Data-driven approaches to managing people

Regular pulse surveys and employee feedback initiatives are critical for understanding broader, long-term employee sentiment. However, these are no longer enough to reflect the speed of change affecting all companies in the present circumstances. When collaboration depends on the effectiveness of virtual interaction, something different and more immediate is needed.

Managers need new ways to support their team’s welfare and develop remote working practices to increase employee engagement and improve team productivity.

New tools and techniques at the intersection of people and data offer ways to address these challenges. As so many organizations adapt to remote working, now is the time to experiment with them. Before we begin however, we must start from an ethical position.

Employee data, AI and ethics

Data science and AI give rise to a range of ethical concerns. The pace of technological advancement tends to outstrip the pace at which regulatory frameworks addressing those concerns are developed. Last year our report, Why addressing ethical questions in AI will benefit organizations, underlined some compelling reasons for organizations to take these issues seriously:

• 42% of employees globally have already experienced use of AI by their organization that resulted in ethical issues
• 76% of consumers expect new regulations on the use of AI, following positive perceptions of recent data privacy regulations such as GDPR
• Organizations whose AI systems consumers see as interacting ethically enjoy a 44-point Net Promoter Score (NPS®) advantage compared to those seen as not using AI ethically.

While offering new ways to monitor employee engagement, productivity and wellbeing, the use of these tools rests on the principle of informed consent. Employees must be made aware of the purpose of capturing and analyzing their data, and have the right to refuse permission.

But it’s about far more than whether people opt in or opt out before data on their work or performance is gathered.

Business leaders need to lay the foundation with a strategy and code of conduct for the ethical use of data and AI.

Systems must be transparent and explainable, supported by clear policies, strong data management, a culture of discussing ethics from the outset in projects, and ways of empowering individuals to seek recourse where necessary.

When these ethical considerations are proactively handled and a culture of responsibility and trust is developed, organizations are well placed to leverage tools and techniques in three areas.

1. Team productivity

When you are physically working together, it’s easy to monitor people’s productivity levels. Not so when everyone is working remotely. How do you measure the confidence (or fears) of your employees as they embrace new digital tools? Are they getting the most out of them, or spending too much time on the wrong things, ultimately increasing their stress levels?

Work-life balance challenges may also increase in a remote working context, when people can be less conscious of the boundary between work and home life. This presents managers with the challenge of recognizing where to intervene to protect wellbeing.

Applying automation and data visualization to reporting tasks offers managers insights into these areas.

When team members can spend less time creating manual reports or updating others on progress, the opportunity arises to refocus effort on higher-value activities. Advanced analytics dashboards from Sapience, for example, allow managers and employees alike to see what kind of work (calls, marketing, meetings, management, etc.) they are spending their time on and how productive entire teams are.

Sapience allows team members to track their own performance and work habits, and by raising their awareness of their working styles using this data, provides a stimulus for improving both work-life balance and individual performance.

2. Team dynamics and individual engagement

By definition, remote working replaces face-to-face engagement between colleagues with voice or video calls, and the often transactional exchange of messages. Yet, it is body language, non-verbal communication and other softer types of interpersonal interaction that enable us to read between the lines – to understand colleagues’ emotions, and how they truly feel about any aspect of their work. In response, facial recognition tools and artificial intelligence (AI) are increasingly being used to analyze people’s emotions and engagement during video conferencing calls.

The Riff Platform is one such tool. It is a cloud-based video and text chat data insights web application. It measures conversational dynamics, analyzes vocal activity, and uses AI-driven conversation models to track who is talking and collaborating. This tool offers insights into engagement levels during remote meetings, social awareness, and who is more dominant in a meeting. Participants and managers alike can use the data to better understand their interpersonal behaviors.

How might your team dynamics change if everyone could refer to objective data about who is more or less engaged in a discussion? Who interrupts most? Or who shows most emotional sensitivity?

3. Listening to your team

In a remote working context, how can you assess how your whole team is feeling and what their concerns are dynamically, day to day? One answer is by reinventing the traditional employee survey as a continuous, dynamic listening exercise; and using AI and data visualization to interpret the data that comes back.

Our Capgemini Invent team in Norway uses the Microsoft Forms platform to assess the impact of COVID-19 and remote working on a large workforce.

A simple, automated online survey process gathers data anonymously to establish how employees are feeling, identify unmet needs, and evaluate whether the interaction with management was transparent and frequent enough. It also gathers insights on how partners and customers are affected, and the overall productivity of the team when working from home. The questionnaire can be amended rapidly to respond to the changing situations.

Automation of the data flow ensures that new responses automatically appear in continually changing visualized datasets. A dashboard and the compliant sharing of analysis with all relevant stakeholders form another stage in the workflow.

The data reveals what topics people need information about, overall sentiment, and how people’s dialog with their customers is developing. In response, changes have been made to communications and certain aspects of the working day, such as when to run department meetings, social gatherings and virtual PT sessions.

The value of engagement

As we all continue to confront new, virtual ways of working, how we engage and support our people has become more relevant than ever. Organizations able to identify and quickly address problems impacting employee wellbeing will be better placed to retain talented people. Culturally too, improving engagement by nurturing a culture of listening and feedback increases employee wellbeing.

But the business impact is also undeniable. Higher levels of engagement are proven to increase productivity. Warwick University’s research Happiness and productivity: Understanding the happy-productive worker shows that happy employees are 12% more productive. Research by Gallup – How employee engagement drives growth – underscores the relevance of the topic at this moment:

Gallup researchers studied the differences in performance between engaged and actively disengaged work units and found that those scoring in the top half on employee engagement nearly doubled their odds of success compared with those in the bottom half. Those at the 99^th percentile had four times the success rate of those at the first percentile. These kind of performance differences are always important to businesses, but they are especially crucial during a recession.

It’s always been the case that the more we know about how people are working, the more we are able to manage their motivation, performance and productivity. In a context where remote working and digital collaboration have become the norm, data science will increasingly play a role in delivering that insight.

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Co-author

Claudia Crummenerl

Expert in Change Management, Culture Change, Digital transformations, HR Transformation, Leadership in the digital age

After 8 years in the automotive industry, Claudia Crummenerl joined Capgemini Invent for their reputation in organizational transformation and change management. The People and Organization teams represent the employee perspective in change projects and support clients in the design and implementation of their transformation.