Data Analysis Methodology and Conventions IMS Consulting Group Training January 31 2012

Data Analysis Methodology and Conventions

IMS Consulting Group Training

January 31 2012

2

What this course is about

We will teach you how to make dynamic analyses with simple user interfaces to automate analyses

IMS Consulting Group Data Analysis Training - January 17 2012

• Simple user interface to select countries, drugs, therapy areas etc.

• Titles and labels update automatically

• Metrics are calculated instantly from the raw PADDS MIDAS extract

• Charts are updated automatically

3

What this course is about

More importantly we will teach you good practices to perform fast, accurate and insightful analysis of MIDAS sales data


1. Understand your therapy

areas and countries

2. Extracting data from

PADDS

3. Processing the data in

Excel

4. Making dynamic tables

5. Checking the analysis

5 Data Analysis Steps

4

Agenda


Introductions and course overview 8:30 – 9:15

Explanation of the ADHD market 9:15 – 9:30

Understand your therapy areas and countriesExercise: Answer questions about the ADHD market

9:30 – 10:15

Export from PADDS 10:15 – 10:30

Break 10:30 – 10:45

Process the dataExercise: Process data, link to datasets and update data for an existing file

10:45 – 12:15

Lunch 12:15 – 13:00

Make dynamic tables: basic functionsExercise: Create dynamic tables

13:00 – 15:45

Break 15:45 – 16:15

Make dynamic tables: user interface (forms)Exercise: Add pick-list interfaces to control the content of tables and charts

16:15 – 16:45

Check the analysisExercise: Hunt for errors

16:45 – 17:30

Wrap-up and feedback 17:30 – 18:00

5

Introductions

• Please say:− Your name

− Your office

− What you want to learn today


6

Training objectives

1. Improve the speed and efficiency of data analysis, allowing consultants to spend more time on value-added activities

2. Improve accuracy and reduce the need for rework

3. Introduce the good habits of documentation and structure to help reuse, update or revise analyses at a later date

4. Teach a set of standard approaches, so that work can be understood and reviewed more easily by others

5. Give confidence to the attendees that they have the skills to be resourced across the full range of IMSCG projects

We want to enable our staff to perform common analyses quickly and accurately


7

What you will learn

• A 5-step framework for undertaking MIDAS data analysis

• Things to look out for to understand sales data for therapy areas, drug classes and countries

• A recommended approach to pulling and processing MIDAS data

• New techniques:− Use of functions to create dynamic tables

− How to replicate tables for multiple countries / products

− Some simple user interface tools (forms)

• Standards for colours and formats that will improve consistency and readability across tools and projects

• Good practices to work cleanly, quickly and accurately

This course is designed to teach practical skills and good practices for sales data analysis


8

Data analysis steps

Today’s training is structured around 5 steps that are followed in almost all good MIDAS data analyses



areas and countries


PADDS


Excel




9

Training exercises

During the course of today, we will follow a set of exercises to extract data from PADDS and create analyses and user interface


PADDS Completed Analysis With User Interface

10

Project example

The techniques demonstrated today can be used to create more sophisticated client deliverables


11

Project example

More complex models still use the same principles


12

Course overview

Understanding your therapy area and countries of interest is vital to minimise errors later on in the process


1. Understand your therapy areas and

countries


PADDS


Excel



Learning objectives:• How to use MIDAS and other resources to understand the therapy area and countries of interest so that you are equipped to pull the data correctly from PADDS

Key activities• Review and discuss key questions to ask about the data and the resources used to answer them

• Quiz based exercise using MIDAS and other resources

13

Course overview

With good knowledge of the therapy area and countries of interest the data can be correctly pulled from PADDS


Learning objectives:• Best practice for pulling data from PADDS

Key activities• Review and discuss top tips for pulling data from PADDS


countries


PADDS


Excel



14

Course overview

Following the extract from PADDS, the data must be processed before it can be analysed


Learning objectives:• Good practice for processing MIDAS data in Excel

• Formatting conventions to improve consistency across projects

• Advice for how to work ‘cleanly’ and in a traceable way

Key activities• Review and discuss top tips and examples of best practice for processing data

• Practical Excel exercise to process a raw MIDAS extract


countries


PADDS


Excel



15

Course overview

Dynamic tables are a highly efficient and accurate way to analyse the processed data


Learning objectives:• Practical techniques to create dynamic tables in Excel

• Understanding of various different applications for dynamic tables and their power to save time and improve accuracy

