The scope, speed and impact of the Fourth Industrial Revolution is disrupting almost every industry in every country. Melissa Swift, Global Leader for Digital Solutions, Korn Ferry HayGroup, says that digital disruption will forcibly require traditional organisations to have a firm understanding of their business strategy and company culture so that they can understand where action needs to be taken, and sustainably manage change.

Industry 4.0 – or the Fourth Industrial Revolution – can be seen in two ways. Some believe it is just a prolonged version of the fundamental changes brought by the third industrial revolution, while others see it as a paradigm shift into a wholly new world. Regardless of which point of view one holds, it is certain that the scope, speed and impact of this revolution is disrupting almost every industry in every country, bringing about unprecedented change for consumers and businesses alike[1].

Industry 4.0, in the strictest sense, refers to the rise of automation and data exchange in manufacturing technologies. The revolution itself includes cyber-physical systems, the Internet of Things (IoT), cloud computing, and cognitive computing[2]. According to Siegfried Dais, the rapid developments in smart technologies and automation are creating a world that will become more and more networked until everything is linked with everything else[3].

This revolution is promising far-reaching impact that transcends geography and industry, and will sooner rather than later require every cog in the wheel of global business to ready itself for the challenges and opportunities that lie ahead.

Challenges for traditional organisations

Perhaps the long and growing list of challenges for traditional organisations is best summarised in one phrase – continued and accelerating disruption.

Leaders have, for some time, understood the need for constant transformation but according to Korn Ferry research[4],  organisations in all industries are struggling with the ability to transform continuously as waves of disruption upend the business world.  What this study proves is that what got you here — hierarchies, traditional rewards, static teams — will not get you where you want to go. It simply will not sustain organizational performance in the future of work.

So, how can complex, hierarchical and matrixed organisations with decades of legacy infrastructure become agile businesses? The revolution required to respond to today’s reality is not about simply introducing digital technologies – it requires seismic change and that, in turn,  means:

  • helping employees embrace consistent disruption;
  • organising, leading, attracting sought-after talent of all demographics from across the world, developing and engaging our people;
  • designing digital customer experience and effective customer journeys by introducing better products and services featuring speed and simplicity;
  • engaging directly with  customers on an ongoing basis;
  • keeping up with – or even overtaking – pure-play digital leaders;
  • developing the capacity to continually transform and thus achieving digital sustainability.

Critical to driving this change is the right balance of human capital talent to ensure genuine interconnection of all employees and functions within an organisation[5]. Organisations are seeking to cultivate an employee population who can act together quickly to produce more relevant, insightful financial counsel and services.

Big data and analytics in HR

There is no question that hiring and empowering the right team of professionals to prepare for the many changes that lie ahead is a priority of many organisations around the world. Today, the questions that HR teams want to have answered about potential and existing employees are far more complex than in previous eras.

Historically, the human resource function has been focused on evaluating experience, performance, engagement and remuneration. However today, the potential of existing and external talent is weighed against a host of deeper and more thoughtful questions around performance, ethics, innovation, remuneration and engagement in line with an organisation’s succession strategy. A new and more challenging set of concerns dominates the agenda – where answers are far more elusive.

Research shows that organisations who actively employ HR data analytics are twice as likely to improve their recruiting and leadership pipeline, three times as likely to realise cost or efficiency gains and 3.5 times as likely to get the right people in the right jobs[6]. The promise of data analytics in HR is seductive: the possibility exists to increase productivity and engagement, empower talent, activate innovation and transform leadership for more effective recruiting and better talent retention.  In the most advanced, AI-enabled state, HR analytics can serve as an “extra brain” for CHROs, raising, digesting, and answering provocative questions.

The reality, though, is a bit less elegant. Data scientists spend 80% of their time collecting and cleaning data[7] spread across various sources – HR information systems, applicant tracking systems, learning management systems, total rewards systems, performance systems, social media, ad hoc spreadsheets and sometimes, just random pieces of paper. In addition to the frustration this work produces in the data scientists performing it – across organizations, data scientists are showing notably low engagement scores – a host of logistical changes then arise. Data types and sources must be evaluated for their advantages and challenges to ensure integrity and quality. Key questions to be asked include: Who entered this data, and why? How old is this data? Are there structural or technological barriers to accuracy or completeness? Could unconscious bias influence this data? How can this data be evaluated for accuracy and precision?

And what about analytics – the fine art of separating signal from noise? New analytics techniques such as network analysis, sentiment analysis, predictive analysis and artificial intelligence have the potential to add tremendous value. That being said, organisations big and small are getting ‘quick wins’ by simply going back to the basics. Often simple analysis, conducted thoughtfully on well-curated data sets, can yield powerful results to key questions: Are people using the tools provided to them? Are people rewarded consistently and fairly? Where might employee dissatisfaction cause issues?

What is fascinating in the current environment is that classic data types such as interviews, assessments, performance, rewards and benefits, and engagement and attrition data are being examined with a new eye. Analysis of interactions between these data sets, for instance, can produce provocative insights. New data sets such as external supply and demand conditions or social media interactions are also being heavily mined for fresh insights.

And at the end of the day, these leading practices should compass the way for any team employing either complex or basic analytical tools:

  • Invest in well-functioning systems but understand that systems are no substitute for a business-driven understanding of the situation.
  • Get the right HR analytics talent in place but do not forget to utilise knowledge of the organisation to drive context.
  • Learn from data from the outside world but have a strong view on your own environment and context first.
  • Benchmark but know where your organisation is unique.
  • Delve into complex issues but keep outputs simple.
  • Use data to illuminate the future but know that there is no single, predetermined future!

 

The original version of this article first appeared in The Link Magazine, issue 28, 2018 – published by Asian Institute of Finance.

[1] The Fourth Industrial Revolution: what it means, how to respond, World Economic Forum, https://www.weforum.org/agenda/2016/01/the-fourth-industrial-revolution-what-it-means-and-how-to-respond/  14 Jan 2016.
[2] Wikipedia, the free encyclopedia https://en.wikipedia.org/wiki/Industry_4.0
[3] The Internet of Things and the future of manufacturing, McKinsey & Company, https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/the-internet-of-things-and-the-future-of-manufacturing, June 2013.
[4] https://focus.kornferry.com/the-korn-ferry-digital-sustainability-index/
[5] Nine challenges of Industry 4.0, IIoT World, http://iiot-world.com/connected-industry/nine-challenges-of-industry-4-0/
[6] https://www.bersin.com/deloittes-bersin-finds-effective-use-people-analytics-strongly-related-improved-talent-business-outcomes
[7] https://www.forbes.com/sites/gilpress/2016/03/23/data-preparation-most-time-consuming-least-enjoyable-data-science-task-survey-says/#1040380c6f63

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About Contributor

Melissa Swift is the Global Leader for Digital Solutions at Korn Ferry Hay Group. She is charged with driving the development, alignment, and marketing of innovative solutions for digital transformation offerings. Melissa partners with clients to understand their deepest challenges in the digital arena, and to address those challenges in novel and comprehensive ways. She is a frequent speaker and writer on the digital topic and her research has been published in such venues as Harvard Business Review and The Wall Street Journal.

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