Inaccurate
Forecasting and a Scenario Planning Alternative
Introduction
Forecasting and scenario planning are two processes by
which a business or enterprise attempts to predict their future (Wade, 2012). Forecasting is the more scientific of two
options. Forecasts are based upon models
of regression analytics (Dwivedi, Niranjan, & Sahu, 2013). Forecasting considers dependent and
independent variables and is considered a linear continuation of the present
(Wade, 2012). This may be where forecasts
are flawed, though. Forecasts are based
upon mathematics and, thereby, will likely never be totally abandoned as a
means of supporting strategic planning or change management. They are based upon, however, statistics of
what is currently known. Scenario
planning, by contrast, attempts to recognize a future of numerous possibilities
that realistically may occur based the present (Wade, 2012). It is more respectful of innovation in this
way. Scenario planning is more
considerate of the realm of the possible or even the imagined versus what is strictly
more scientifically likely. Forecasting
predicts a definitive future as regression analyses only have one dependent variable. Scenario planning supports change management
by recognizing the possibility of numerous realities or scenarios with the scope
of these scenario being only limited by what is known in the present day.
Unfortunately, there are some enterprises that can
testify personally to the woes of being misled by forecasting. Nintendo is one such company, and the consequences
of their mispredictions are discussed below in this paper.
Inaccurate
Forecasting the Nintendo 3DS
Forecasts are based upon data analytics implemented as
mathematical modeling and scripted programming.
Because of this, forecasts may be offered as often as the mathematical models
or scripted analytics may be implemented.
It is very intricate to supply
chain management (SCM), and supply chain managers regularly reforecast to accommodate
for changes among variables as well as to ensure process improvement (Albarune
& Habib, 2015). Nintendo’s release of
their 3DS is a cautionary tale concerning the misgivings of inaccurate
forecasting that led to overcorrection during the SCM process.
Between April, 2014, and March, 2015, Nintendo sold 8.73
million 3DS units globally (Lopez, 2017).
Nintendo released the base 3DS in 2011, but began the release 3DS XL in
2014 very likely because of success with the original model. They were expecting that release of the 3DS
XL would boost sales. Nintendo forecasted
in 2015 that approximately 7.6 million units—3DS and 3DS XL combined—to be sold
in 2016. By February, 2016, the predictive
modeling had changed, and the forecast was modified (Lopez, 2017). By March, 2016, Nintendo was now forecasting only
6.6 million units to be sold globally for that entire year, a million fewer than
that predicted approximation a year prior.
The new modeling misled Nintendo; they sold 6.45 units in the U.S. and
Japan alone. The demand out-paced the
supply, and according to Lopez (2017), Nintendo may still be facing shortages of
the 3DS now because of conservative forecasting in 2016 and 2017.
The Hanjin Shipping Co. of South Korea was the seventh
largest shipping carrier in the world until they declared bankruptcy in August,
2016 (Kitroeff, 2016). In terms of this
company’s effect on Nintendo’s forecasting calculus for 2016, Hanjin was likely
flailing long before they declared bankruptcy, and Nintendo 3DS sales started
to suffer because of it. It is believed
that Hanjin’s demise negatively influenced Nintendo’s 3DS forecast (Lopez,
2017). This bankruptcy would be considered
a scenario, and even though Nintendo’s predictive analyses did reflect the decreased
availability of shipping, the new forecast presumed that the demand for the 3DS
would align with the slowed shipping, or so Lopez believed (2017). This forecast was incorrect.
Considering
Scenario Planning as an Alternative
Valid scenario planning might require of think tank of individuals
if for no other reason than to ensure as many as viable scenarios are
considered as possible. The think tank
would be composed of stake holders in a continual dialogue discussing what-if
scenarios. Forces such as product innovation,
diminishing demand, and the availability of suppliers would be regularly
discussed. The scenario planning think tank
would be planning for the production of more innovative products than those
currently on retailer shelves strictly to maintain the market share when the
demand of current products diminishes. The
think tank would presume as a scenari9on that competitors were doing the
same. That think tank would also be considering
the availability of external organization in the supply chain. This scenario planning think tank would already
be considering alternative shippers should Hanjin or any other shipper be no longer
available. The objective would be to have
contingency plans in place as a result of the scenario planning to ensure
seamless transition should one of those discussed what-ifs actually came to fruition.
References
Albarune,
A. R. B. & Habib, M. (2015). A study of forecasting practices in supply
chain management. International Journal
of Supply Chain Management, 4(2), 55 – 61.
Dwivedi,
A., Niranjan, M., & Sahu, K. (2013).
A business intelligence technique for forecasting the automobile sales
using adaptive intelligent systems (ANFIS and ANN). International Journal of Computer Applications,
74(9), 7 – 13.
Kitroeff,
N. (2016). Hanjin bankruptcy is the tip of the iceberg
for flailing shippers. Retrieved from https://www.latimes.com/business/la-fi-hanjin-shipping-industry-crisis-20160913-snap-story.html.
Lopez,
E. (2017). How Nintendo’s forecasting miscues led to 3DS
shortages. Retrieved from https://www.supplychaindive.com/news/nintendo-shortage-3ds-supply-chain-failure/435662/.
Wade,
W. (2012). Scenario Planning: A Field Guide to the Future. Hoboken, NJ: Wiley & Sons.