• Simple user interface techniques

Key activities• Review and discuss top tips and examples of best practice for developing dynamic tables data

• 6 practical Excel exercises of increasing difficulty building dynamic tables and accompanying charts


countries


PADDS


Excel



16

Pivot tables

Pivot tables are an alternative way to create dynamic tables and are often a fast and effective analysis tool


Advantages of pivot tables:• Often very quick to set up

• Eliminates some kinds of errors

• Automatically eliminates rows for non-existant data*

Disadvantages of pivot tables:• Not appropriate for client deliverables as hard to format

attractively

• Not as flexible as setting up a table from scratch

• Charting forces a PivotChart (unless do a workaround)

• Long timeframes can be a pain to set up (e.g. 84 months of data)

*depending on settings

due to time constraints pivot tables are not covered in this course

17

Course overview

Once the analysis is complete the it is crucial to check you work for error


Learning objectives:• Gain awareness of the different sorts of error that can occur

• Lean various approaches for preventing, spotting and correcting the different sorts of error

Key activities• Review and discuss top tips and examples of best practice for error handling

• Exercises for spotting and correcting various errors

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• For example, in the chart below would you normally expect to see originals taking share away from generics?

• Perhaps looking at a more granular level might be a better analysis?

Looking for inappropriate analysis relies on spotting surprising trends

IMS Consulting Group Data Analysis Training - J anuary 17 2012


countries


PADDS


Excel



18

Agenda





9:30 – 10:15


Break 10:30 – 10:45


10:45 – 12:15

Lunch 12:15 – 13:00


13:00 – 15:45

Break 15:45 – 16:15


16:15 – 16:45


16:45 – 17:30


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ADHD Overview

There are three different types of ADHD, depending on which symptoms are strongest in the individual


• It is hard for the individual to organize or finish a task, to pay attention to details, or to follow instructions or conversations.

• The person is easily distracted or forgets details of daily routines

Predominantly Inattentive Type

Predominantly Hyperactive-

Impulsive Type

Combined Type

• The person fidgets and talks a lot. It is hard to sit still for long (e.g., for a meal or while doing homework). Smaller children may run, jump or climb constantly.

• The individual feels restless and has trouble with impulsivity. Someone who is impulsive may interrupt others a lot, grab things from people, or speak at inappropriate times.

• It is hard for the person to wait their turn or listen to directions. A person with impulsiveness may have more accidents and injuries than others.

• Symptoms of the above two types are equally present in the person.

Source: CDC ADHD Facts

20

ADHD Overview

ADHD is one of the most common neurobehavioral disorders of childhood


Percent of Youth 4-17 ever Diagnosed with Attention-Deficit/Hyperactivity Disorder: National Survey of Children's Health, 2007

Source: CDC State-based Prevalence Data of ADHD Diagnosis

• ADHD is usually first diagnosed in childhood and often lasts into adulthood

• In Europe the prevalence is lower than the US which may be explained by lower awareness and use of different diagnostic tools

21

ADHD Overview

Treatment for ADHD is a combination of medical and behavioural therapy


Molecule Trade Name

Stimulants• The best-known and most widely

used treatments

• Between 70-80 percent of children with ADHD respond positively to these medications

Methylphenidate

Ritalin, Ritalin LA, Ritalin SR, Concerta, Daytrana (patch), Metadate, Metadate CD, Methylin, Equasym, Medikinet

Mixed amphetamine salts (amphetamine & dexamphetamine)

Adderall, Adderall XR

DextroamphetamineDextrostat, Dexedrine, Dexedrine Spansule

Dexmethylphenidate Focalin, Focalin XR

Lisdexamfetamine Vyvanse

Non-Stimulants• First approved for treating ADHD in

2003. Medications seem to have fewer side effects than stimulants and can last up to 24 hours.

Atomoxetine Strattera

Guanfacine Intuniv

Commonly Prescribed ADHD Medications

22

Agenda





9:30 – 10:15


Break 10:30 – 10:45


10:45 – 12:15

Lunch 12:15 – 13:00


13:00 – 15:45

Break 15:45 – 16:15


16:15 – 16:45


16:45 – 17:30


23

1. Understanding your therapy area / countries of interest

Answering these questions will make sure that you pull the data correctly from PADDS


PADDS Pull & Export

• Have you included all the attributes that you need (e.g. Molecule List, ATC123 Corporation, Manufacturer, Country, Product, Int Product, Int Strength, Strength, Pack, NFC123, etc.)?

• Within the attributes, have you selected all of the molecules, countries, forms etc. that you need?

