Data is most powerful when presented in clear, concise ways to the people who need to see it. Data dashboards are about identifying who needs to see what data to inform their decision-making, and how data can be easily presented in a way that can be interrogated without too much peripheral clutter.
The time it takes for data to process is important too. For some decisions, presenting results made up of a huge number of data points that take time to process is important, but often dashboard data needs to be ‘live’ and readily available. This is especially key for telecoms and IT businesses.
We help you understand what data is really useful to inform decisions, and to construct dashboards to present this in an intuitive and easy-to-access manner.
Gathering huge quantities of data is becoming increasingly easy. Assessing the quality of that data, and being confident enough in it to make business decisions, however, can be more complicated. We look to assess the quality of different elements of the data sets, assign a weighting to them based on their quality, and identify any missing data that would add significant confidence.
Too much data confuses the situation and makes it harder to make concise, well-informed decisions. Identifying which data to report on, and to whom, is key to getting the best insights from it and enabling decision makers. Also important is defining from the start how judgements made against this data will be assessed over time so that you can continuously assess and improve accuracy. We work to build the plans and justifications around the data used.
Historical data is always key to identifying trends and helping to project patterns forwards. Identifying at what point data becomes too old to be useful, or how the weighting of data over time helps build accuracy and confidence in models and predictions is also important. Assessing historical data requires a holistic look at your data sets, ascertaining what variables (such as the sensitivity of sensors) may have varied over time.
Cunniffe & Helm are experienced in finding ways to present data in a meaningful and accessible manner. In particular, this may be for performance reports, marking information or board decision-making. We drill down into what the data really shows, what this needs to be related to, and who it is relevant to.
Extrapolating from trends in your own or externally sourced data is important for most business decisions. How trends are extrapolated from varies based on needs and experience. For some data sets, a mathematical approach to forecasting provides sufficient accuracy. For other data sets, it is vital that this is mixed with industry and business expertise. We work with key stakeholders to understand the environment and cases that the data and forecasts will be used in. For IT- and telecoms-related data sets, we can provide the expertise to inset human-generated weightings into forecasting algorithms.
At best, trend extrapolation and forecasting are always a ‘best effort’ based on a number of movable variables. We work from the start to assess the risk of inaccuracy in each data set and prediction, and to look at how we can test predictions against historical outcomes or tweak them as they are compared to actual outcomes.