Despite all the data that retailers and e-tailers can now gather about poin
t-of-purchase information, buying patterns, and customers' tastes, they sti
ll haven't figured out how to offer the right product, in the right place,
at the right time, for the right price.
Most retailers largely ignore the billions of bytes of customer data stored
in their databases-or they handle that information incorrectly. As a resul
t, they don"t adequately supply what consumers demand.
But some retailers are moving profitably toward what the authors call "rock
et science retailing"- a blend of traditional forecasting systems, which ar
e largely based on the gut feel of employees, with the prowess of informati
on technology.
Marshall Fisher, Ananth Raman, and Anna Sheen McClelland recently finished
surveying 32 retail companies in which they tracked their practices and pro
gress in four areas critical to rocket science retailing: demand forecastin
g, supply-chain speed, inventory planning, and data gathering and organizat
ion.
In this article, the authors look at some companies that have excelled in t
hose four areas and offer some valuable advice for other businesses seeking
retailing perfection. In particular, the authors emphasize the need to mon
itor crucial metrics such as forecast accuracy, early sales data, and stock
outs-information that will help retailers determine when to tweak their sup
ply-chain processes to get the right products to stores at just the right t
ime.
The authors discuss the information technologies now available for tracking
that information. They point out the flaws in some reporting and planning
systems and suggest alternate methods for measuring stockouts, inventory, a
nd losses.