• Have you included all of the measurements that you need (e.g. Sales, LC Sales, Standard Units, etc.)?

• Have you selected the correct time units (e.g. QTRs, Months, Years, MATs, etc.) and timeframe?

Key therapy area questions

Key country questions

Purpose of the analysis

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Example therapy area questions

Sources

MIDAS

sales data

BNF / Mimms

/ Prescribing

Information

Wikipedia / Desk

research/ Xchange

Knowledg

e Link

MIDAS

Medical

Is all treatment drug related?

Does the ATC class define the market or do you have to create a bespoke definition?

What are the key molecules / products?

Do they have multiple indications (e.g. asthma & COPD, epilepsy & neuropathic pain)?

Which of the products have generics?

How directly do the products compete (e.g. same line of therapy or not, some products used only in combination)

What are the different strengths available?

What formulations are you dealing with (e.g. all oral solids, extended release, IV, patches, etc.)?

What are the dosing regimens (e.g. QD, BID, once weekly)

Are there any licensing deals / multiple brands / co-marketing agreements you should be aware of?

Unless you've worked in the therapy area before, read up on it before diving in


25


Some useful resources


• Disease Primers can often be found on Xchange

26




27




28


With a couple of PADDS pulls you can learn a lot


29


Key country questions Resources

Which panels are available in PADDS (e.g. hospital, retail, other)?

• CAD sheets (available on the IMS portal)

• IMS Market Prognosis

• PADDS

• Previous projects

Are other panels available locally (and are they necessary)?

What is coverage of the data?

Are your products sold through a channel that is not covered (e.g. homecare for some biologics)?

In what setting will this therapy area be treated in this country?

Which important PADDS attributes are missing / unassigned in this country (e.g. generic classification)

Make sure you are familiar with the data coverage in your countries of interest


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Exercise 1

To familiarise yourself with the therapy area and ensure that your PADDS extraction is appropriate, carry out the following exercise


Exercise 1• Consider Brazil, Italy, UK, US only (all panels)

• Using PADDS, answer the following questions:

1. What drugs (molecules) are available in ATC N6B0 in each country?

• IF YOU HAVE TIME: which of these should be used in our drug class definition for ADHD? (search the internet – not MIDAS for this task)

2. What formulations are available in each country?

3. What products have generic versions in each country?

4. How many strengths exist for oral methylphenidate in the USA?

How do the strengths relate to the formulation?

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Agenda





9:30 – 10:15


Break 10:30 – 10:45


10:45 – 12:15

Lunch 12:15 – 13:00


13:00 – 15:45

Break 15:45 – 16:15


16:15 – 16:45


16:45 – 17:30


32

2. Pulling data and exporting from PADDS

Some top tips for pulling and exporting data from PADDS


Top tips Why important

For global sales figures, select all countries and deselect “All others”

• For global sales figures, select all countries and deselect “All other”

Set up your default layout to absolute values instead of thousands

• Rounding errors for low-volume drugs cause severe problems• A bit complex, but you only have to do it once for each database

Don’t export price – calculate it in Excel

• Very often you will adjust class/product definitions etc. and need to re-calculate prices anyway• Can get rounding errors for very cheap drugs

Save your queries • You’ll often have to adjust and re-run your fetches

Pull everything at once • If in doubt add extra products and detail – you can always eliminate and roll things up in Excel• Recoding, custom grouping etc. is typically faster and more flexible in Excel than PADDS

Often LC or “local currency” sales are required

• “Local Currency” means “at constant exchange rate”• Do not use the words “LC” or “Local Currency” in any presentations

For volumes most often SUs or “standard units” are required

• Pulling “Units” will pull out packs

Always export at “flat lowest level only”

• Pulling by hierarchy can cause problems with duplication of data

33



• Pull “everything” at once

• Be sure to remove “all others” for global sales estimates

34



• Switch Layout to Absolute

• Pull “Local Currency” Euro/USD for a constant exchange rate

35



• To change the layout default to absolute, select Layouts in the Report menus and then select “IMS Standard (absolute)”

• You have to change this in each database – monthly, quarterly and medical

36



• Always export as “Flat (only lowest level)”

37


• Your European client has defined your ADHD molecule market of interest as:

− Amphetamine & dexamfetamine

− Methylphenidate

− Dexamfetamine

− Atomoxetine

The client has provided us with the following definition with which to investigate the ADHD market


• We have extracted 12 years of quarterly Standard Units and Sales (Mfn) Local Currency*

• The following attributes were used to define the rows:

