A data-driven prognosis report

Posted by Marcus Hammarberg on October 11, 2021

I have a big project ahead here at Salt - I’m going to write an entire boot camp from scratch. This is done as a single-person project and all my other colleagues are working on as normal around me.

I wanted to report my progress to them so that they know what’s happening and also that I can get some leeway of keeping my focus.

In this post, I wanted to share a very simple prognosis tool that I created based on the data that my work create. As always, it’s not perfect but it will give an accurate enough feel for where I am and when it will be done

A few words about the project

Unlike most software development projects I’ve been in the scope of this project is very clear;

  • I’m going to write slides, labs, and instructions for 13 weeks, 5 days a week
  • The topic is given
  • The content on heading level per week is given (after some initial vetting work with external consultants).

So … all that is left is to fill out the blank. Well, it’s not that simple, but I have to ensure that I managed to fit the content.

What I did is that I listed all days (and weeks) for the entire boot camp and then created a status for each day:

  1. Documentation initialized
  2. Heading of the week created
  3. Heading of days created
  4. Content stubbed out
  5. Slides written
  6. Lab/test written
  7. Ready to go

I also added one more property per day: completion in 15%. I use this to indicate how much work is left to do on the day. Stubbing out the content for the day takes a very short time. While writing slides or the labs take considerably longer.

With that in hand, I was ready to create some reporting

Simple reporting

The most simple thing I could do was to add a report for how all of these numbers add up. This was things like a circle diagram showing how far I’ve come

Status per day

Or just showing per week how much has reached 100%

Completion per week

This is good and probably interesting but doesn’t say anything about when I will be done. The works I’ve done so far is the easy part. I could copy just about everything from other sources.

But let’s try to fix that - time to get prognosticate (no .. that is not right… time to make a data-driven prognosis)


Here’s the thing, I do know, how far I’ve come right now. And after each day I work, I know how far I’ve come so far.

For example, here’s the data for my first couple of sessions:

Date Completion %
2021-09-10 15%
2021-09-13 24%
2021-09-14 25%
2021-09-16 27%
2021-09-18 27%
2021-09-22 33%
2021-09-26 46%

Now, what if I could create a prognosis based on that data.

I first calculated how far I came per day in each session:

Date Completion % Days Gain in % Gain in % per day
2021-09-10 15%      
2021-09-13 24% 4 9% 2.25%
2021-09-14 25% 2 1% 0.50%
2021-09-16 27% 3 2% 0.67%
2021-09-18 27% 3 0% 0.00%
2021-09-22 33% 5 6% 1.20%
2021-09-26 46% 5 13% 2.60%

It was some simple Google Sheet calculations, required, to calculate those 3 columns:

=IF(A3<>"",Days(A3,A2)+1, "")

Gain in %
=IF(A3<>"", B3-B2, "")

Gain in % per day

Perfect - now let’s create some prognosis.

Each day I progress a few %. Some sessions it’s more and others less. Sometimes I don’t get time to work on this for quite some time and others it’s a few days after each other.

I’m gonna use PERCENTILE for that and call the lowest 25% my worst case, 50% my probable, and the top 75% my best-case scenario.

Projection - Bottom 25% gain / day (G) Projection - Median gain / day (H) Projection - Best 75% / day (I)
0.54% 0.93% 1.99%

The formula uses the Gain in % per day column like this

Worst case
=PERCENTILE($E$2:$E, 0.25)

=PERCENTILE($E$2:$E, 0.5)

Best case
=PERCENTILE($E$2:$E, 0.75)

I then create a long list of dates, going from the first time I worked on the project and 6 months into the future. For each date I added four columns like below, and incremented the 3 first with the values I calculated with the percentiles above:

Date (L) Worst case (M) Probable (N) Best case (O) Actual (P)
2021-09-10 15.0% 15.0% 15.0% 15.0%
2021-09-11 15.5% 15.9% 17.0% 15.0%
2021-09-12 16.1% 16.9% 19.0% 15.0%

(I also started at 15% as I didn’t have any data before that)

That means that the second rows formula looks like this:


Take the value from the G2-cell and add it to the value of the row above: 15% + 0.54% = 15.54%. For the probable and best scenarios, I did the same thing but using those percentiles.

The final column is the actual value, where I used my original data, which I based the prognosis on. It shows what actually happened and makes a nice little addition to the prognosis to see where we are today.

But I don’t have all the dates in that list so I will use the latest value I have until a new is discovered:

=IF(COUNTIF($A$2:$A, L3) > 0, VLOOKUP(L3, $A$2:$B, 2, TRUE), P2)


  • $A$2:$A contains the dates where I made some work
  • $A$2:$A contains the percent of completion when I made some work
  • L3 contains the date for this row

After filling out all the days six months worth of data was easy and I could then create the following graph:


Summary and future

The projections are based on the data that I have created so far and hence this graph will be updated as we go. This is exactly what I wanted because it reflects what has happened. Just like a good weather prognosis, we update it as we get more data.

For example, let’s say that I get two days worth of working this week (at the time of writing) and I get a few percent done each day:

Date Completion % Days Gain in % Gain in % per day
2021-10-14 48% 19 2% 0.11%
2021-10-15 49% 2 1% 0.50%

That will make both the actual line and the projections change into this…


And I’m in trouble, but I can explain that I need more time. And I will have a nice way to communicate with my colleagues about how things are going and when I will be done

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Published by Marcus Hammarberg on Last updated