This is a short article to explain to the wonderful people working in People Analytics departments everywhere, how easily and effectively you can incorporate Emotion Analytics software into your existing toolset. Or, at least, how easily Pansensic does it with our partners.
If you are one of those wonderful people but are not sure (a) what Emotion Analytics is, or (b) why you should care, please check out this short article.
Emotion Analytics software…extracts a new depth of understanding from human generated textual data
At Pansensic, we have developed Emotion Analytics software that is used daily by many industry-leading organisations to extract a new depth of understanding from human generated textual data. It turns human experience into accessible knowledge. It delivers a novel stream of metrics, trends, and evidence-based insights to add robustness and depth to your existing workforce analytics activities.
As with every step-change and switch to new technology or approach, there can be blockers that slow the transition. Blockers can be anything from concerns over software integration into existing systems, lack of planning, poor communication, failure to achieve key-stakeholder buy-in, and anxiety that the new software isn’t as good as the hype.
Working through these steps will result in effective and hassle-free integration of a new and highly valuable capability
The experience we have gained making this change and overcoming those blockers with our existing partners has been condensed below into four easy steps. Working through these four steps, with Pansensic as a highly collaborative partner, will result in effective and hassle-free integration of a new and highly valuable capability into your organisation.
We typically recommend a try-before-you-switch approach. This means you can run your workforce data through your existing analytics systems at the same time as you run it through ours. The ability to compare legacy systems with the new capability in a risk-free environment works well for both parties. The potential new user gets to sample our Emotion Analytics software and incorporate its output into the existing reporting mechanisms, which can then be distributed to the wider stakeholder community for assessment, feedback, and buy-in.
(It works very well for us too, as once the benefits of using Emotion Analytics software have been experienced, it’s very hard to go on without it).
The four steps to trial Emotion Analytics software across your workforce with Pansensic:
Step 1: Project Setup and Data Discovery
- Project Briefing – introduce internal stakeholders to project purpose and scope
- Business perspective – agree business context & parameters, key objectives
- Data evaluation – identify existing employee data, option to generate new employee data
- Data ETL – data formatted and uploaded to the Pansensic Emotion Analytics software
- Milestone: Finalised data file
Step 2: Data Processing
- Tagging – data is tagged by Pansensic software for emotions & employee categories
- QC – data is scored against 5 quality metrics (opportunity to improve future surveying)
- Auditing – refinement of NLP models to balance sensitivity vs accuracy
- Milestone: Pansensic data metric report
Step 3: Analysis and Learning
- Emotion analysis – review behaviour insights via insight platform (Pansensic or existing)
- Employee experience analysis – review insights across 48 business themes
- Insight Discovery – deep dive into workforce behaviour and drivers
- Milestone: High level prioritised insight report
Step 4: Storytelling
- Employee journeys –data-driven insight pathways explaining employee decision-making
- Improvement plan – evidence based & actionable suggestions provided by Pansensic
- System evaluation – Pansensic + partner assessment of project outcomes
- Milestone: Boardroom-ready report
From start, the full process can be delivered in as little as 2 weeks.
Should any wonderful people in People Analytics departments want to know more, we are always available for a friendly and informal chat. We can share our experience and discuss the 4 steps, which provide a low-risk approach to trial what will soon become industry standard capability.
Andy Crouch (UK + US)
Jan-Jaap Nijborg (NL)