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Dana Gardner: Hi,
this is Dana Gardner, Principal
Analyst at Interarbor Solutions,
and you’re listening to BriefingsDirect. Our next digital business innovations
discussion explores new ways that companies gain improved visibility, analytics,
and predictive responses to better manage supply-chain risk-and-reward
sustainability factors.
 |
| Gardner |
We’ll examine new tools and
methods that can be combined to ease the assessment and remediation of hundreds
of supply-chain risks -- from use of illegal and unethical labor practices to
hidden environmental malpractices.
To learn more about the
exploding sophistication in the ability to gain insights into supply-chain
risks and provide rapid remediation, I’m pleased to welcome our panelists, Tony Harris, Global Vice President
and General Manager of Supplier Management Solutions at SAP Ariba. Welcome,
Tony.
Tony Harris:
Thanks, Dana.
Gardner: We are
also here with Erin
McVeigh, Head of Products and Data Services at Verisk Maplecroft. Welcome, Erin.
Erin McVeigh: Thank
you, it’s a pleasure to be here.
Gardner: And
lastly, we’re here with Emily Rakowski,
Chief Marketing Officer at EcoVadis. Welcome.
Emily Rakowski: Thanks
so much. It’s good to be here.
Gardner: Tony,
I heard somebody say recently there’s never been a better time to gather
information and to assert governance across supply chains. Why is that the
case? Why is this an opportune time to be attacking risk in supply chains?
The perfect supply-chain storm
Harris: Several
factors have culminated in a very short time around the need for organizations
to have better governance and insight into their supply chains.
 |
| Harris |
First, there is legislation
such as the UK’s
Modern Slavery Act in 2015 and variations of this across the world. This is
forcing companies to make declarations that they are working to eradicate forced
labor from their supply chains. Of course, they can state that they are not taking
any action, but if you can imagine the impacts that such a statement would have
on the reputation of the company, it’s not going to be very good.
Next, there has been a real
step change in the way the public now considers and evaluates the companies whose
goods and services they are buying. People inherently want to do good in the
world, and they want to buy products and services from companies who can
demonstrate, in full transparency, that they are also making a positivecontribution to society -- and not just generating dividends and capital growth
for shareholders.
Finally, there’s also been a
step change by many innovative companies that have realized the real value of
fully embracing an environmental,
social, and governance (ESG) agenda. There’s clear evidence that now shows that
companies with a solid ESG policy are more valuable. They sell more. The
company’s valuation is higher. They attract and retain more top talent --
particularly Millennials and Generation Z -- and they are more likely to get
better investment rates as well.
Gardner: The impetus
is clearly there for ethical examination of how you do business, and to let
your costumers know that. But what about the technologies and methods that better
accomplish this? Is there not, hand in hand, an opportunity to dig deeper and
see deeper than you ever could before?
Better business decisions with AI
Harris: Yes, we
have seen a big increase in the number of data and content companies that now
provide insights into the different risk types that organizations face.
We have companies like EcoVadis
that have built score cards on various corporate social responsibility (CSR)
metrics, and Verisk Maplecroft’s indices across the whole range of ESG criteria.
We have financial risk ratings, we have cyber risk ratings, and we have compliance
risk ratings.
These insights and these data
providers are great. They really are the building blocks of risk management. However,
what I think has been missing until recently was the capability to pull all of
this together so that you can really get a single view of your entire supplier
risk exposure across your business in one place.
What has been missing was the capability to pull all of this together so that you can really get a single view of your entire supplier risk exposure across your business.
Technologies such as artificial intelligence (AI), for example, and machine learning (ML) are supporting businesses
at various stages of the procurement process in helping to make the right
decisions. And that’s what we developed here at SAP Ariba.
Gardner: It
seems to me that 10 years ago when people talked about procurement and supply-chain
integrity that they were really thinking about cost savings and process
efficiency. Erin, what’s changed since then? And tell us also about Verisk Maplecroft
and how you’re allowing a deeper set of variables to be examined when it comes
to integrity across supply chains.