− Country combined

− Mol list

− Mol count

− Int prd

− Corp

− NFC123

− Gx Product Class,

− Int strength

• The client would like to compare the following countries:

− Italy

− UK

− USA

− Brazil

*”Local Currency” means at constant exchange rate

38

Agenda





9:30 – 10:15


Break 10:30 – 10:45


10:45 – 12:15

Lunch 12:15 – 13:00


13:00 – 15:45

Break 15:45 – 16:15


16:15 – 16:45


16:45 – 17:30


39

3. Processing the data in Excel

Important tips for data processing


Tip tips Why important

Maintain the integrity of the original data – do not insert columns into the middle of the raw data

• Keep the data untouched in its original form, so that it can be copied back in / adjusted with new data if required• It’s a good idea to keep a pristine copy of the original pull in your workbook so that you can refer back to it

Do not have additional tables (e.g. for lookups) on your main data page

• These run the risk of being deleted if rows are added to / deleted from the worksheet

Create calculated variables and “key” variables in new clearly-identified columns next to the raw MIDAS data

• This makes for a clear workbook and enables good auditing without having to move between sheets too much

Keep as much as possible of your analysis live

• This is important for saving time and effort when updates need to be made• Reduces the chance of user error if analysis needs to be recreated• Allows the development of dynamic tables

Where possible use functions to categorise the data (IF, text functions etc.)

• To save time and improve accuracy

Use colour standards • Helps with clarity and auditing

Don’t use: array formulae or subtotals • Not widely used or understood by others, therefore don’t help with auditing

Pivot tables ok to use and can be useful, but have their drawbacks

• Can be a very quick way to carry out the analysis• Not appropriate for client deliverables as hard to format attractively• Not as flexible as tables

40


Type Example Meaning

Formatting conventions

Black text on white Original data column (i.e. no special formatting)Black text on light yellow

Input cell

Black text on light blue

Linked / calculated column header

Black text on green “Key” column header 2,000 (red text) Dummy inputs2,000 (black text) Final inputs

RangeName (italics)Label of named range (usually as column header or beside a row)

Sticking to certain formatting standards will allow others to understand your work faster


41


Type Example Meaning

Naming conventions

mmm-yy (e.g. Jan-11)

Format of months

B, M, k Billion, Million, Thousand$, €, £ US Dollars, Euros, UK Pounds

CHF, EGYUse ISO 4217 3-letter abbreviations http://www.currency-iso.org/iso_index/iso_tables/iso_tables_a1.htmLipitor Brand names start with capital letters

atorvastatinINN names are not capitalised unless at the beginning of a sentence

UK, GBR

Use the official ISO 3166 2-letter abbreviations: http://www.iso.org/iso/country_codes/iso_3166_code_lists/country_names_and_code_elements.htm)

or the UN 3-letter abbreviations: http://unstats.un.org/unsd/methods/m49/m49alpha.htm



http://www.currency-iso.org/iso_index/iso_tables/iso_tables_a1.htm

http://www.currency-iso.org/iso_index/iso_tables/iso_tables_a1.htm

http://www.iso.org/iso/country_codes/iso_3166_code_lists/country_names_and_code_elements.htm

http://www.iso.org/iso/country_codes/iso_3166_code_lists/country_names_and_code_elements.htm

http://unstats.un.org/unsd/methods/m49/m49alpha.htm

42


TypeConfusing Language

Better Language

Rationale

Language conventions

Market“Country” or “Therapy Area” or “Drug Class”

“Market” is non-specific

“LC dollars” or “Local currency dollars”

“USD at constant exchange rate”

“Local Currency” is a non-obvious name and not understood by many clients

“Share”

“Share of Molecule Volume” or “Share of ATC Sales”

“Share” is not specific enough without additional definition

“Sales”“Value sales” or “Volume”

Some people use the word sales to mean both value and volume



43


It is vital to maintain the integrity of your original data in case you need to quickly update it at a later stage


×• Do not insert columns into the middle of your data

• Insert any new columns to the right or left

44


Simple relationships between the sheets improves readability and auditing


Data Sheet(s)

Analysis Sheet(s)

Lists & Selections

Sheet

Data Sheet(s)

Analysis Sheet(s)

• This structure is bad because tracing

calculations has you jumping back and forth between sheets which makes the task much more complex

• Elements such as selections and lists are harder to find because they don’t have a ‘home’

Simple relationships among sheets Overly complex relationships among sheets

• It is good to have lists and selections on a separate sheet to make them easier to find and maintain good structure for the workbook

