New Technology with Larry White – New Perspectives on Accounting and Finance

(upbeat music) – As accountants move in to the AI world and the technology associated with it, they need to rethink their perspective. Accountants need to quit focusing on just one model of financial information, the model associated
with generally accepted accounting principles, financial reporting financial accounting, essentially the model
every accountant was taught as an undergraduate or graduate student, they need to move into
information modeling in a way that’s relevant to
the people in their company. Now by in their company this is a complicated question because accountants have
always done a good job in what I call the up and out. In other words,
communicating to the C suite and communicating to stakeholders. The new challenge with automation and artificial intelligence is to communicate around and down to their peers and to the
employees throughout the company and make the information
they provide relevant and actionable to those people because a lot of the
information we’ve provided that’s structured in the way that financial reporting requires it is based on standards and conventions, not based on the reality of
the resources and the processes that the people throughout
the company actually see and need information and
need insights to use. (upbeat music) There’s an interesting
challenge for accountants today. We need to fundamentally
rethink a little bit about what accounting is. Is accounting about the rules of man or the laws of man? Is it, does it reflect
the social consensus that’s established by, for instance, the Financial Accounting Standards Board or the International
Accounting Standards Board or should accounting more
accurately reflect the laws of nature, the reality of the resources and processes inside a company? I think we need to develop accounting as actually a financial modeling focus, not focus just on the one model that all accountants learn, generally accepted accounting principles, wherever that is around the world but to focus on modeling reality, to have a more scientific
and reflective look. That look will be
extremely useful to people throughout the company,
not just to executives and stakeholders that are
making investment decisions or working towards, perhaps
bonuses and incentives. (upbeat music) The challenge that occurs
when you look at a new style of information, when
you look at what I call, causal information or
information based on the laws of nature to provide scientific insights, it is a whole different ballgame. What we’re seeing is that industry 4.0 or manufacturing 4.0 has arrived and that environment
is extremely data rich. They’re looking not
only at the performance of their production line on quality, they’re looking at the performance
of their production line in terms of meeting various metrics. They’re looking ahead at
forecasting equipment failures so they can take action before
that happens accidentally. (upbeat music) There’s a case study that
specifically intrigues me and that’s the case of a South African
platinum mining company. They had developed an exceptional
set of operational metrics and they were using this
and they had supervisors that were actually arguing
about which operational metrics made the most difference to the company? Which would produce the best results? And perhaps on one shift,
one metric would work, on another shift a
different metric would work. So, this company had gone to the problem of identifying what was
the optimal condition for many of the metrics. But even that didn’t fill the bill, they needed a monetary overlay so that all those
metrics could be compared with one uniform type of measure and that measure, the measure
that works best is money. And so we were able to go in
and create a monetary model of their operations that
was extremely granular and we created a model
for their ideal condition and then we created real time models associated with all of their key metrics. And so consequently supervisors could sit in their control room, they could look at the, instead of looking at eight
or nine different metrics and deciding which one they should adjust, they could watch one metric
that really provided them with the difference between
the optimal condition and the condition they were at. (upbeat music)

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