This is a guest post by Chandeep. He won our recent dashboard contest and kindly agreed to share the technique and process for creating such an awesome dashboard with all of us.
Hi to all the awesome people at Chandoo.org
Quick Intro – My name is Chandeep Chhabra and I live in Gurgaon, India. Luckily Chandoo’s 2016 Dashboard contest, my Dashboard entry was picked up as a winning entry. Thank you so much for all your appreciation and likes
A few days later I reached out to Chandoo asking him to let me write everything about this dashboard, right from the thought process I followed to finally making a ticked and tied dashboard.
What I am going to cover in this post ?
Since we are talking about an entire dashboard here, this is going to be a long post (I mean really long). Here is what I plan to cover
- How did I plan this Dashboard ? – All my Dashboard pre-work is included here
- How did I create the Dashboard – This all about number crunching, formula writing, setting up things etc.. I am not going to discuss the formulas in detail but I will give you the overall logic and the formula behind it. To make things structured I have divided this part into 2 main sections
- Screen 1 Calculations – Everything about the 1st screen (company comparison)
- Screen 2 Calculations – All about screen 2 (overall market)
- How did I format the Dashboard – I discuss everything right from colors themes to the overall look and feel. Again the formatting is divided into 2 sections
- Screen 1 Formatting
- Screen 2 Formatting
- How much time did I spend creating it – Specific breakdown into hours for each section
- Mistakes that could have been avoided – A few mistakes that I personally found in my work that could have been avoided
Alongside this post, I have also put together a video to explain this dashboard you can get the video + resources here
Part 1 – How did I plan this Dashboard !
The first glance at the data made me feel comfortable, since I carry a finance background and have mostly played with financial data. So I came with 2 key objectives
- My dashboard has to answer all important questions that were relevant to the audience/management
The look and feel of the dashboard has to be simple and yet stunning - I am going to breakdown the objective into concrete actionable steps that I took to finally complete this dashboard + throw in some general good practices that I personally follow
Quick Tip: I draw from Chandoo’s 10 step Dashboard Process with a few tweaks of my own
Gathering all important and relevant questions
Chandoo did give us a good head-start about objectives of the dashboard
I also reached out to a few friends and asked them, what additional things would they like to know from the data. The list got a bit bigger. This is exactly what I came up with
I then started quickly crunching numbers and doing analysis to find the answers to the above questions. Once I did all the meaningful calculations, I quickly made a rough sketch (mock) of the dashboard. This mock is to understand 2 things
- How am I going to fit all this data and analysis in the sheet?
- How the overall picture will look like?
Below is how the mock up looked!
Part 2 – How did I create this Dashboard ?
Even before I start showing the workings of the dashboard I strongly suggest you to download the Dashboard and then follow the instructions discussed, it will a lot easier that way.
You can also get access to the explainer video + resources
Screen 1 Calculations – Performing a multiple criteria lookup
Take a look at how the Visualisation and its backend is performing a 2 way lookup
- When you select a Company name (using a slicer), the pivot table stores the value of the slicer (company name) in a cell
- When the cost variable is selected (again using a slicer), the chart highlights that variable. But we are not exploring the chart as of now, We’ll keep that aside for a while
Now here is the Lookup formula used to lookup values for cost variables. Total Variable Cost and Operating Leverage were calculated separately. Note that the formula
- Matches the company name (Company1)
- Matches the Variable Name
- And the year using the Columns Function
Once these values were calculated I directly plugged them in the Dashboard
Links for newbies to INDEX, MATCH, OFFSET & COLUMNS Functions
[One of the techniques used] – How to use slicer without a Pivot Table
Screen 1 Calculations – How the Stacked Chart was made
A regular stacked chart looks like this. One big problem – too many colors!\
Stacked Charts can get pretty hard to read because of multiple colors for each part. Highlighting the variables in the chart was the key to make it look simple to read. Here is how it was done!
Take a look at the logic
We needed a dummy calculation to support the highlighted section.
- Dummy = Sum (Values below the selected product)
- The dummy needed to be dynamic which changes as the user selected the product
Using these 2 calculations (Dummy & Highlighted section) a stacked chart was made
I wrote a pretty detailed post about how to highlight parts of a stacked chart. Check it out if you want to get into more details.
