At Decision City, we utilise creative and customised methods that tailor our work to the client’s environment to the maximum.

We use a mix of analytical methods to resolve problems based on issues identified, following effective understanding of issues affecting client’s performance. These methods include:

  • Cluster analysis – used in market research
  • Factor analysis – used in quantitative studies to evaluate dependent and independent issues.
  • Decision Tree analysis – used in examining probabilities of events (losses or profits) occurring
  • Machine or Autonomous Learning – using software algorithms to facilitate findings
  • Regression analysis – used in evaluating a dependent issue against one or more independent issues
  • Multivariate analysis – used in evaluating one or more statistical outcomes
  • Correlation analysis – used in visualising the relationships between issues
  • Segmentation analysis – used in evaluating and grouping customer behaviours
  • Sentiment analysis – used in identifying and categorising opinions expressed in written texts
  • Simulation analysis – used in evaluating change
  • Time Series analysis – used in evaluating demand against time in demographic studies

At Decision City, a mix of methods are utilised in problem analysis and solution modelling, using the following five analytics structure:

  1. Descriptive analysis
  2. Diagnostic analysis
  3. Predictive analysis
  4. Prescriptive analysis
  5. Adaptive and autonomous analysis.

We invite you to discover value with us!