In part one of our blog series on people analytics, See into the Future: The Crystal Ball of People Analytics, we explored the use of leading versus lagging measures (to look beyond the past and toward future-oriented inputs and actions) and how to frame future-focused questions. Both actions allow organizations to sense future-of-work impacts such as automation, the open talent economy, and the virtual workplace. Now in part two, we’ll explore how a listening architecture can develop an ongoing and actionable approach to sensing the future.
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Creating a listening architecture
There are many ways to collect workforce information, from using HR information systems, enterprise / operational data, and workforce surveys to mining internal and external social media. Establishing a listening architecture can help organizations make the most out of these sources. A “listening architecture” is a structured approach to repeatedly collect information and derive meaning. There are a variety of ways to create a listening architecture, but organizations should consider four elements when designing theirs: purpose, channels, muscle, and governance.
Listening architecture considerations
Purpose: What are you listening for and why?
Asking “What is the future?” is not as insightful as asking “What capabilities and skills are most critical for our workers over the next few years?” When creating a listening architecture, partner with business stakeholders to identify the future-facing business / talent challenge you are trying to address (e.g., to get ahead of skill shortages, to partner humans with automations, to increase remote worker productivity) and define how insights gained from these challenges would be actioned.
If an organization has a poorly defined listening purpose—or jumps right into collecting data—it may struggle to identify what findings matter most and may lack leadership support for taking action. High-performing organizations are three times more likely than low-performing organizations to have both a clear vision and mission for people analytics and strong partnerships with business units and corporate functions.1
Channels: How will you collect information?
There are many options for collecting information, from active channels (e.g., surveys, interviews, focus groups) to passive channels (e.g., social media, job postings, communication metadata). On average, high-performing organizations use seven different channels, while low-performing organizations use three.1
Depending on your purpose, the information your organization needs will most likely not come from a single source—it will require accessing new information channels and / or the combination of different channels. For example, if you are trying to gain information on future skill gaps, that information is most likely not available through your HR system and may require new channels such as analyzing external job postings (i.e., to identify skill trends in the market) and comparing these insights to your workforce’s current skills (i.e., a proficiency survey or supervisor assessments).
Organizations can also consider how often they collect information so they can move beyond point-in-time measures to more frequent or continuous measures such as:
- Pulsing: Shorter, more frequent surveys that may include sampling the workforce rather than including the full population
- Life-cycle integration: Gathering data as it occurs—such as a new worker completing a survey posthire or real-time attrition metrics / trends updated information enters the HR system
- Always on: Harvesting data from virtual collaboration spaces that are organized via topic-based categories so workers can share what is working well or poorly
Muscle: How will insights gained be put into action?
A listening architecture should not overlook the need to translate the information gained into insights and actions. High-performing organizations have stronger basic data literacy skills within both people analytics resources and their broader HR teams, and they are much more likely to use automated dashboards and self-service reporting tools.1 These strengths aid them in understanding and analyzing data to gain insights and in getting those insights into the hands of those who need to act on them.
As organizations consider developing their listening architecture muscles, they can start with smaller weights. High-performing organizations are more than three times as likely as low-performing organizations to test a variety of different solutions.2 They don’t have to go right into large-scale enterprisewide efforts; rather, they can start small by testing analytical methods with a few functions or groups, then scale and adapt the leading practices.
Governance: How will listening be managed and improved?
Companies are facing the need to be agile, to quickly respond and adapt to change. A listening architecture can act as a sensing capability to continuously sense—and make sense of—what is happening inside and outside their borders.3 For this capability to operate effectively, it should be governed and continuously improved.
Governance can help the organization’s listening architecture to:
- Define scope.
- Create common data definitions.
- Establish roles and responsibilities (for collecting, managing, and acting on data).
- Monitor for data quality, security, and compliance.
- Improve operations (e.g., utilize new technology or features, automate data collection or analyses, personalize dashboards).
- Align to changing organizational needs (e.g., evaluating and adapting data practices to meet shifting priorities).
Accelerating the listening architecture
Taking these listening architecture considerations into account can help organizations sense the future, but creating the right listening channels, analyzing complex data, and scaling practices is a journey. The good news is that the growing field of people analytics solution providers can help make this journey easier.
More than 75 percent of surveyed people analytics solution providers offer capabilities on data management and reporting.3 Solution providers can also help in putting these insights into action: 88 percent offer results interpretation. Many also have advanced capabilities.4
- 47 percent offer sentiment analyses (identifying worker feelings / emotions through text analysis)
- 44 percent offer natural language processing (breaking up sentences to identify key words, parts of speech, or phrases)
- 41 percent offer network analyses (visualizing the relationships between workers)
The future doesn’t need to come as a surprise. Through a strong listening architecture that is empowered by people analytics technologies, organizations can sense trends and monitor scenarios to plan for whatever the future may bring.
What does the future hold for people analytics?
Organizations can better sense and navigate the future through an effective listening architecture, but what about the key questions surrounding people analytics itself? For example:
- What are organizations focused on solving?
- How are data skills changing?
- How is people data being governed and ethically used?
- What leading technologies and cutting-edge methodologies are helping organizations to realize impacts?
The future of work is here, and it’s more analytical than ever.
Take our High-Impact People Analytics survey (intended for leaders or individual contributors involved with people-related analytics) to receive an instant snapshot of how your organization compares with others and to be invited to a free webinar on key findings.
|Kathi Enderes, PhD, is a vice president and the talent and workforce research leader at Deloitte Consulting LLP. |
Zach Toof is a manager and people analytics research leader at Deloitte Consulting LLP.
|1 High-Impact People Analytics study, Deloitte Consulting LLP, 2017.|
2 High-Impact People Analytics study, Deloitte Consulting LLP, 2017.
3 Six Top Findings for Designing Tomorrow’s Companies Today, Deloitte Consulting LLP / David Mallon and Timothy Davis, 2019.
4 People Analytics Solutions: Market Capabilities and Differentiators, Deloitte Consulting LLP / Kathi Enderes, PhD, and Matthew Shannon, 2019.