45


Create calculated variables and “key” variables in new clearly-identified columns next to the raw MIDAS data


• “Key” variables are useful for “rolling-up” data into custom groups and form the building blocks for the dynamic tables

• Create key variables in your data sheet and then use formulas such as SUMIF to group the data together

• In this example, all the sales for a particular molecule-form have been summed

Data sheet

Output sheet

46


Creating custom groupings and “key” variables requires a good knowledge of different text functions


CLEAN Removes all nonprintable characters from text

CONCATENATE or & Joins several text items into one text item

FIND Finds one text value within another (case-sensitive)

LEFT Returns the leftmost characters from a text value

LEN Returns the number of characters in a text string

LOWER Converts text to lowercase

MIDReturns a specific number of characters from a text string starting at the position you specify

PROPER Capitalizes the first letter in each word of a text value

RIGHT Returns the rightmost characters from a text value

SUBSTITUTE Substitutes new text for old text in a text string

TRIM Removes spaces from text

UPPER Converts text to uppercase

47


• IF(logicalExpression, valueIfTrue, valueIfFalse)− LogicalExpression can be any valid Excel expression that evaluates to TRUE or FALSE

(e.g. A1 > 0).

− ValueIfTrue is the value that is returned if logicalExpression evaluates TRUE.

− ValueIfFalse is the value that is returned if logicalExpression evaluates FALSE.

• IF statements may be nested up to seven layers deep. For example, the following expression returns ‘Yes’ if A is greater than zero and less than 10 but not equal to 5.

− IF(A1 > 0, IF(A1 < 10, IF(A1 = 5, “No”, “Yes”), “No”), “No”)

The IF function returns one value if its logical expression evaluates to TRUE and another value if it evaluates to FALSE


48


• Days of therapy (DOT), also called treatment days (Tx days), is an important and commonly used volume measure

• It is critical to use when the therapy area has multiple forms and/or dosing regimens, since 1 standard unit is not always comparable between products

• Days of therapy = Volume (in SUs) / average (or defined) daily dose (in SUs per day)

Calculating days of therapy is a common part of processing the data


49

Exercise 2

Exercise 2a

• Open file “DA Training Exercise 2a Complete Data Tables v_.xls”− Instructions are in the Excel file

− A completed example is in the Excel file for Exercise 2b

Exercise 2b

• Open file “DA Training Data Sources ADHD Sales.XLS”

• Open file “DA Training Data Sources ADHD AVDD.XLS”

• Open file “DA Training Exercise 2b Extend Data Tables v_.xls”− Instructions are in the Excel file

− A completed example will be given to you

Now that you have extracted your data, there are various processing tasks to be completed before it will be ready to analyse


50

Agenda





9:30 – 10:15


Break 10:30 – 10:45


10:45 – 12:15

Lunch 12:15 – 13:00


13:00 – 15:45

Break 15:45 – 16:15


16:15 – 16:45


16:45 – 17:30


51

4. Making Dynamic Tables

• They are much faster when analysing multiple countries, products etc.− With practice, a single dynamic table takes only slightly longer to create than a non-

dynamic table

− A dynamic table can be adapted very quickly to analyse different countries, products etc.

• They reduce errors − Avoids errors that inevitably occur when people do repetitive tasks

− Allows better audit and trace when errors occur or changes are required

• They can be quickly formatted to into client-ready tools and deliverables

• They are more fun to create

Dynamic tables improve the speed, accuracy and replicability of data analysis


Benefits of dynamic tables

52


A particularly poor method would be to use individual SUM formulae which have to be defined manually for each country and indication


This table is not dynamic×

• Individual sum formulae with manually defined ranges have been used

• The means that a new formula would have to be written for each country and each indication

53


Make sure that the selection criteria in your SUMIF formulae are not hard coded


This table is not dynamic

• The main SUMIF formula uses a hard coded selection criteria (“GERMANY RETAILAsthma”)

• The formula will need to be manually updated to select the data relating to a different country

×

54


Dynamic tables should update when the source data is changed and should have the flexibility to select different categories of data


This table is dynamic, will update when new countries are added into the data, and will update when different countries are selected

• The main SUMIF formula in the dynamic table feeds off a dynamic lookup cell• Data relating to new countries can be added to the analysis without the need

to update the formula in the table• The table will also update when different countries are selected

55


Useful tips for creating dynamic tables


Tip tips Why important

Use formulae to keep the analysis live

• So that the tables will update when different criteria are selected• So that tables will update when new data is added

