Wearable Computing Unit Sales Will Decline 20% in 2015. Really?

This Wearable Computing Forecast Makes a Common Mistake

Why do professional forecasters do it?  Are they lazy or just ignorant?  I don’t know, but here is how it goes.

Consider the forecast published recently by Business Insider in the article

The ‘Internet Of Things’ Will Be Bigger Than The Smartphone, Tablet, And PC Markets Combined.  The BI  graph (below) shows the installed base of devices in several categories.  “Installed base” is simply the count of devices in use by year.

BI supplies an Excel file from which I extracted the data for wearable devices in use, which is graphed (below) as a line graph.

The Wearables Devices in Use graph, as expected, looks like the beginning of a classic s-curve: starts low and rises steeply.  Although not shown on the graph, eventually this curve will flatten as the market approaches saturation or as the product is replaced by another type of product, in which case, devices in use may even decline.  The wearables market is at a very early stage and, if PCs and cellphones are good analogies, will have a run of at least 15 years before any sustained flattening takes place.

Let’s explore this wearables forecast a little further.  This Wearables Devices in Use series contains implicit information about Unit Sales of wearable devices  by year.  To dig it out we need a few definitions:

• Wearable — a wearable computing device.
• User — an owner of one or more Wearables.
• Use — a function (or related functions) for a Wearable.  A Use is often defined by the location on the User’s  body (e.g., eyeglasses. watch).  A User may have one or more Uses.  A Device in Use is counted as one Use.
• Potential Use — a Use that is not yet served by a Wearable device.
• Devices in Use — the count of Wearable devices that are owned by Users and have not been retired (taken out of use).
• Installed Base — same as Devices in Use.
• New Use Unit Sales  — the number of Wearables sold in a given year for a Use that had previously been unserved.  New Use Unit Sales in a year is Devices in Use for the year minus the prior year’s Devices in Use. This is “Adoptions” in diffusion forecasting models.  The cumulative sum by year of New Use Unit Sales is Devices in Use (Installed Base) by year.  If needed, these quantities can be adjusted for forecasted Attrition by year.
• Replacement Unit Sales — the number of Wearables sold to replace previously purchased Wearables.  A Replacement Unit Sale does not increase the number of Devices in Use.
• Unit Sales — The Total of New Use Unit Sales plus Replacement Unit Sales.
• Attrition – Uses that had been counted in Devices in Use in a prior year but are no longer in use; for example, a computer watch that was thrown away and not replaced.
• Net New Use Unit Sales — If Attrition is included in the model, Net New Use Unit Sales is New Use Unit Sales adjusted by Attrition.

In the early years of a market, such has that being consider here, Replacement Purchases and Attrition are typically low; therefore, New Devices in Use is essentially Unit Sales.  In the graph below, notice that Wearables Unit Sales increases, then declines and continues flat.  Really?

To better illustrate this unfortunate surprise calculate Unit Sales year-over-year growth rate (below).  Notice the negative growth in 2016. The jaggies in these charts are also unexpected. Historical data can be expected to have its ups and downs due to the unpredictable nature of complex systems. But, the forecaster has not yet been born who can justify forecasting jaggies like these. “Something is rotten in the state of Denmark.”

Why Did BI Forecast that Wearable Computing Unit Sales Will Decline 20% in 2015.

The answer is: they surely didn’t mean to.  But, by estimating an Installed Base curve without attention to the implicit Unit Sales curve, they made a rather ridiculous forecast.  They are not alone in making this blunder.  It is all too common in the forecasting business.  I, too, have been there and done that — and, have been sufficiently embarrassed that I gave up such shortcuts many years ago.  When I see this mistake in a forecast, for me, the entire forecast has no credibility and should be considered only as an opinion that a new market will grow.  The Installed Base data points are not worth the bits they are printed on.

Why, Why, Why?  It Is So Much Easier to Do It Right!

The correct way to do a forecast, such as a forecast for Wearable devices, is to first forecast Unit Sales.  In the early years of a hot new market, forecasted Unit Sales should increase annually while the growth rate should gradually decline but is never forecasted to be negative.  Only in a mature market, when a product is being replaced by another (e.g., desktop PCs being replaced by laptops) should negative growth rates be forecasted.  Second, the forecasted Unit Sales by year are then summed cumulatively to yield the Devices in Use (Installed Base) curve.  If important, Devices in Use and Unit Sales can be adjusted by forecasted Replacements and Attrition.  By forecasting a nice smooth curve for Unit Sales first, the cumulative, which is Devices in Use, will be a nice smooth s-curve.  If, as BI did, the Devices in Use curve is estimated first, the Unit Sales curve will likely be weird.

An even better way to build a forecast for a new product  is to use a diffusion model (e.g., the Bass Model).  The diffusion model parameters can be varied until reasonable forecast curves are obtained.  A diffusion model for Wearables will simultaneously forecast Devices in Use and Unit Sales, as well as the penetration curve, years to saturation and the potential market size.  Soon I will  do this for wearables in another blog post using a downloadable Excel spreadsheet tool as well as an interactive Bass Model tool.

You May Quote Me:

“In forecast curves, only the past is jagged — the future is smooth.”