Screen 1 Calculations – How did I generate Comments ?
Notice the comments – Most words just stay the same and only a few words change. There were 2 comments with 2 different messages
- Comment #1 : Shows the absolute change since 2011. Depending on the % change a text tag is added (for eg. moderate / considerable / drastic change etc..)
- Comment #2 : Compared to the previous year which year had the largest % change.This was a bit tricky and the reason why I chose to show it because we wanted to bring out interesting insights (drastic or alarming changes) from the 5 year trend. We needed the following ingredients for setting this up
- Which year had the largest change (+/-) over the last year
- How much change has happened (i.e. the exact %)
- Tag (moderate / slight / no change etc..)
The first thing was to set up a Comments Reckoner table
Nothing fancy about this, it is simple 2 columnar data with % change and an appropriate tag along with it. All this data was manually created! We will use this reckoner to lookup an appropriate tag for % change calculations
Working for Comment #1
The calculations are pretty straight forward
- We calculating the absolute % change since 2011
- Using that % change we are looking up for a relevant comment tag in the comment reckoner. Since we are working with a range (between 90% – 50% = drastic change) the lookup method used is approximate match
- After calculating % change and tags for all the variables we needed to narrow it down to only the variable selected
Which was done using a simple Index-Match formula to find the % change and tag for the relevant variable selected
Working for Comment #2
Let’s take a look at each of the 4 parts
- Finds the change over last year for each variable
- Finds the position of the maximum change. This position number will help us find that in which year the change happened
- Calculates the % change that happened
- Adds a tag relevant (from the comment reckoner) to the % change
Using the above calculations, now we lookup for the relevant variable selected
Just like the previous one a simple Index formula for looking up the relevant % change, tag and year
Then I concatenated all these calculations to write comments and used the camera tool to create a linked picture and pasted them in the Dashboard
Phew!! that was some work.
If you have reached till here you might be interested in taking a look at an explainer video + resources that I have put together on this Dashboard
Screen 1 – Overall Layout !
Since I had to show comparison between 2 companies therefore both the frond end and back end calculations were set up in 2 blocks – Left side for 1st Company Selected and Right Side for 2nd Company Selected
This also made it easier for anyone to see my workings and understand how things are formed!
Quick Tip: It is important to layout your calculations clearly! It not only becomes easier for you but also for anyone else to understand your model
Screen 2 – Overall Market
Setting up this screen was not complex apart from conditional formatting. There were 3 major things
- 5 Pivot Tables for each year sorted in descending order (that will enable ranking)
- Slicer for selecting any company and pivot table to store the value
- Slicer for selecting any variable and pivot table to store the value. Note that the variable slicer was connected to all 5 pivot tables
Screen 2 – The tricky part, Conditional formatting
I applied 2 layers conditional formatting
- Layer #1 The selected company should be highlight for all the years
- Layer #2 Icon sets should display the change from last year has been positive, negative or no change
Layer #1 – Conditional formatting for highlighting the Company
- I wrote a simple formula to equate the company selected in the slicer with the companies displayed
- Where ever the result was true the format set was blue color
Layer #2 – Icons that display change from last year
Since icon sets do not accept relative cell referencing so I had to play a trick. I first wrote a formula to find out last year’s value for the selected company and selected variable. This was the formula is copied down in 4 cells and pasted in each column containing values
A key thing to note is that the below formula also accounts for 2 additional factors
- If the user selects Profit – Green icon should be displayed when the profit is up from the last year and a red icon when the profit has dipped from last year
- If the user selects any Cost Variable – Green icons when the cost has gone down from the last year and red icons when the cost has increased from last year
Then I applied conditional formatting (icon sets) for each value separately and referred to each cell containing the above formula
and that completed all the number crunching and setting up of the Dashboard! The next big thing was to format this beast and make it a beauty!
Wow..!! If you are still hanging around I would love to share with you an explainer Video + Resources that I have put together for you. I think you’ll love it
How did I format the Dashboard ?
Screen 1 – Headline Bar
- I set up the headline bar in dark grey because I din’t want to overwhelm the dashboard with too many colors.
