BUSINESS SKILLS 6/2019 Business Spotlight 43Alternatives:
which path will
you take?Illustrationen: Yann Bastard
offers a key insight, namely, that data is
not “clean” information. It is the result of
a selective process of data gathering that
is underpinned by many potentially un-
provable assumptions and beliefs. If we
examine many of the beliefs informing
leadership decisions — for example that
empowering people motivates them, that
outsourcing leads to cost efficiencies or
that centralization is the most effective
management structure — we can find
studies indicating either the total oppo-
site or that the claims are at best contex-
tual and are not general truths.
Ask yourself: Which assumptions and
beliefs inform the data I use to takedecisions? To what extent can I trust
these assumptions?b) Data quality is a massive problem.
Most large organizations, whether they
like to admit it or not, have a data quali-
ty issue. Often, the IT systems on which
they rely were built so long ago that they
cannot capture in a meaningful way the
data that is needed to take decisions to-
day. Or the data that is entered into the
system by people and via other data sys-
tems is inaccurate or unreliable. There is
an old but still relevant adage about IT
systems and their human operators —
“garbage in, garbage out”.MOST LARGE
ORGANIZATIONS,
WHETHER THEY
LIKE TO ADMIT
IT OR NOT,
HAVE A DATA
QUALITY ISSUE
adage [ˈædɪdʒ]
, Sprichwort
capture sth.
[ˈkæptʃə]
, etw. erfassen
contextual
[kənˈtekstʃuəl]
, kontextabhängig
garbage
[ˈɡɑːbɪdʒ] US
, Müll; hier: Aus-
schussdaten
underpin sth.
[ˌʌndəˈpɪn]
, etw. untermauern