Add new data by inserting rows in the middle of existing formulae ranges

•This means that the ranges of the dynamic formulae will automatically extend to accommodate the new data

When replacing data that is fewer rows than the original data always delete the extra rows

•This ensures that the formulae in your dynamic table remain correct

Don’t hard code the selection criteria

•Keep them dynamic

Use forms rather than validation lists to create drop down lists

• They are more flexible and importantly more visible to the end user• Can quickly be copied to other sheets

Use some named ranges and other names

• This helps to simplify formulae and makes auditing easier

56


The SUMIF function is very commonly used in dynamic tables for shares as well as totals


• In this example the $’s are used to fix all the ranges except:• the country changes with the table row• the sales year changes with the table column

• To calculate shares or prices, simply divide two SUMIF functions within the same formula

• To calculate averages, divide a SUMIF function by a COUNTIF function within the same formula

Example of a SUMIF function to complete a dynamic table

57


It is a good idea to use some simple Excel names for cells and ranges to simplify formulae and make the workbook more auditable


• Naming important columns is helpful as it allows formulae to be simplified and quicker to understand for other users

58

Exercise 3

Exercise 3a

• Open file “DA Training Exercise 3a Dynamic Tables v_.xlsx”− We will work through this exercise together before moving on to Exercises 3a-3e

− Instructions are in the Excel file on the sheet “Exercise 3a”

− A completed example is in the Excel file for Exercises 3a-3e

Exercises 3a-3e

• Open file “DA Training Exercise 3b to 3e Dynamic Tables v_.xlsx”− Instructions are in the Excel file

− It is likely you will not have time to complete all 4 tasks


In these exercises you will analyse value sales by molecule form, share of market volume and generic penetration by molecule


59

Agenda





9:30 – 10:15


Break 10:30 – 10:45


10:45 – 12:15

Lunch 12:15 – 13:00


13:00 – 15:45

Break 15:45 – 16:15


16:15 – 16:45


16:45 – 17:30


60


To insert forms first enable the Developer Tab then select Insert Form Controls


• First enable the developer tab in Excel Options first

• Then, on the Developer tab choose Insert

61


Forms controls can be used to set up pick lists for intuitive user interface


• In this example we want to add a pick list to put the selected name in the blue cell

Example - Objective

62


The pick list can be set up in three simple steps


Example - Steps1. Draw a combo box from the Forms toolbar and right-click on it and select

Format Control.2. Enter the list of names as the input range: $C$5:$C$9 and enter the purple box as the

cell link: $C$43. Put an INDEX function in the green box to return the name selected:

=INDEX($C$5:$C$9,$C$4).

1

2 3

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As a result, both the value and the number of the selection are populated in the appropriate cells


• The name selection box now controls yellow cell, which controls the green cell.

Example - Result

64

Reasons to use Excel Form Controls for pick lists:• Can link multiple pull-downs to the same cell• Is very obvious to anyone using the file that there is a pick-list vs. data validation looks

like a regular cell• Can link to a list on another sheet without having to name the range

Reasons to use Validation for pick lists:• Is very efficient if doing many cells with the same list of choices (can copy and paste)


In most cases Excel Form Controls are better than using the Validation functionality


A Forms control is always visible

Validation is visible only when you click on the box

Note: to use Validation with a list on a different sheet, simply name the range for the list and use the name instead of he Excel ranges

65

Exercise 4

Exercise 4

• Open file “DA Training Exercise 4 Forms v_.xlsx”− Instructions are in the Excel file


Now that the data analysis is complete, your can make it more client friendly by adding user interfaces


66

Agenda





9:30 – 10:15


Break 10:30 – 10:45


10:45 – 12:15

Lunch 12:15 – 13:00


13:00 – 15:45

Break 15:45 – 16:15


16:15 – 16:45


16:45 – 17:30


67


There are various categories of error to be aware of


CATEGORIES OF ERRORS

Excel Errors

• Errors in the calculation logic that cause Excel Errors:

• #VALUE• #DIV/0! • #NAME• #N/A• #REF! • #NUM!

Logic Errors

• Errors in the calculation logic which provide a number but not the one that was intended

MIDAS Errors

• Coding errors

• Low coverage

• Errors in the data itself

Inappropriate Analysis

• Does the analysis answer the right question?