- I used Red for highlighting the chart and Blue for Company slicer
- Also in the past I have read many reports from Bain & Co and they use red with grey/black, so I knew that color combo looks pretty cool !
Screen 1 – Slicers for Companies
- I spent a lot of time customising the look and feel of the slicers
- Mostly removing the non essential elements and make them look seamless as if they are a part of a web based report
- If you want this same format
- Just copy and paste this slicer in your workbook
- You’ll find a new style created in slicer options
- Now apply the style on your existing slicer and delete this slicer! Done
[Related] – Learn to work with slicers
Screen 1 – Formatting Stacked Chart
- I wanted the charts to look simple and clean
- I included the vertical axis and not the data labels. Instead I highlighted the values (via conditional formatting) below
- The years (horizontal axis) was put on the top so that it becomes common label for the chart and the values below
Screen 1 – Formatting Cost Variable Slicers, Values and Comments
- Note a few things about Slicers
- Just to make sure that slicers look like clickable and yet NOT look like buttons I gave a little stick at left side in red. It was a trial and error exercise but it did the trick
- Just to be more explicit I even wrote it on the top “Pick a Cost”
- Arranged the slicers accurately so that they look seamless and appear as spreadsheet values
- Formatting Values
- I applied 2 layers of conditional formatting
- Color the values in red for the cost variable selected
- If the total variable cost is select then apply bold formatting on Power, Other, Variable Cost and Freight & F
- Other than that there was a slim border between each row
- I applied 2 layers of conditional formatting
- Formatting Comments – There no major formatting done here. These are just linked pictures
Screen 1 – Overall Formatting – I did some overall formatting to tighten & secure the dashboard and make it look compact
- I protected the sheet (with no passwords)
- All objects (lines, charts, boxes / shapes) were locked
- The slicers were left unlocked, else clicking wouldn’t have happened
- The sheet name tab was removed
- The headings (column and row number) were hidden
- The formula bar was removed
- The extra rows and columns were hidden
[Related] Hiding Options in Excel
Screen 2 – Headline Bar
- The slicers on screen 2 were exactly the same as screen 1.
- The 2 buttons interchanged appearances when clicked, which made it look like dynamic but technically it was just moving from one sheet to another
Screen 2 – Slicers Formatting
- Formatting of both slicers were consistent
- Red for cost variables
- And Blue for Companies
- A label was put up on the top, just to make things more explicit
Screen 2 – Formatting Years, Data and Legends
- Formatting Years
- They were slightly in a bigger font than the data
- And I placed slim separators in between
- Formatting Data/Values
- Most of this formatting came from Conditional formatting as explained above
- I also left a column with a very narrow width in between each year as a separator
- Formatting Legends
- The legends were pasted as a picture
- The legends also depicted 2 inferences (for cost and profit separately)
Screen 2 – Overall Formatting
- I carried most of the formatting practices from screen 1
- Additionally I also made sure that the total width of Screen 1 is equal to Screen 2
How much time did I spend in creating this Dashboard ?
- Dashboard Pre-Work – Planning, Rough work and Mock Dashboard (1.5 Hour)
- Number Crunching and Analysis – (2 Hours)
- Formatting and Creating the look and feel – (2.5 hours)
I gave 3 sittings over 3 days to finish this task 🙂 . You can also watch a quick video explaining the entire dashboard
Mistakes that could have been avoided
I found 2 mistakes that could have avoided.
- The variables were static (hard coded) and they did not link back to the data. That could have been a problem or could have required additional work when
- The variables change completely
- More variable were added. In those cases the Dashboard was not capable of adapting to the changes automatically
- It could have been solved by a formula (to extract uniques) or by power query. Thanks Abhay for pointing that out 🙂
- The Overall Market Sheet could have had some additional analysis on the overall trend or may be an infographic. The space utilisation was not optimum
With all that work put it, I finally closed the Dashboard and sent it to Chandoo! and it clicked 🙂
I have put together an Explainer Video + Some additional resources on this Dashboard. I sure you’ll love them
Closing ..!
If you have any questions, please put them down in the comment below. I’ll be glad to answer as many as I can.
About the Author : Chandeep comes from the Investment Banking background and has been an avid excel user since last 6.5 years. He now runs an excel/powerpoint blog (www.goodly.co.in) and does training workshops for companies in India on Excel, PowerPoint Presentations, BI Dashboards, Financial Modelling.
