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TRANSVERSE ANALYSIS
Method
The cross-functional analysis, which leads to an overall perspective on the population under investigation and its cost
control practices, is based on a four-dimension breakdown: the
size
of the company, its
business sector
, its
dynamism
, and its
nationality
(or culture). From a method point of view, the breakdown choices are debatable.
Nevertheless, this approach brings a complementary and synthetic view of typical profiles of organizations with which
readers could identify. In line with our previous editions (from 2011 to 2014), the cross-functional analysis does not
lead to clear-cut conclusions, given the complexity of the reality. But even if we observe a certain homogeneity of
practices worldwide, differences exist.
"Size", defined by the variable "revenue", is split into three dimensions: "small firms" (revenue below
€
50 M),
"medium-sized companies" (revenue between
€
50 and
€
249 M), "large companies
͟
(revenue of
€
250 M and above).
The "business sector" is divided into four sections: "
Industry
" (consumer goods, industry, energy and facilities,
engineering and construction), "
Services
" (retail and trade, banking, insurance and financial services, transport and
logistics, media, telecoms and new technologies) and "
Others
" (public services, other services).
"Dynamism" is based on "revenue growth": "
decrease
" (from a sharp drop in revenue - above 10 % drop
–
to a
smaller drop), "
stable
" (no revenue change), "
growth
" (revenue growth from slight to significant - above 10 %).
The "nationality" dimension corresponds to the homeland of the firm or the group it belongs to; it is analyzed
through a
geographical dimension,
according to continents (Africa, America, Asia, Europe, Oceania) and a
cultural
dimension (Anglosphere, European, and Asian). Within these categories, more focused observations were made (for
example Northern Europe vs. Southern Europe or North America vs. Central America), in order to fine-tune the
analysis and highlight significant results.
Findings
Size analysis
The size of companies turns out to be a differentiating factor
on several topics. In small companies, management
controllers devote less time to information systems, and we observe the shortest (one month) or the longest (6
months) budget process lead-time. Small companies are also
the fiƌst ͞ŶoŶ
-
useƌs͟ of ƌefoƌeĐast
ing (26% vs. 4% in big
companies), and Excel remains the main tool for planning, budgeting, reforecasting, or reporting. It is in large
companies that controllers are most involved in cash forecasting or in transfer prices issues. It is worth noting that
over 50% of mid-sized or large companies believe that issuing warnings and implementing corrective action plans are
the main benefits of forecasting, as against only 38% in small companies. In addition, the larger the size of the
company, the less involved in strategic planning the operational staff are but the more involved in operational issues,
budgeting, and forecasting. Finally, large companies are more aware of Big Data issues.
On other issues,
the differences between small and large companies are less obvious
. It is the smaller companies that
consider planning, budgeting, and reporting as high value-added activities. For large companies, it is rather economic
studies, Corporate Social Responsibility (CSR) reporting, or high tech cost control. Rolling forecasts are used by mid-
sized and large companies rather than smaller ones, probably because they have more time and resources at their
disposal. Large companies are also more inclined to develop their reporting systems and regularly add indicators.
Small and large companies can also behave similarly
. We noticed, for example, a consensus on the activities adding
value to performance monitoring (forecasting and reforecasting, business reviews, management of the operational
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