McVeigh: There’s
been a lot of shift in the market in the last five to 10 years. I think that
predominantly it really shifted with environmental regulatory compliance. Companies
were being forced to look at issues that they never really had to dig
underneath and understand -- not just their own footprint, but to understand
their supply chain’s footprint. And then 10 years ago, of course, we had the California
Transparency Act, and then from that we had the UK Modern Slavery Act, and
we keep seeing more governance compliance requirements.
 |
| McVeigh |
But what’s really interesting
is that companies are going beyond what’s mandated by regulations. The reason
that they have to do that is because they don’t really know what’s coming next.
With a global footprint, it changes that dynamic. So, they really need to think
ahead of the game and make sure that they’re not reacting to new compliance initiatives.
And they have to react to a different marketplace, as Tony explained; it’s a
rapidly changing dynamic.
We were talking earlier today
about the fact that companies are embracing sustainability, and they’re doing
that because that’s what consumers are driving toward.
At Verisk Maplecroft, we came
to business about 12 years ago, which was really interesting because it came
out of a number of individuals who were getting their master’s degrees in
supply-chain risk. They began to look at how to quantify risk issues that are
so difficult and complex to understand and to make it simple, easy, and
intuitive.
They began with a subset of
risk indices. I think probably initially we looked at 20 risks across the board.
Now we’re up to more than 200 risk issues across four thematic issue categories.
We begin at the highest pillar of thinking about risks -- like politics,
economics, environmental, and social risks. But under each of those risk’s
themes are specific issues that we look at. So, if we’re talking about social
risk, we’re looking at diversity and labor, and then under each of those risk
issues we go a step further, and it’s the indicators -- it’s all that data
matrix that comes together that tell the actionable story.
Some companies still just want
to check a [compliance] box. Other companies want to dig deeper -- but the
power is there for both kinds of companies. They have a very quick way to
segment their supply chain, and for those that want to go to the next level to
support their consumer demands, to support regulatory needs, they can have that
data at their fingertips.
Global compliance
Gardner: Emily,
in this global environment you can’t just comply in one market or area. You
need to be global in nature and thinking about all of the various markets and
sustainability across them. Tell us what EcoVadis does and how an organization
can be compliant on a global scale.
Rakowski: EcoVadis
conducts business sustainability ratings, and the way that we’re using the
procurement context is primarily that very large multinational companies like Johnson and Johnson or Nestlé will come to us and say, “We would
like to evaluate the sustainability factors of our key suppliers.”
 |
| Rakowski |
They might decide to evaluate only
the suppliers that represent a significant risk to the business, or they might
decide that they actually want to review all suppliers of a certain scale that
represent a certain amount of spend in their business.
What EcoVadis provides is a 10-year-old
methodology for assessing businesses based on evidence-backed criteria. We put
out a questionnaire to the supplier, what we call a right-sized questionnaire,
the supplier responds to material questions based on what kind of goods or services
they provide, what geography they are in, and what size of business they are in.
Of course, very small
suppliers are not expected to have very mature and sophisticated capabilities
around sustainability systems, but larger suppliers are. So, we evaluate them
based on those criteria, and then we collect all kinds of evidence from the
suppliers in terms of their policies, their actions, and their results against
those policies, and we give them ultimately a 0 to 100 score.
And that 0 to 100 score is a
pretty good indicator to the buying companies of how well that company is doing
in their sustainability systems, and that includes such criteria as environmental,
labor and human rights, their business practices, and sustainable procurement
practices.
Gardner: More
data and information are being gathered on these risks on a global scale. But
in order to make that information actionable, there’s an aggregation process under
way. You’re aggregating on your own -- and SAP Ariba is now aggregating the aggregators.
How then do we make this
actionable? What are the challenges, Tony, for making the great work being done
by your partners into something that companies can really use and benefit from?
Timely insights, best business decisions
Harris: Other
than some of the technological challenges of aggregating this data across
different providers is the need for linking it to the aspects of the procurement
process in support of what our customers are trying to achieve. We must make sure
that we can surface those insights at the right point in their process to help
them make better decisions.
The other aspect to this is how
we’re looking at not just trying to support risk through that source-to-settlement
process -- trying to surface those risk insights -- but also understanding that where
there’s risk, there is opportunity.