• Has it been carried out at the right level of granularity

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Different tools and techniques help you correct errors



Follow the error messages ‘upstream’

• This will allow you to trace the error back to the first cell where it occurs and identify the source

Use charts to visualise your outputs

• Charts are quick to create and are the fastest way to spot surprising / suspicious trends in the data

Use the Formula Auditing tools and Evaluate

• These are very useful for tracing back errors in logic

When manually checking a large data table, look for errors at the bottom right

• Most of the time you are looking at the top left of the table and will spot errors as you work – ones at the bottom right are seen less often and more likely to slip through

Be on the lookout for errors that give plausible results and perform additional checks

• Not all errors will be immediately visible thanks to an Excel message, some errors (e.g. logic errors & inappropriate analysis will require more thorough checking)

When using look up functions be sure to indicate “exact match”

• Not typing 0 or FALSE at the end of lookup functions is a common mistake and results in incorrect matches

69


Good working practices and a focus on answering business questions will help you deliver a quality analysis



Ask someone else to review your work

• You can become ‘blind’ to obvious errors that someone with ‘fresh eyes’ can spot

Work cleanly • Good working habits and avoiding shortcuts will help you avoid errors in the first place and will speed tracing and correcting errors when they do occur

Trust your gut if something looks wrong and investigate until you are satisfied

• Just because you’ve traced a clean analysis all the way back to the MIDAS database doesn’t mean it’s correct – MIDAS (or your interpretation of MIDAS data) may be wrong

Ask yourself if the analysis addresses the business question

• Even if it is what was specified, if the analysis isn’t right, it will need to be changed – better you identify this than your project leader or your client

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• The formula auditing features can be found on the Formula tab

Formula auditing features can be used to uncover and correct most types of error


• Trace Precedents / Dependents allows you to visualize which cells are up/down-stream of a particular cell in a chain of calculations

• Trace Precedents / Dependents and Evaluate Formula are particularly useful features

• Evaluate formula allows you to run through a complicated formula step by step so you can trace the source of the error

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• The Excel error message gives you a big clue about how to fix the problem.− #VALUE! - the wrong type of argument or operand is used

− #DIV/0! - a formula divides by 0 (zero)

− #NAME? - Microsoft Excel does not recognize text in a formula

− #N/A - a value is not available to a function or formula

− #REF! - a cell reference is not valid

− #NUM! - a problem occurs with a number in a formula or function

− #NULL! - an intersection is specified of two areas that do not intersect

• The Excel Help database contains more information on how to correct these errors (see topic “Troubleshoot formulas and error values”)

• Locating the problem is usually a matter of going “upstream” to the source of the error

− Excel shows an error message in the cell causing the error and in every “downstream” cell.

− Start from the result cell and work backward, looking for the first occurrence of the error message.

Correcting Excel errors is usually straight-forward


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Functions for handling errors

The IF function has many applications but is often used in conjunction with other functions to handle errors

IMS Consulting Group Excel Training - January 9 2012

• The IF function returns one value if a condition you specify evaluates to TRUE, and another value if that condition evaluates to FALSE

• Use the syntax: IF(logical_test, value_if_true, value_if_false)

• Logical test: Required. Any value or expression that can be evaluated to TRUE or FALSE

• value_if_true Required. The value that you want to be returned if the logical_test argument evaluates to TRUE

• value_if_false Optional. The value that you want to be returned if the logical_test argument evaluates to FALSE. Returns a FALSE if no value is entered

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The ISERROR function can be used in conjunction with the IF function to perform a different action if an error occurs


• The highlighted cell returns an error because the calculation divides by zero

• Use ISERROR in conjunction with IF to return a specific value in case an Excel error occurs

• Note: this is can be used as an alternative to IFERROR (which does not work in Excel 2003)

• ISERROR provides the logical test component of the IF function

• In the formula above if C5/D5 returns an error then ISERROR returns a TRUE result

• The IF function can be use to return a zero if the logical test is TRUE and the original calculation if the test if FALSE

Logical test Value if TRUE Value if FALSEPrice = Sales /

Volume

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The TYPE function can also be used to handle errors in the same way



• TYPE function identifies the type of value that appears in an Excel cell

• If TYPE is used on a cell with an error it returns the value 16 (other values are returned for other cell types)

• The same formula as before is used except that the TYPE function replaces the ISERROR as the logical test

• In this case the logical test will also return a TRUE because the TYPE function will return 16 due to the #DIV/0 error

Price = Sales / Volume

Logical test Value if TRUE Value if FALSE

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IFERROR is the most efficient way to handle errors but is not available in Excel 2003



• IFERROR combines the IF and ISERROR functions to simplify the formula

• Use the syntax:IFERROR(value,value_if_error)

