Finance - Top Tips - Analysing Data

Analysing data

This document is designed as a quick reference guide to analysing data.

This will enable you to gain knowledge of a particular skill, task or process.

This means you can quickly find the key information that you need and refer to it on an ongoing basis whenever you need to refresh your knowledge.

Introduction

Analysing data is a skill that you can put to good use to help you to:

● Identify the key opportunities that exist to improve your business performance

● Identify factors contributing to a specific problem in your business

● Measure the effectiveness of an action you have taken

Finance - Top Tips - Analysing Data

What you need to know

Analytical thinking has been described as ‘the logic of turning of raw data into useful information.’ Some people will find that the ability to analyse data comes naturally, others less so.

Some basic guidelines you may find useful when analysing data are:

● Start with known facts and figures, not beliefs and assumptions.

● Check back to make sure you are looking at causes, not symptoms.

● Compare like with like. For instance, if you are comparing one period’s sales or profit with the same time last year, make sure it is the same week, and there were no variables such as Easter or half-term which affect one set of figures only.

● Avoid opinions unless and until these are supported by facts.

● Although ideas for conclusions may be welcome, they are only ideas.

● Dig deep and sift evidence for relevance. If something is not relevant, do not use it just because it points to a conclusion you like.

● Test your conclusions. You will often be able to draw more than one conclusion from your analysis; test each one to see if it is possible, probable, and relevant.

● Make sure all relevant information is included in your thinking, and no random but relevant factors have been omitted.

In addition to these generic guidelines there are a number of tried and tested analysis methods you could choose to apply depending on the nature of the information you are looking at.

SQ3R

A tool to help increase your retention of written information such as briefings, reports and books and get maximum benefit from the time you have available to read through information.

SQ3R is an acronym for the five stages of this technique:

● Survey – scan the contents of the document and look at the top line information it contains to decide whether it will be of any help. If the information isn’t useful, you can discard it at this point.

● Question – as you read, make a note of any questions that come to mind or any points that are of particular interest. Finding answers to these questions may form part of your action plan to move forward

● Read – Now read through the sections that you have highlighted as useful in detail. This may take a while if there is a lot of dense, complicated information. You may find it useful to take notes as you read.

● Recall – Run through what you have just read in your mind several times. Isolate the key facts or essential information and piece this together with any other information you have.

● Review – You can review what you have read by rereading the document and making additional notes or discussing the information with colleagues. One very effective method of reviewing is to pass the information onto to someone else e.g. briefing your team.

Finance - Top Tips - Analysing Data

What you need to know

Speed Reading

In a fast paced business environment such as ours you will often be required to take in large volumes of information in a short space of time e.g. daily updates and briefings on the intranet, store e-mails and financial reports.

Speed reading is a technique that can help you to work through all that information and quickly extract the essential facts.

N.B. If you find that you need to understand all the detail of the document you should not speed read it, in these instances it will always be necessary to read through it slowly and thoroughly.

As children, most people learn to read - either letter-by-letter, or word-byword.

As an adult, this is probably not the way you read now - think about how your eye muscles are moving as you read this. You will probably find that you are fixing your eyes on one block of words, then moving your eyes to the next block of words, and so on. You are reading blocks of words at a time, not individual words one-by-one. You may also notice that you do not always go from one block to the next: sometimes you may move back to a previous block if you are unsure about something.

A skilled reader will read many words in each block. He or she will only dwell on each block for an instant, and will then move on. Only rarely will the reader's eyes skip back to a previous block of words. This reduces the amount of work that the reader's eyes have to do. It also increases the volume of information that can be examined in a period of time.

Logged in as: Adam Bramwell

Finance - Top Tips - Analysing Data

What you need to know

Step by Step

A process for analysing an issue

1. Start by going back to the root of the issue; the sales figures, margin made, LTO, etc. until you reach data, which cannot be disputed. Make sure you are looking at the cause, not the symptoms.

At this point, avoid using conclusions that other people have reached from this data; they may well be flawed.

1. If necessary, take the data apart and examine how it was reached before accepting it as factual. For example, if a customer survey shows something to be true, would asking different customers have reached a different conclusion?

1. Weight the facts where necessary. For instance, if sales of waterproofs suddenly rose on a given week, the weather is more likely to have been a significant cause than an advertising campaign, although both would be relevant.

1. Sift and sort the data, and gradually re-assemble it, checking all the way that random or irrelevant data is identified as such and where necessary discarded, for instance unexpectedly high sales one day due to a power failure at a competitor’s store.

1. Compare like with like as outlined above.

1. Estimate a likely answer where appropriate; if your final answer is way out from this, check carefully you’ve not made an error of logic.

1. Form hypotheses. These are statements such as ‘Given the data, we have, is it safe to conclude that……?’

1. Challenge the hypotheses; if they stand up to examination, they may well be true. You should also challenge anyone else’s conclusions in the same way.

1. Weigh up the options and use your logic to decide which fits the facts best and is most likely to be correct.

1. Construct future hypotheses if appropriate, such as A could lead to B or C depending on D. This will assist forward planning. Remember however that these are only hypotheses until they happen.

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