Added by Chandoo: Thank you Chandeep
Thank you Chandeep for such an insightful, detailed and awesome write up. I really enjoyed learning from this. I am sorry I took too much time to schedule this.
If you too liked this post and learned something from it, please say thanks to Chandeep.
35 Responses to “75 Excel Speeding up Tips Shared by YOU! [Speedy Spreadsheet Week]”
I see most are saying that array formulas are bad. But I thought that when you use array formulas it grabs all the data at once and performs the calculations in one fell swoop. At least that is how the UDFs that I created work. When I did the time test it was much faster that way. Maybe I'll go back and check to make sure my work is right, but that's what I did.
When I work with array formulas I get a full column of data then work on that column and return a full column of data all at once. Which has shown to be much faster than the alternative.
Anyone have special insights on this?
wow..! thats a pretty impressive list, some real gems in there. I read somewhere the other day that spreadsheet development should be 80% planning and 20% implementation - taking the time to think about layout, how you're going to calculate things and how to structure the data often results in a lot less headaches, and more time for deeper analysis...
Hi Chandoo...
Mixed feeling about this article, while I completely agree with you when you share everyone's points under their name giving credit to contributors, but at the same time I see alot of repeated tips and few those may not be applicable under all cases. (I may have sounded harsh). Some kind of sorting of tips were required than mere 3 categorization. (Tough ask, I know). Some really worthy and awesome tips get lost in occean.
I would have been happy to read only non repititive tips and more like standard chandoo articles.
Well, I have also got two tips (may get lost in the list above), which is not presented above:
1. When using too many pivots - Disable data drilling option. This reduces file size, cache memory and speeds up file.
2. If your macro has used too many files for gathering input, close the file and open. This is also release or kill unwanted space in memory and speeds up. Again this can be achieved by macro to close self file and reopen same file, using timer function.
Please do not count me negative.
Regards,
Prasad DN
Hey, one thing that really speeds up VBA processing of data is to extract ranges into arrays & then working on those arrays. Arrays are a lot faster than using cell offset or any other method for working with a database. After you are done you can also paste the value directly into the range with one single command. This will speed up the macros considerably.
Here is a msdn article with examples in it:
msdn.microsoft.com/en-us/library/aa139976(v=office.10).aspx
Hope this helps
oops, noticed a typo in the tip I posted:
Re directly assigning values in VBA rather than copying & pasting should have read:
Sheet2.Range( "B1:B200 ").Value= Sheet1.Range( "A1:A200 ").Value
not
Sheet2.Range( "B1:B200 ").Value= Sheet1.Range( "A1:A100 ").Value
Corrected with double quotes:
Sheet2.Range("B1:B200").Value= Sheet1.Range("A1:A200").Value
[...] posts on speeding up Excel worksheets, one of the posts focuses on formulas and another he let the general readers make their suggestions. I made the suggestion that people use array formulas. But most of the other suggestions said not [...]
OK, I tested it. My UDFs were faster as array functions (like a couple thousand times). But Excel's built in functions are faster when not doing arrays. Not sure this is the case for all situations.
I can't help but to speak up.
Deleting a PivotTable will not speed up your workbook. It will only reduce the file size. There is zero memory processing for a pivot table if it just sits there.
Instead of destroying the pivot table, why not remove the redundant raw data. That would equally reduce the file size of the workbook, while keeping the pivot table functionality.
http://datapigtechnologies.com/blog/index.php/cut-the-size-of-your-pivot-table-workbooks-in-half/
Thanks a lot guys for your valuable tips !!
It really worked for me
Application.ScreenUpdating = False
Application.Calculation = xlCalculationManual
...
...
...
Application.ScreenUpdating = True
Application.Calculation = xlCalculationAutomatic
I would add:
Application.StatusBar = "Wait a second..."
............
Application.StatusBar = False
Optimizing Speed using Pivot Tables:
If you find that Pivot Tables are becoming sluggish becomes of the sheer volume of tables there is a way to increase performance. By default (xls 2010) pivot tables are designed to autofit the data within the columns as well as preserving formatting. I discovered that unchecking these two options alone will exponentially increase performance.
