee what’s in store for tomorrow, we can work today on building a smarter global supply chain.

The need to modernize supply chains to gain end-to-end insight into the production, procurement, inventory and the delivery of goods and services is certainly not new. Today’s environment accentuates the need for this modernization and transformation.

But the supply chain is complex and intricate. Merely plugging in new technology won’t yield an organization any insight if it doesn’t first review why it needs to change long-standing supply chain practices and how it will do so. By embracing change management methodologies before any upgrade to the supply chain, organizations will recognize the level of collaboration and commitment needed to make the most of any new technology and reap the benefits of a modernized supply chain.

There’s a long list of things to consider when advancing change, but an organization needs to prioritize the roles of its employees and determine if they have the proper skills to thrive. Above all, leadership needs to show employees how they and the company will directly benefit from new supply chain technology.

Collaboration across the supply chain

Because companies have relied on legacy supply chain technologies for years, they’ve probably given little consideration to the steps behind digital transformation. They need to ask: How massive are our organizational silos? Do the varying systems and processes within each silo clash with our key performance indicators? How do outdated manual processes impede information sharing?

Indeed, the expectations and output of a single but important warehouse might be misaligned with what the company wants to do, but few might recognize the disconnect.

Change management encourages companies to step back and review what would happen if new technology isn’t immediately adopted. This tempers any rush to purchase technology for its own sake. Instead, they’re encouraged to review how their competitors approach supply chain management and then turn inward to determine what will be their own top goals of modernization. Many things will seem important, but by narrowing the initiative to a handful of achievable KPIs — increasing service level, decreasing working capital, improving process efficiencies — companies can refine what their future supply chains should look like. They’ll also be able to better align their goals with the appropriate technologies.

A formalized change management process also spurs leadership buy-in at the outset. Engaged leaders shape the vision of their improved supply chain and prepare clear messaging that can be shared with the organization over the long haul.

There are ways to mitigate a long transformation process by having an agile change methodology and involving all key participants in co-creation studios, emphasizing the need for cross-functional collaboration. Because a supply chain runs wide and deep, a variety of departments and teams that otherwise might not regularly communicate with management or other units about new technology will have to join the discussion.

Communication breakdown

Effective communication is central to employee engagement, the most critical aspect of widespread change. Leaders shouldn’t solely dictate to employees how they’ll use new technologies and processes. Employees need to be nurtured and advised to achieve true progress.

To start off on the right foot, leadership should understand the roles and tasks of the employees behind the supply chain. By developing personas — profiles that consider an employee’s experience with the technology, location and duties central to their job — the company can better understand how a particular group of employees will be affected by, for example, a new warehouse management system.

Employees will inevitably ask what’s in it for them. They want to know how their jobs will change and whether their career development and fulfillment will be affected. When managers understand how new processes and technology will affect employees, they can communicate what the changes will accomplish and help workers transition. A new perpetual inventory management system, for instance, would allow some store employees to spend more time with customers instead of scrambling to find inventory — a development many would probably embrace. With employees, it’s not just about buy-in — it’s also about giving them an ownership stake in new processes, and that requires finding out how employees learn new skills.

Training will probably be necessary. Middle management should walk employees through new technologies and processes. Employees can also learn at their own pace on digital training platforms offered by professional training services – particularly useful during these times.

Changing from the inside out

Customers’ expectations will only increase, and the internal processes behind a supply chain will only become more complex. Supply chains should be dynamic, responsive, and interconnected to an organization’s ecosystem and processes. This requires end-to-end visibility, real-time insights, and decisive actions – particularly in escalating situations. While new and innovative technologies — such as machine learning, advanced analytics and blockchain — can help organizations build smarter supply chains and help companies maintain business continuity amid disruption and uncertainty, these applications can’t be added in a void.

Companies first need to embrace rigorous — and undoubtedly difficult — change management methodologies to understand how they should update their supply chains. Change management services, such as those as offered by IBM, have the expertise (through consultations, workshops and innovation labs) and technology (AI, advanced analytics, an insights dashboard) to help organizations modernize their supply chains from the inside out.

Source: ibm.com

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