So what we are looking at here
is how can we help organizations to determine what value they can derive from
turning a risk into an opportunity, and how they can then measure the value
they’ve delivered in pursuit of that particular goal. These are a couple of the
top challenges we’re working on right now.
We're looking at not just trying to support risk through that source-to-settlement process -- trying to surface those risk insights -- but also understanding that where there is risk there is opportunity.
Harris: If we
look at some risk aspects such as natural disasters, you can’t react timelier
than to a natural disaster. So, the way we can alert from our data sources on
earthquakes, for example, we’re able to very quickly ascertain whom the
suppliers are, where their distribution centers are, and where that supplier’s
distribution centers and factories are.
When you can understand what
the impacts are going to be very quickly, and how to respond to that, your
mitigation plan is going to prevent the supply chain from coming to a complete
halt.
Gardner: We
have to ask the obligatory question these days about AI and ML. What are the
business implications for tapping into what’s now possible technically for
better analyzing risks and even forecasting them?
AI risk assessment reaps rewards
Harris: If
you look at AI, this is a great technology, and what we trying to do is really
simplify that process for our customers to figure out how they can take action
on the information we’re providing. So rather them having to be experts in risk
analysis and doing all this analysis themselves, AI allows us to surface those
risks through the technology -- through our procurement suite, for example --
to impact the decisions they’re making.
For example, if I’m in the
process of awarding a piece of sourcing business off of a request for proposal
(RFP), the technology can surface the risk insights against the supplier I’m
about to award business to right at that point in time.
A determination can be made based
upon the goods or the services I’m looking to award to the supplier or based on
the part of the world they operate in, or where I’m looking to distribute these
goods or services. If a particular supplier has a risk issue that we feel is
too high, we can act upon that. Now that might mean we postpone the award
decision before we do some further investigation, or it may mean we choose not
to award that business. So, AI can really help in those kinds of areas.
Gardner:
Emily, when we think about the pressing need for insight, we think about both
data and analysis capabilities. This isn’t something necessarily that the buyer
or an individual company can do alone if they don’t have access to the data.
Why is your approach better and how does AI assist that?
Rakowski: In
our case, it’s all about allowing for scale. The way that we’re applying AI and
ML at EcoVadis is we’re using it to do an evidence-based evaluation.
We collect a great amount of
documentation from the suppliers we’re evaluating, and actually that AI is
helping us scan through the documentation more quickly. That way we can find
the relevant information that our analysts are looking for, compress the
evaluation time from what used to be about a six or seven-hour evaluation time
for each supplier down to three or four hours. So that’s essentially allowing
us to double our workforce of analysts in a heartbeat.
AI is helping us scan through the documentation more quickly. That way we can find the relevant information that our analysts are looking for, allowing us to double our workforce of analysts.
And that way we we’re
combining AI with real human analysis and validation to make sure that what we
we’re serving is accurate and relevant.
Harris: And
that’s a great point, Emily. On the SAP Ariba side, we also use ML in analyzing
similarly vast amounts of content from across the Internet. We’re scanning more
than 600,000 data sources on a daily basis for information on any number of
risk types. We’re scanning that content for more than 200 different risk types.
We use ML in that context to
find an issue, or an article, for example, or a piece of bad news, bad media. The
software effectively reads that article electronically. It understands that
this is actually the supplier we think it is, the supplier that we’ve tracked,
and it understands the context of that article.
By effectively reading that
text electronically, a machine has concluded, “Hey, this is about a contracts
reduction, it may be the company just lost a piece of business and they had to
downsize, and so that presents a potential risk to our business because maybe
this supplier is on their way out of business.”
And the software using ML figures
all that stuff out by itself. It defines a risk rating, a score, and brings
that information to the attention of the appropriate category manager and
various users. So, it is very powerful technology that can number crunch and
read all this content very quickly.
Gardner: Erin,
at Maplecroft, how are such technologies as AI and ML being brought to bear, and
what are the business benefits to your clients and your ecosystem?
