What – Descriptive Analytics looks at past issues and describes them. This enables us to determine what happened in the past.
Why – A rarely defined form of analysis, Inquisitive Analytics looks at the ‘Why’ of ‘What happened’ and tells us, after the fact, why it happened.
When – Predictive Analytics uses the ‘How’ and the ‘Why’ in predictive algorithms and estimates the probability of something happening in the future.
Then – Prescriptive Analytics is the ‘So what?’ and the ‘Now what?’. The How, Why and When are fed into a multitude of business rule algorithms, multiple mathematical and computational modelling systems and will automatically synthesize hybrid data sets to answer not only ‘What’ will happen but (and this is what makes it special) ‘What’ needs to be done about it.
This form of analysis, which continuously and automatically tries to anticipate the What, Why and When of unknown future events, is truly going to be a game changer.
It is not hard to see the potential in this form of fledgling analytics. However, despite the massive potential, it is barely registering on the business analytics radar. In fact, according to Gartner, it is only being used by approximately 3% of organisations. ***
So why the disconnect? It could be that the availability of source data, along with the cost of this kind of analytics, has led to it being priced out of the reach of most businesses. However, the ever increasing expansion and availability of unstructured data (including video and audio feeds, machine data and social media streams) and the decreasing costs of hardware and software, means we may be on the verge of an exponential explosion in the growth market for Prescriptive Analytics.
That is the ‘buzz’ anyway. The reality?
Prescriptive Analytics is widely being touted as the final phase in the development of management analytics. Basically – if a business has a good grasp on what is happening (descriptive) and why (inquisitive) and a good model that can estimate future outcomes for various potential management actions (predictive), then it may be able to use an optimisation tool or model to search through various management actions for those that lead to better outcomes for the organisation.
In essence, integration of the Descriptive –> Inquisitive -> Predictive –> Prescriptive information chain is a key to the success of any business.
That being said, these tools do not passively estimate what is likely to happen given past trends. Rather they actively incorporate management decisions into predictions – predictions that can and will directly affect the bottom line as well as the Returnof Investment (ROI) of any business.
For example* – Prescriptive Analytics can aid strategic healthcare planning by not only predicting the potential for a seasonal flu/asthma/chest infection pandemic but also by determining what steps should be taken to mitigate the influx of patients – add more beds or employ more doctors, as well as showing the impact of each option.
Another example** is energy and utilities. Natural gas prices fluctuate dramatically depending upon supply, demand, econometrics, geo-politics, and weather conditions. Gas producers, pipeline companies and energy firms have a vested interest in more accurately predicting gas prices. In doing so, they can lock in more favourable terms while hedging their downside risk. Prescriptive Analytics can accurately predict prices by modelling both internal and external variables simultaneously while also providing optimal decision options and highlighting the impact of each decision option.*
The combination of Predictive and Prescriptive Analytics, in the hands of a skilled practitioner, can and will help businesses achieve both efficiency and effectiveness. The ability of business to understand the drivers behind customer buying patterns in order to anticipate the products customers want, the ability to optimise scheduling, production, inventory and supply chain design to deliver what customers and business want in the most optimised way – these are all achievable through Prescriptive Analysis. **
If you are one of those companies that is waiting until you have everything fully in place before you explore advanced analytics, in my opinion, you are waiting too long and you are definitely missing out. Discovering answers to questions that you hadn’t thought to ask yet – that is achievable now – with a little foresight, a little nerve and with a little Prescriptive Analytics!
*Predictive, Descriptive, Prescriptive Analytics – Anayliticbridge
http://www.analyticbridge.com/profiles/blogs/predictive-descriptive-prescriptive-analytics
**Prescriptive Analytics – A Step Beyond Predictive Analytics – Spotfire
http://spotfire.tibco.com/blog/?p=6170
***Prescriptive analytics is coming to a future near you – Search CIO
http://searchcio.techtarget.com/opinion/Prescriptive-analytics-is-coming-to-a-future-near-you
The post The ‘How’, ‘When’, ‘Why’… and ‘Then’ of Prescriptive Analytics appeared first on What Lies Beneath.
