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We address 3 questions: 1. What data do we really need answers for? 2. Why is a sound methodology critical? 3. Do metrics that focus on small but useful improvements make sense?

With business analytics, the toughest challenge is collecting data needed for questions one needs answered. My emphasis here is on:

– must-have answers, not – desired answers!

This is the third post in a series of entries about big data. Others so far are:

– Facebook mood study: Why we should be worried!
– Secrets of analytics 1: UPS or Apple?

New technqiues will not do

Often, we focus on predicting or forecasting the future. However, in management it is more important to understand the analytic HOWs and WHYs. These matter more than the promise of prediction. In the past we did not call things predictive analytics but forecasts instead. We used

– time series, as economists still often do, and – tried our luck with multivariate analysis (both part of what is called parametric statistics). These days, we still use the above methods. However, new ones have come to the fore, such as:

– k-means clusters, and – random graphs.

2014-09-08-EPFL-evolution-of-random-graph-Erdoes-Renyi

A random graph is obtained by randomly sampling from a collection of graphs.

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Continue reading “Scottish referendum: A false sense of precision?” »

KEY INSIGHTS
Why little data mean a lot: Incremental innovation is key.
Google Trends shows a spike in searches – iPhone6: Remember the flu trends? Increased searches do not make something a fact…
Constant experimentation and rapid implementation: Strive for lots of small and frequent advances, because that is good enough.

We address three questions

1. What does it mean when Google Trends shows a spike in searches?
2. Should we aim for lots of small wins from ‘big data’ that add up to something big?
3. Do metrics that focus on small but useful improvements make sense?

Get the latest news on your mobile
Subscribe to our award-winning blog: DrKPI – the trend blog

CLICK - Caution - things may not be as they appear. Check the methods.

1. ‘iPhone slow’ and Google Trends

There are three types of business analytics:

Descriptive analytics that look at historical data,
Predictive Analytics that try to determine what might happen, and
Prescriptive Analytics that focus on giving us different options, in which case we choose what we think suits us best, given time and money constraints.

The question remains whether we have the right data… To illustrate this challenge, we can look at the Google Flu Trends (GFT). Using search results from Google, the GFT supposedly indicates how the flu spreads and affects people in various countries.

Continue reading “Data analytics: UPS or Apple?” »