We deliver a range of analytics services and typically work with our clients in one of three ways:
Consulting and training – information auditing, process mapping, developing key performance indicators, analytics training courses and workshops
Analysis and reporting – in-depth analysis, predicitive analytics and forecasting, scenario modelling, dashboard design, detailed reporting
Development and roll-out – project management, developing proofs of concept, dashboard development, engaging with users to support roll-out
Our work can be broadly summarised into three main categories:
Our performance management work helps clients to carefully design and track key performance indicators (KPIs) so that the board members and decision makers can have confidence that they are in control of their organisation.
The screenshot on the right is taken from a dashboard we have developed for the Together Housing Group. The highly visible traffic lights provide a very quick visual overview of performance over the five selected KPIs. These traffic lights are also broken down to show the performance of the individual regions, allowing for easy comparison of different parts of the organisation. The panel on the right-hand side of the screen helps to put the numbers on the left into context; the waterfall chart provides an efficient way of visualising the sources of lost income, while the table below it shows the actual amounts involved.
Our scenario modelling work aids decision making by allowing the user to explore numerous options and refine the underlying assumptions. We build our dashboards on financial models that can link into underlying financial systems.
As part of our work with Urban Splash, we designed a dashboard that let property developers gain insight into the potential financial impact of development schemes. Within the dashboard, the user is able to easily change the assumptions regarding cost and income so that a variety of "what if" scenarios can be run. This gives developers an invaluable understanding of the possible risks involved with different strategies.
The screenshot to the left shows another dashboard created for property developers, allowing them to evaluate the viability of a scheme. The user can set the size and rent of each type of property within the development, and factors such as yield, inflation and costs can also be adjusted. A series of output graphs are then created to give an insight into the relative benefits of buying or selling, along with a cash flow forecast.
More recently we have moved into the field of predictive analytics, of which forecasting is an integral part. Where the data is of sufficient completeness (i.e. time series going back several periods or well-understood explanatory variables), forecasting can provide a useful early warning system for the performance of a given metric.
To the right is a screenshot of a dashboard built for a social housing company. Using time series data going back four years, we have been able to forecast the performance of the metric over the next 12 months (orange line). Additionally, the forecast is re-run each month as new data becomes available; the updated forecast for the remaining months is shown in light blue. For context, we have also included the performance of the metric over the previous year (purple line) and the target (green line), which may be set within the organisation or anchored to external benchmarks.
The importance of such forecasts is that they give decision makers an understanding of which KPIs need the most attention. This is done by taking the focus away from seemingly high or low values that do not affect the end-of-year forecast; for example, variations due to regular seasonal effects, which are taken into account during the forecasting process.