• The calculation only has to be entered once and if error will automatically revert to the value if it does not generate an error

Price = Sales / Volume

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To avoid untidy looking charts (particularly for price) you can replace the #DIV/0 error with a #N/A error using the NA function


• Using the NA function as the value to display in case of error allows you to convert all #DIV/0 errors to #N/A errors

• #DIV/0 errors appear on an Excel chart as a 0, which is confusing on a pricing chart

• #N/A errors do not chart at all, which makes for a more sensible looking chart

×

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Be sure to select and “exact match” when using lookup functions


• By typing a 0 or FALSE as the final component of the vlookup formula an “exact match” is selected

Or

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When a formula refers back to its own cell, either directly or indirectly, it creates a circular reference – by default these are turned off in Excel


• This cell in the total line is now both:

• the result of calculations in the using the cells below

• used to calculate the cells below

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Exercise 5

Exercise 5a – Excel Errors

• Open file “DA Training Exercise 5a to 5b Error Tracing v1.xlsx”

− Instructions are in the sheet: ‘‘Ex 5a (excel error)’’

− The answer will be discussed with the class


Before any analysis can be handed over to a client, or used to create presentation material, it must be checked for obvious Excel errors

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• Manually trace the calculations for a representative cell or set of cells – are there any unexpected results?

• Create and examine a summary chart to look for interesting or surprising trends

− Surprising trends may mean a logic error or could be a result of inappropriate analysis (e.g. a lower level of granularity may be required to uncover the true story)

Finding logic errors calls for sharp eyes and a keen mind


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Exercise 5

Exercise 5b.1 and 5b.2 - Logic Errors

• Open file “DA Training Exercise 5a to 5b Error Tracing v1.xlsx”

− Instructions are in the sheets: ‘‘Ex 5b.1 (logic error)’’ and ‘‘Ex 5b.2 (logic error)’’

− The answers will be discussed with the class


Errors in formula logic must also be eliminated otherwise the analysis could lead to the wrong conclusion

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1. Coding errors – where certain products have been miscategorised (e.g. generic products labelled as original and vice versa)

2. Low coverage – where the sales for a particular product look particularly low because the data is not being picked (this could be for a variety of reasons)

3. Errors in the data itself – often caused by problems with IMS’s various data suppliers (e.g. in one month a supplier may not deliver any sales data, leading to a drop in sales for particular products)

There are three main categories of MIDAS Error to be aware of

• Adjust coding errors with manual corrections or fomulae

• Use the CAD sheets to check data coverage

• If all else fails contact the MIDAS help desk

• Sometimes we must accept that certain analyses are simply not possible


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Exercise 5

Exercise 5c – MIDAS Errors

• Open file “DA Training Exercise 4 Forms v_.xlsx”

− Find the product that is classified as neither an original nor a generic product (in sheet ‘‘ADHD Sales Data’’)

o Why might this product have a non-specific classification in MIDAS?

o If we were to re-classify this product, would you recommend to re-classify it as a generic or as an original product, and why?

o How could we implement the re-classification?


Sometimes the errors will be the result of MIDAS data, these must also be removed

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Exercise 5

Exercise 5d - Inapproproate analysis

• Examine the chart below from the answer to Exercise 4.− What is the question being asked?

− What does the chart mean? How would you interpret it?

− What could be causing the deviations in the line (red arrows below)?

− How could we change this analysis to give better insight into the originals’ share?


Finally, before the analysis is handed over, you must be sure that it answers the business question at hand

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Agenda





9:30 – 10:15


Break 10:30 – 10:45


10:45 – 12:15

Lunch 12:15 – 13:00


13:00 – 15:45

Break 15:45 – 16:15


16:15 – 16:45


16:45 – 17:30


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What have you learned?

• 5 steps to consider when undertaking MIDAS data analysis

• Things to look out for to understand sales data for therapy areas, drug classes and countries

• A recommended approach to pulling and processing MIDAS data

• New techniques:− Use of functions to create dynamic tables

− How to replicate tables for multiple countries / products

− Some simple user interface tools (forms)

• Standards for colours and formats that will improve consistency and readability across tools and projects

• Good practices to work cleanly, quickly and accurately

We hope you have learned practical skills and good practices for sales data analysis


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Data analysis steps

Remember to consider all 5 steps in your work plan for MIDAS data analysis



areas and countries


PADDS


Excel




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Action Planning

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Documents

Data Analysis Methodology and Conventions IMS Consulting Group Training January 31 2012