The incident at the Oscars, where
the wrong winner was announced in the category of “Best Picture” is very
interesting. The results were vetted and made watertight by PWC, but I
guess moonlight consists of smaller molecules than H2O. So the question is, if you hired PWC,
what did you pay for?
First of all, the 2 PWC employees
who oversee the whole process are stars in their own right; and show their process with personal attention to detail[1]. They even have their glamourous pictures
on the red carpet[2]
The job of PWC is simple, ensure
the votes are correctly counted, and the results delivered to the correct
people at the right time to make the right announcement.
Sounds like a simple big data
problem actually, you know: right offer, right person, right time...
However, PWC chose a very
analog method, you can actually follow the Oscar votes briefcase across America!
Perhaps in line with the rumours of hacked vote counting machines this is not a
bad idea, but the execution must be there.
PWC is not the only one to have
had major failures, a quick search on google with the name of a big 4 and
the word “failures” shows: PWC[3],
EY [4], Deloitte
[5],
KPMG [6].
And for people in Singapore, who
can forget the Barings Bank collapse? Barings had not one but 2 Big 4 Auditors[7].
I am not against PWC, it's just that the incident triggered this blog.
While I looked at auditors, I
could have as easily looked at the large IT consultancies... IBM[8]
or Microsoft[9],
Google [10]... In sum, even highly reputable companies do make 'big mistakes'.
So what are organisations paying
for? Is it to ensure things are right or is it someone to blame?
If it is to ensure things are
right, are you getting value for your money? This brings me to my 2 current bug
bears:
1 When organisations are
employing external experts, are they getting value for their money in terms of
quality? Or are you paying for layers of management? This article from 2011
questions why large organisations were finding it so hard to change[11].
As a result, interesting business
models that offer independent expert services have sprung up such as expert360[12] and alphazetta[13], this phenomenon has been explained in a McKinsey article on
the gig economy [14].
This also ties in to my earlier argument that most organisations could use resources
much better than hiring full time data scientists [15]
(experts in the field of Analytics/'Data Science')
2 Why aren’t organisations such as auditing firms taking
advantage of “Big Data”? I am not privy to the detailed workings of auditing
firms, but I doubt they actually make full use of “Big Data”. Most auditing is
done purely looking into the client organisations focused on looking at
internal discrepancies. Very often, discrepancies are easier to detect if you
have context, especially if the context is outside the control of the client
organisation.
Let me give a very simple real life example in
the domain of risk. Most banks have a risk rating to each of their clients, and
again, these risk ratings tend to be based almost exclusively on the accounts
of the client, with some variation for health of the sector in general.
However, it is easy for a bank to
understand the relationships between various organisations.
 |
| http://assets.teradata.com/resources/aofa/dollar-diadem2.html |
This art piece from Teradata[16] illustrates
what can quickly be done to understand the relationships between organisations.
Now imagine what it means for an organisation whose main customer happens to be
highly risky. Even if the organisation has healthy balance sheets, if the major
customer collapses, it poses high, at least short term, risk (and opportunity depending
on your risk appetite). But if you look at organisations independently, however
deeply, you will miss this, and systematically underestimate the risk.
Similarly, looking at the Barings
collapse, having a context against which to compare the activities of Mr Leeson
would have been critical in understanding the risks. This is more into the area of employee activity, dealing with internal threats. Similarly in the recent
case of 1MDB where a lot hinged on an unauthorised letter vouching for the
worthiness of the accounts by an ex-Goldman Sachs dealmaker [17] this
could easily have been spotted when looked at in context.
The real question is, did the
players really want to look, or were they content to close one eye and hope for
the best as their tills kept ringing?
I believe that the
advent of “Big Data” and the gig economy will change or even is already fundamentally
changing the provision of expert services. Organisations are likely, going
forward, to use independent experts that know how to make use of “Big Data” on
an as-needed basis, paying directly for the expertise, rather than engage large
companies that are not evolving to adapt to the new realities and find
themselves laden with too many overheads.
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