Or more appropriately titled, the one where Power Query solves the problem in less time than it takes you to say Get & Transform Data.
Recently, one of my students Mr. K, sent me a pivot table problem.
Today my boss asked me “how much we paid to staff since the inception of our business with their respective date of joining?” He wanted to know, level wise summary of the last 16 years (on Quarterly / Year wise basis).
The records appended from the database month wise. Have a look to the file and give your ideas.
Mr. K’s data looked like this.
and his boss wanted a report like this:
What now?
The obvious solution – VLOOKUPs and patience
Even before I could go thru Mr. K’s problem and reply to him, he wrote back to me saying that he found the solution.
He used what I call as VLOOKUP and patience method. First he unpivoted original data using 233,000+ VLOOKUPs . Then he created a new pivot table from this unpivoted data to answer his boss’s questions.
While this method is fine, it consumes a lot of time and coffee.
A better solution – Power Query and pop corn
We, humans are not evolved to write two hundred thousand VLOOKUPs in afternoons. We are better at building powerful machines, watch them do bad ass work while we chew delicious pop corn.
So why not let the computer solve the problem?
Here is the ridiculously simple four step tutorial to get the same results.
- Load the data in to Power Query using From Table feature.
- Unpivot all the monthly data columns
- Load the data in to Excel as a new table
- Pivot it to create the report we need.
All this takes less than 15 seconds. Whenever you have new data, simply refresh the connection and everything (PQ, Pivot tables) gets updated.
Download the example workbook
Here is the workbook just in case you need to see everything. Please use Excel 2013 or above to play with this.
More power to you
Power Query is a truly remarkable feature of Excel. It saves you a lot of time and hassle. If you are new to Power Query (also known as Get & Transform data in Excel 2016), check out below tutorials to get started.
- Introduction to Power Query
- Import and work with web data using PQ
- Unpivot data with Power Query – an example
How would you solve this?
Prior to Power Query, I would have used VBA (as there is a lot of data) for something like this. For smaller data sets, I would have used VLOOKUPs.
What about you? What method would you use to rearrange data like this? Please share your tips in the comments section.
18 Responses to “Best Charts to Compare Actual Values with Targets – What is your take?”
Great post. I can't vote, though, because the answer I want to put down is "it depends". As with all visualisations, you've got to take into account your audience, your purpose, technical skills, where it will be viewed, etc.
I'm with Andy: It depends. Some I would use, some I might use, some I won't touch with a barge pole.
Naturally I have comments 🙂
The dial gauge, though familiar, is less easy to read than a linear type of chart (thermometer or bullet). It's really no better than the traffic lights, because all it can really tell you is which category the point falls in: red, yellow, or green.
By the same token, pie charts are so familiar, people don't know they can't read them. Remember how long it takes kids to learn to read an analog clock?
Bullet charts don't show trends.
With any of the charts that have a filled component and a marker or ine component, it makes more sense to use the filled component (area/ column) for target, and the lines or markers for actual.
[...] Best Charts to Compare Actual values with Targets (or Budgets … [...]
I voted for #6 even though I agree with the other comments that it depends.
The majority of the votes are for the #2, thermometer chart. I still have yet to understand what happens when you are above plan/goal, which was brought up in yesterday's post.
Also, I agree with Jon in that it would be better to flip the series and make the filled part the target or goal and the line or marker the actual.
I am also a fan of using text when appropriate if the data is among other metrics in a type of dashboard. Calling it out by saying actual and % achievement is a good option.
Another "it depends" vote. Are you just looking at one or are you comparing a number of targets with actuals? You didn't include a text box. The problem with sentences is that they can get lost in a page of gray text. A text box can call attention to the numbers and line them up effectively.
I'm with Jon: "Some I would use, some I might use, some I won’t touch with a barge pole" and I'm surprised that some of your readers voted for the last group.
Jon says:
With any of the charts that have a filled component and a marker or line component, it makes more sense to use the filled component (area/ column) for target, and the lines or markers for actual.
Why does this make more sense? I like 6 the way it is, although I would use a heavy dash for the plan/target marker.
"It depends" is also my take. What I usually try to drill into my clients dashboard design is the fu ndamental difference between spot results (am I on target for this month) and long term trends.. I always try to create 3 different set of graphs to represent real perormance:
- spot results vs objectives
- cumulative results vs objectives
- long-term trend (moving average) mostly) to see where we're going
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Jon says:
With any of the charts that have a filled component and a marker or line component, it makes more sense to use the filled component (area/ column) for target, and the lines or markers for actual.
Why does this make more sense? I like 6 the way it is, although I would use a heavy dash for the plan/target marker.
I totally agree, Bob. I would normally favour a line for the target and a column for the actual, you can see quite easily then which columns break through the line, then.
[...] best charts to compare actual values with targets — den Status mal anders zeigen, z. B. als Tacho [...]
Thermometer charts: "Not appropriate when actual values exceed targets" - this is easily solved by making the "mercury" portion a different color from the border, then you can clearly see where the expected range ends and the actual values keep going.
People seem to knock gauges quite a bit in dashboarding, but trying to show comparison of realtime data between operating sites and targets for each site can easily be done with a bank of gauges that have the optimal operating points at 12 o'clock.
The human eye is great at pattern stripping, and any deviation of a gauge from the expected 12 position will quickly register with an operator and attract his attention. Using a colour background, or meter edge, will also indicate the sensitivity of a particular site.
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I am wondering how will the plotting work, for some of the targets which may have been achieved before time. E.g. for the month of Jul the target was 226 and the actual was 219. So the chart will show a deficit in meeting the target by 7 points but what if this 7 may have been completed earlier in month of June. So ideally it not a deficit.