A question such as “Would the proposed HS2 rail project represent the best use of government budget?” soon attracts a range of qualitative opinions. Analytical data modelling offers clearer answers around the quantitative results that can be expected and the extent to which problems are solved and created. Further, comprehensively answering the question requires more than simply deciding whether or not the proposal is a good idea, but considering the full range of possible alternative ways to invest in transport infrastructure for the UK. While this may sound like introducing far too many dimensions to an already complicated issue, analytics quickly shows the predicted result of any possible approach to a problem – or variant thereof – facilitating exploration of possibilities, through rapidly processing huge volumes of data. Thus it is possible to identify and propose only the best options in the first place.

While every investment proposal may reasonably claim to offer improvements to passenger service as well as economic returns, even the fact that a proposal is worth pursuing rather than not, doesn’t mean that it is worth pursuing over another option that hasn’t been considered. Current analytics technology allows thorough examination of all possible ways to solve a problem or optimise outcomes. e.g. how would investing in extra rail capacity for any of the routes into London improve extreme overcrowding?
(It could be argued that this process also makes the most worthwhile use of the political and PR effort required to stand up to public opposition.)

All organisations need to consider this kind of question all the time, generically; “How can we ensure we are investing our budgets in the best way?”, whether this be investing in new staff, equipment, product development, marketing campaigns or acquisition.
It is possible to predict the outcome of one particular possible investment, and decide whether to pursue it. With analytics, your organisation can ensure that the predictions on which decision are based are reliable (using your organisation’s data) and also that the proposals being considered are the best possible options.

An example of how the process works in practice, for a different kind of traffic is this demonstration of using Cognos Insight to analyse pedestrian flow in New York’s Times Square:

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You can download a trial for Cognos Insight, along with various data models here.

If you do have the trial installed, another demo to try, staying with the transport theme, is this data model for World Aviation Incidents.

The latest analytics visualisations and inspiration from IBM can be found at the Analytics Zone.

The official site for HS2 claims that the proposed project’s purpose is to increase capacity; http://www.hs2.org.uk/about-hs2/facts-figures/space-crowded-routes

Rail Statistics from Autumn 2011, from: https://www.gov.uk/government/organisations/department-for-transport/series/rail-statistics