Helping the Chronically Overworked Find Life Balance

What Happens When Features Are Dropped To Make a Launch Date?

Chapter 9: Paint Your Environment Part 6

Ever been on a project that is under time pressure to make a launch date?  One common solution  is to drop features from the product.  For example, when Apple launched the iPad mini in November  2012, it did not have the retina display.  I have no knowledge of how that decision was made, but I can easily speculate that this feature was not included to bring in the launch date.

“Sabina” was a product manager working in lifescience industry who was part of a project that had to make that very choice.  She was working on a new technology to detect and quantify a particular RNA within a sample.  When the original product was scoped, it was designed to meet a set of unmet customer needs, and she created a healthy revenue forecast to justify the expense of development.  Sabina explained the difficulty of creating a forecast for a new technology.

“When you build [mathematical] models, you try to make an intelligent metric,” which was based on sizing the market, and estimating the market share based on what the product could do relative to the competition.  Sabina explained that she felt “pressured to show there is value in doing the project, a positive NPV.  I never felt that I wasn’t being truthful, [but] with a brand new technology, it’s sticking your finger in the air and making the best guess you can.  There was equal pressure from myself and others.”

A forecast is built on assumptions. One key (although often unstated) assumption is that the product will meet the customer’s needs.  Notice how the impact of the assumptions as  Sabina continues her story.

“When I did the original model [at the start of the project] there were assumptions of what we could commercialize.  [As the project progressed,] we had to cut out 2/3 of the features.  Do I want to cut the revenue model?  At that point if I had cut it as much as I should have, the project may have gotten killed.  Yet I believed in it enough longer term, not just first release.”  Sabina made a quiet internal assumption that it would take multiple iterations to get it where the customers really needed it to be.

Unfortunately, the organization was very tied to the forecasts, which came in at 25% of the pre-launch levels.  This in turn meant that additional development resources were not allocated to help the product grow.  And life was difficult for Sabina, with lots of questions from her management team.  “I felt like a failure because [the forecast] was so off.”

In the next post, I will explore Sabina’s options, through the filter of corporate idolatry.

<<Previous Post    Next Post>>

The Accidental Lie In My Forecast

Chapter 9: Paint Your Environment Part 5

I used to agonize over my revenue forecasts.  I’m sure the scientist in me was holding me back, or rather was driving me to make them incredibly precise. But that didn’t make them more accurate.  I used to get advice from people in the know like “be confident” and “just list your assumptions.”  But I never really got it until my very last product forecast.

I presented the forecast on the phone, using hard copy of the slide deck.  It was a routine launch review for a small product, and I had nudged up the numbers since the previous checkpoint due to favorable market conditions.  I got a surprising amount of pushback from the executive review committee, but I confidently defended the numbers, citing “changing market conditions.”  I was really surprised at how excited the execs were as they signed off.  The next day I discovered why: finance made an error in the last minute slide preparation, such that the revenue was one hundred times higher than it should have been.

I should have caught the mistake, and earlier in my career I would have been panicked and mortified.  But that day, I laughed out loud and never said a word to anyone.  The bar graph was absurd: one huge bar on the right, and a bunch of tiny pancakes to its left.  But I was a hero for my rosy prediction of the future.

I finally got it.  I was so hung up on finding the truth, but there is no truth to be had in a forecast.  Predicting the future is impossible.  And by changing assumptions, a forecast can be made to say anything.

What has been your experience with forecasts?

<<Previous  Next>>

Why You Should Care About The Revenue Forecast

Chapter 9: Paint Your Environment: Part 4

As I argued in the last post, if you want the company to do the right thing, make sure you have a set of numbers to back it up. To fully understand why I think this is critical, lets step back for a moment and look at where a revenue forecast come from.  The Cambridge dictionary online defines a revenue forecast as “a calculation of the amount of money that a company will receive from sales during a particular period.”

In a very real sense, a revenue forecast is a prediction of the future, and a forecast can have a very real impact on the day-to-day activities of employees.  It is tempting to think that these numbers are scientifically derived and reliable, but often they come from sticking a finger in the air, and then justified after-the-fact in Excel.

I heard a cautionary tale from “George” the former VP of marketing at a mid-sized biotechnology company about how a bogus forecast helped propagate a disaster.  Research created an elaborate robotic system to streamline the user experience for one of the flagship product lines.  After a few experiments, they pronounced it ready to ship to customers, and did not need to go through a formal development process.

I cringed when I heard the story.  Product development is always needed to make a new technology robust enough to work consistently in customer hands.

But “ready for customers” is exactly what the CEO wanted to hear.  He was a Scorpion, a “visionary” who felt that the technology should sell itself.  The President and CFO were hungry for revenue growth, and via a process that sounds a lot like groupthink, the executive team convinced themselves that “we should be able to make $10M on this product this year.”  Marketing then back calculated the number of units, service contracts, and consumables that would need to be sold to make the forecast.  (As a point of reference, this represented 25% of the company’s projected revenue growth for the year.)  Then when the product ran into development issues, the same executives went on a headhunt to find out where the number came from.

The rest of the company scrambled to fill the $10M revenue hole.  Timelines for other products were accelerated, and employees throughout the organization put in long weeks to “make it happen.”

Bad management?  Sounds like it.  But there was not a rush of people heading for the door.  Inside the asylum, everyone looks sane.  (See this post on stress and loss of perspective for more.)

How far will your company go to make the numbers?  Where do the numbers come from?  If you can’t control the forecast, what can you control?

<<Previous Post  Next Post>>