The AI-aggregation advantage
McVeigh: As an
aggregator of data, it’s basically the bread and butter of what we do. We bring
all of this information together and ML and AI allow us to do it faster, and more
reliably
We look at many indices. We
actually just revamped our social indices a couple of years ago.
Before that you
had a human who was sitting there, maybe they were having a bad day and they
just sort of checked the box. But now we have the capabilities to validate that
data against true sources.
Just as Emily mentioned, we
were able to reduce our human-rights analyst team significantly and the number
of individuals that it took to create an index and allow them to go out and
begin to work on additional types of projects for our customers. This helped
our customers to be able to utilize the data that’s being automated and
generated for them.
We also talked about what
customers are expecting when they think about data these days. They’re thinking
about the price of data coming down. They’re expecting it to be more dynamic,
they’re expecting it to be more granular. And to be able to provide data at
that level, it’s really the combination of technology with the intelligent data
scientists, experts, and data engineers that bring that power together and
allow companies to harness it.
Gardner: Let’s
get more concrete about how this goes to market. Tony, at the recent SAP Ariba Live conference,
you announced the Ariba
Supplier Risk improvements. Tell us about the productization of this, how
people intercept with it. It sounds great in theory, but how does this actually
work in practice?
Partnership prowess
Harris: What
we announced at Ariba Live in
March is the partnership between SAP Ariba, EcoVadis and Verisk Maplecroft
to bring this combined set of ESG and CSR insights into SAP Ariba’s solution.
We do not yet have the
solution generally available, so we are currently working on building out
integration with our partners. We have a number of common customers that are
working with us on what we call our design partners. There’s no better customer
ultimately then a customer already using these solutions from our companies. We
anticipate making this available in the Q3 2018 time frame.
And with that, customers that
have an active subscription to our combined solutions are then able to benefit
from the integration, whereby we pull this data from Verisk Maplecroft, and we
pull the CSR score cards, for example, from EcoVadis, and then we are able to
present that within SAP Ariba’s supplier risk solution directly.
What it means is that users
can get that aggregated view, that high-level view across all of these
different risk types and these metrics in one place. However, if, ultimately
they are going to get to the nth degree of detail, they will have the ability
to click through and naturally go into the solutions from our partners here as
well, to drill right down to that level of detail. The aim here is to get them that
high-level view to help them with their overall assessments of these suppliers.
Gardner: Over
time, is this something that organizations will be able to customize? They will
have dials to tune in or out certain risks in order to make it more applicable
to their particular situation?
Customers that have an active subscription to our combined solutions are then able to benefit from the integration and see all that data within SAP Ariba's supplier risk solutions directly.
If I have more bias toward
that kind of financial risk aspects, or if I have more of the bias toward ESG
metrics, for example, then I can weigh that part of the score, the algorithm,
appropriately.
Gardner: Before
we close out, let’s examine the paybacks or penalties when you either do this
well -- or not so well.
Erin, when an organization can
fully avail themselves of the data, the insight, the analysis, make it
actionable, make it low-latency -- how can that materially impact the company?
Is this a nice-to-have, or how does it affect the bottom line? How do we make
business value from this?
Nice-to-have ROI
Rakowski: One
of the things that we’re still working on is quantifying the return on
investment (ROI) for companies that are able to mitigate risk, because the
event didn’t happen.
How do you put a tangible
dollar value to something that didn’t occur? What we can look at is taking data
that was acquired over the past few years and understand that as we begin to see
our risk reduction over time, we begin to source for more suppliers, add
diversity to our supply chain, or even minimize our supply chain depending on
the way you want to move forward in your risk landscape and your supply
diversification program. It’s giving them that power to really make those
decisions faster and more actionable.
And so, while many companies
still think about data and tools around ethical sourcing or sustainable
procurement as a nice-to-have, those leaders in the industry today are saying,
“It’s no longer a nice-to-have, we’re actually changing the way we have done
business for generations.”
And, it’s how other companies
are beginning to see that it’s not being pushed down on them anymore from these
large retailers, these large organizations. It’s a choice they have to make to
do better business. They are also realizing that there’s a big ROI from putting
in that upfront infrastructure and having dedicated resources that understand
and utilize the data. They still need to internally create a strategy and make
decisions about business process.