Here's how to do it:
Right click on your pivot table(s) --->choose 'Pivot Table Options' -->Layout & Format' Tab --->uncheck two boxes at the bottom. Done!
here is my list:
1. Avoid Variants when possible
2. Use long instead of integer
3. Use double instead of single
4. Use booleans as much as possible
5. pull data into arrays, manipulate, then dump back to workbook
6. use .value2 instead of .value if you are looking at strings or numeric values
7. set object variables
dim Wks as Excel.Worksheet
set wks = thisworkbook.Sheets("Sheet1")
8. use with statements...
with wks.cells(x,y)
.value2 = "abcd"
.interior.colorindex=4
with .font
.bold=true
.size =20
.underline=xlunderlinestylesingle
end with
9. use string version of functions (Left$() instead of Left())
10. Test for empty string variables with len() or lenb()...if lenb(String1)=0 then
11. Use the Mid$() function if it is possible instead of split()
12. use the join$() function instead of concatenating strings
13. AscW() to evaluate first characters
14. combine if statements and booleans together
boolean = (lenb(String1) = 0)
16. InStr(), InStrB(), InStrRev() are very fast, InStr() can be used to quickly return a substring occurrence of a string
17. DICTIONARIES!!!!!!!!!!!
18. FileSystemObject
19. My machine runs slightly faster when i fill in all the inputs of a function (instead of InStrB(String1, "abcd"), i use (InStrB(1,String1,"abcd",vbBinaryCompare)
20. Short Circuit If statements: If x = 2 then if y >3 then if z = 5 then b=true or
if x=2 then
if y >3 then
if z=5 then
b=true
c=true
end if
end if
end if
21. use ElseIf
22. my testing indicates ElseIf is slightly faster than a Case Select
23. set strings to empty by: = vbnullstring
24. with application
.screenupdating = false
.displayalerts = false
.enableevents = false
end with
25. UserForms can be very beneficial
26. User-Defined Types are a very neat way to encapsulate data
27. User-Defined Functions are handy, but can increase run-time if called thousands of times
28. if using ElseIfs, nested And Ifs or Select Case statements, put the argument that will occur most frequently at the beginning
29. Looping is not the worst thing...just got to figure out how to do it the most efficiently
30. Use dynamic arrays instead of static arrays
31. if you can figure out Win32 APIs, then they are usually much faster than VBA functions
I worked on a massive spreadsheet and it had become very slow over time as I developed it. I tried stripping down more and more formulas by replacing with pasted values, removed all conditional formatting etc. In the end what finally did the trick was when I removed the last single SUMPRODUCT fomula. It changed the updating time after one change from 7-8 seconds to instantaneously. The SUMPRODUCT I had used the full columns, and if I put it to only look at rows 1-500 it was fine.
[...] Speeding up Excel – 75 tips [Visitors: 36,157 ] Using Excel as your database [ 32,455 ] Comprehensive guide to VLOOKUP [ 23,745 ] 66 Dashboards visualizing Excel salary survey data [ 26,148 ] Interactive Sales chart in Excel [ 21,444 ] Compare 2 Excel sheets – howto? [ 21,820 ] Send mails using Excel VBA & Outlook [ 22,294 ] Customer Service Dashboard in Excel [ 18,136 ] Making your dashboards interactive [ 15,294 ] Extract numbers from text in Excel [ 18,490 ] [...]
TIPS FOR SPEEDING UP EXCEL
(1) Instead of writing a lot of formulas to organise data, you can VLOOKUP() the data in a Pivot table, thereby combining the advantages of Pivot table and VOOKUP().
(2) If you have a range named ‘TotalTaxForTheCurrentFinancialYear’, then it is not compulsory to use this name when making the worksheet. Naming the range as ‘Tax’ or simply ‘T’ will be sufficient. The formula =SUM(T) will be shorter and easier to use.
After completing typing all the formulas, simply edit the name of the range from ‘T’ to ‘TotalTaxForTheCurrentFinancialYear’, in the name box. The formula =SUM(T) will automatically change to =SUM(TotalTaxForTheCurrentFinancialYear).
Vijaykumar Shetye, India
VBA
I don't write many macros and like most of you when doing a recalculation it sometimes takes forever.
