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Analytics - can there be too much analysis?

Today we store endless data and thus there are many historic and real-time data to interpret. This chapter clearly illustrates that there are different ways of interpreting financial data, and how these may be categorized.

Analytics is the discovery and communication of meaningful patterns in data. Analytics relies on the application of statistical programmed analysis, often requiring extensive computation with algorithms and other mathematical tools.

Analytics is more than mere analysis, as the inference is that the data analysis will then be used as a base for forecasting to assist with decision making or recommend courses of action.

Here is one example from Google illustrating what they believe can be done:

Google analytics - Tag Management Made Easy

Want to focus on marketing instead of marketing technology? Google Tag Manager is the web's most popular enterprise-grade tag management solution for marketers and IT teams. It lets you add or update your website tags and mobile applications, easily and for free, whenever you want.

Data-Driven Attribution

Which digital channels are driving the business results you want? Our algorithmic attribution model gives you a complete and actionable view of the entire customer journey so you can make better marketing decisions and put your dollars into the areas that will yield the best return on investment.

(Google, 2013)

Just a word of caution, one definition of analytics is 'the science of logical analysis', but are all events logical? As mentioned in Chapter 7, some claim that there are no such things as coincidences or random events, that there is a logical explanation for everything. Random events do occur and can sometimes mask other events and their reported numbers. In today's world, we rely so much on computer processing and models that if we do not think in apparently illogical ways we may miss valuable opportunities or head for logical disaster!

Conclusion

Chapter 9 covers some of the principal aspects of management accounting and focuses on internal models and reports that assist in planning new strategies and delivering existing ones.

Points to check to ensure strategies are being fully but not over- reported:

- Ensure the integrity of management data - does it reconcile with financial data?

- Strategies and detailed tactics may be obscured by too much analysis.

- Decide what is sufficient detail for your reports.

- Ensure that reports lead to action.

Revision and learning pointers

You have access to your own company's reports, and while they may be considered perfect and in any case you may be unable to change them, a review of their style and effectiveness may reinforce the benefits of focused internal reports.

Points to check

First, ensure that your management accounting numbers are not disconnected in any way from the actual financial accounting results. With single-source databases of financial data this should not happen, but even with the most sophisticated and allegedly foolproof systems it may be possible to select data for a management accounting exercise detached from reality.

 
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