We can automate through
technology, we can provide data, and we can help to create technology that embeds
their business process into it -- but ultimately it requires a company to
embrace a culture, and a cultural shift to where they really believe that data
is the foundation, and that technology will help them move in this direction.
Gardner: Emily,
for companies that don’t have that culture, that don’t think seriously about
what’s going on with their suppliers, what are some of the pitfalls? When you
don’t take this seriously, are bad things going to happen?
Pay attention, be prepared
Rakowski: There
are dozens and dozens of stories out there about companies that have not paid
attention to critical ESG aspects and suffered the consequences of a horrible
brand hit or a fine from a regulatory situation. And any of those things easily
cost that company on the order of a hundred times what it would cost to actually
put in place a program and some supporting services and technologies to try to
avoid that.
From an ROI standpoint,
there’s a lot of evidence out there in terms of these stories. For companies
that are not really as sophisticated or ready to embrace sustainable
procurement, it is a challenge. Hopefully there are some positive mavericks out
there in the businesses that are willing to stake their reputation on trying to
move in this direction, understanding that the power they have in the
procurement function is great.
They can use their company’s
resources to bet on supply-chain actors that are doing the right thing, that
are paying living wages, that are not overworking their employees, that are not
dumping toxic chemicals in our rivers and these are all things that, I think,
everybody is coming to realize are really a must, regardless of regulations.
And so, it’s really those
individuals that are willing to stand up, take a stand and think about how they
are going to put in place a program that will really drive this culture into
the business, and educate the business. Even if you’re starting from a very
little group that’s dedicated to it, you can find a way to make it grow within
a culture. I think it’s critical.
Gardner: Tony,
for organizations interested in taking advantage of these technologies and
capabilities, what should they be doing to prepare to best use them? What
should companies be thinking about as they get ready for such great tools that are coming their way?
Synergistic risk management
Harris:
Organizationally, there tend to be a couple of different teams inside of
business that manage risks. So, on the one hand there can be the kind of
governance risk and compliance team. On the other hand, they can be the corporate
social responsibility team.
I think first of all, bringing
those two teams together in some capacity makes complete sense because there
are synergies across those teams. They are both ultimately trying to achieve
the same outcome for the business, right? Safeguard the business against
unforeseen risks, but also ensure that the business is doing the right thing in
the first place, which can help safeguard the business from unforeseen risks.
I think getting the
organizational model right, and also thinking about how they can best begin to
map out their supply chains are key. One of the big challenges here, which we
haven’t quite solved yet, is figuring out who are the players or supply-chain
actors in that supply chain? It’s pretty easy to determine now who are the
tier-one suppliers, but who are the suppliers to the suppliers -- and who are
the suppliers to the suppliers to the suppliers?
Once you get the mapping done, our software and our partners' software surfaces those kinds of risks across the entire supply chain.
Gardner: I’m
afraid we will have to leave it there. You’ve been listening to a sponsored BriefingsDirect
discussion on new ways that companies are gaining improved visibility,
analytics, and predictive responses to better manage supply-chain risks.
And we’ve learned how new tools
and methods can be combined for easy assessment and remediation of hundreds of
supply-chain risks. So, a big thank you to our guests, Tony Harris, Global Vice
President and General Manager of Supplier Management Solutions at SAP Ariba; Erin
McVeigh, Head of Products and Data Services at Verisk Maplecroft, and Emily
Rakowski, Chief Marketing Officer at EcoVadis. Thank you, all.
I’m Dana Gardner, Principal Analyst
at Interarbor Solutions, your host throughout this series at SAP Ariba-sponsored
BriefingsDirect discussions. Thanks again for listening and do come back next
time.
Listen to the podcast. Find it on iTunes.
Get the mobile app.
Download
the transcript. Sponsor: SAP Ariba.
Transcript
of a discussion on new
ways that companies gain improved visibility, analytics, and predictive responses
to better manage supply-chain risk and sustainability factors. Copyright
Interarbor Solutions, LLC, 2005-2018. All rights reserved.
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