I have found that when I looked at my spreadsheet, I could determine which order of calcuations (by column) would produce the least number of iterations. So I wrote a macro to do my calculations on my terms. I picked the order of the columns I wanted to calcuate and it sped up my recalc 5-10X.
I did this so long ago, I believe I used "expression .Calculate".
TIPS TO SPEED UP EXCEL by Vijaykumar Shetye, India
You can view all the formulas in the entire worksheet quickly by pressing [ctrl] and [~] keys simultaneously.
To view results, press the key combination again.
i need help about excle lerning and reports making with dash bord i have no facility to join the on classes.
sajjad.hussain165@gmail.com
Is there any command to get time with seconds
Is there any way to create an excel file for specific time period, afterwards it will not open
[...] are looking for , but give it a try : Optimize Slow VBA Code. Speed Up Efficient VBA Code/Macros 75 Excel Speeding up Tips - How to speed-up & optimize slow Excel workbooks? | Chandoo.org - Lea... [...]
I've had to do a lot of mass calculations for reports etc. that involved repetitive identical, yet complex formulae, which took forever...
I hit on a great time-saver: sort the spreadsheet data; if, for example, the same result was due to a lookup of Hotel Name (A column), Date (B column), and Room Type (F column), the formula (Z column) would be: "=IF(A2&B2&F2=A1&B1&F1,Z1,VLOOKUP(A2&B2&F2,LookUps!A:G,7,FALSE))".
This meant that if the result is the same as the row above, just use the same answer, thus saving loads of time instead of VLOOKUPs. (This is a simplified example, the actual one had INDIRECT(ADDRESS...) in it, too!)
Check files for invalid range names, invalid links and names that aren't needed any longer.
Clearing out some 200 old references in a template made the file open go from 30 seconds to 2.
You can improve the speed by stopping calculation during changing cell value and after that you can enable it. please follow the link.
http://webtech-training.blogspot.in/2013/10/how-to-stop-heavy-formula-calculation.html
[…] 75 Excel Speeding Tips Its a long List, many repeated but worth a visit. […]
[…] 75 Speed-up tips by Chandoo (smartly done by crowd sourcing) […]
[…] Are you opening slow excel files? Use this reference to speed up your excel sheets […]
If you want to highlight the content or result within a cell with colour, use content colour not cell fill colour. This make a large data sheet fast as full colour takes up more resource.
There are already so many useful replies, so don't be mad at me if I repeat someone with the following hints.
While using pivot tables:
1. Link (raw) data from external files, rather then building pivots in the same workbook of the data. => Reduces file size.
2. don't flag "keep source data" in pivot settings. => reduces cache.
Downside is when you want to use slicers, you must allow refresh of the source data and thus people need access to that file.
One extra when using tables above ranges: replace the table header references by cell references in heavy duty formulas. I'm not sure but it seems to be faster and lighter (in #MBs).
hi
iam student and need xloptimizer( no demo) for solving the mathematical model
can you help me
thanks alot
@Reza
We cannot give away XLoptimizer
Why not post a question in the Chandoo.org Forums
http://forum.chandoo.org/
Dear Sir,
Thanks a lot for sharing tips & tricks of excel....
I read it , understand it and then use it in job and that has helped me a lot....
Thanks a lot...
Himanshu.
Mumbai, India.
In VBA, send out values to the worksheet all together as an array then excel will only re-calculate once rather than each time a cell that is output.
to the guy who said avoid looping in VBA - easier said than done, it's one of the most powerful uses for VBA out there. I'd therefore recomend the half way house and break the loop as soon as you've got what you want, don't let it run until the end. Use While etc.
What I would say on VBA in general is minimise sheet to code interations. Suck all your data into a VBA array THEN do the maths don't use cells themselves as stand alone visual variables.
And to the lady who said it's faster offline - that's because Microsoft are constantly contacting their own website be it security verification and/or update checks
Apply some logic to the order of criteria in sumifs / countifs formula
order the most exclusive criteria first. Once one criteria fails the others do not execute.
Bing AI, given the following query, confirms this: "excel countifs. if one criteria is likely to exclude most of the data range then should this criteria go first in the list to prevent frivilous executions".