Predictive Behavioural Analytics (Fundamentals 1) is a two-day, practice-led training that equips change, HR and transformation professionals to use behaviour-relevant data as decision support in organisational change. Participants learn how to anticipate how different teams and employee groups are likely to respond to a change initiative, and how to translate these signals into concrete decision scenarios for communication focus, roll-out sequencing and targeted support.
Many organisations rely on dashboards and KPIs to monitor progress. These indicators remain essential, but they often lag behind emerging behavioural shifts and rarely explain why implementation progresses in one area and slows in another. Fundamentals 1 complements KPI reporting by adding a behavioural decision-support layer based on applied predictive analytics and behavioural science.
Participants work in the KNIME Analytics Platform, a visual, workflow-based analytics environment that enables end-to-end data preparation and modelling without writing code. The training follows a clear workflow from data exploration to first baseline predictive models, with continuous transfer into realistic change scenarios.
Day 1 – Foundations and data preparation
Day 1 builds the foundation for using predictive analytics as decision support in change. You learn how to frame practical change questions so they can be tested with data and how this perspective complements KPI reporting. Working through a continuous case study, you clarify which behavioural signals matter, what you want to predict in a given change situation, and what “good data” looks like in organisational settings.
You then prepare a behaviour-relevant dataset in KNIME for modelling. The focus is on creating a clean, decision-ready starting point: checking data quality, handling missing values, structuring variables, and setting up training and test data in a way that supports reliable analysis.
Day 2 – Baseline modelling, evaluation and interpretation
Day 2 moves from preparation to application. Building on Day 1, you create and interpret first baseline models in KNIME and learn what constitutes a reliable result in practice. Logistic and linear regression are introduced as robust entry-level models that estimate probabilities or expected values for what you want to predict in a given change situation.
You learn how to assess model performance using appropriate evaluation logic and how decision trees can support interpretability by making important predictors and decision rules easier to read. The final part focuses on transfer: translating results into concrete decision scenarios, such as where to focus communication and leadership attention, how to sequence roll-outs, and where targeted support is most likely to be needed.
Details for Fundamentals 1 
Training content:
- Predictive analytics in change: purpose, decision contexts and limits (descriptive vs predictive vs prescriptive)
- Preparing and exploring behaviour-relevant data in KNIME (data quality, missing values, encoding, feature selection)
- Building and evaluating first baseline models (logistic regression, linear regression) and assessing reliability
- Improving interpretability with decision trees and identifying behavioural drivers across groups
- Translating outputs into concrete change decisions (communication focus, roll-out sequencing, targeted support)
- Transfer to your own context using templates and a practical implementation roadmap
What makes it distinctive?
- a continuous case study that anchors every method step in a realistic transformation scenario
- real datasets and hands-on modelling in KNIME, without programming
- explicit focus on interpretation, model limits and responsible use in organisational contexts
- small-group format with high interaction and guided practice
Who is it for?
- Change Managers and leaders in Organisational Development
- Professionals and leaders from HR, People Analytics, People & Culture, L&D and transformation functions
- Consultants and Strategists focused on people-centred change
- Practitioners interested in behaviour-oriented data analysis in organisations
Learning outcomes:
After the training, participants can:
- translate change-related questions into analysable outcomes and behavioural hypotheses
- prepare behaviour-relevant data in KNIME for modelling (cleaning, encoding, feature selection)
- build and evaluate entry-level baseline predictive models and assess reliability
- interpret probabilities and behavioural drivers responsibly and apply results to change decisions
Early-bird plus:
The first three bookings for Fundamentals 1 receive an additional 10% discount on the early-bird price.
(To receive the discount code without creating a user account in the booking system, please send a short email before booking with the subject line “Discount Code Fundamentals 1 – Predictive Behavioural Analytics” and the relevant booking code to [email protected])
