In the news release, SAS helps organizations unlock the
unrealized potential of their analytics investment, issued
02-Oct-2019 by SAS over PR Newswire,
we are advised by the company that the quote in the 6th paragraph
should be updated to read "Most companies struggle to move past the
experimentation phase to unlock real value. Our research tells us
that implementation challenges, integrating AI into the company's
roles and functions, data issues (e.g., data privacy, accessing and
integrating data), cost of AI technologies/solution development and
lack of skills are the top challenges faced by early adopters. To
help clients accelerate the adoption of AI, Deloitte has made
significant investments, including establishing Centers of
Excellence, to educate, deliver, scale and manage AI and Analytics
solutions in a cost-effective manner," said Nat D'Ercole, partner
at Omnia AI, Deloitte Canada's
Artificial Intelligence practice. The complete, corrected release
follows:
SAS helps organizations unlock the unrealized potential of their
analytics investment Comprehensive offering addresses costly
business challenge as more than half of a data scientist's work
never gets beyond the lab
CARY, N.C., Oct. 2, 2019 /PRNewswire/ -- According to IDC,
only 35% of organizations indicate that analytical models are fully
deployed in production.* This results in wasted effort and wasted
money. With organizations investing approximately $189.1 billion in analytics this year alone, the
deployment of analytical models and generating value from data is
more critical than ever. SAS, the leader in analytics, is helping
businesses complete the last mile of analytics and reach their
goals through new offerings, services and education.
![](https://mma.prnewswire.com/media/414673/SAS_Institute_Logo.jpg)
Available now, SAS® ModelOps, is a new packaged
offering combining SAS Model Manager software and advisory
services. The offering streamlines the management, deployment,
monitoring, retraining and governance of both SAS and open source
analytical models. To jumpstart success, it provides the added
benefit of tailored consulting services. Additionally, SAS is
introducing a new standalone service, ModelOps Health Check
Assessment, intended to help organizations understand how to
optimize deployment.
"The inability to put analytics into action is one of the
biggest challenges across industries," said Dan Vesset, Group Vice
President of Analytics and Information Management at IDC. "Many
organizations adopt a data-driven culture but struggle to actually
apply changes that the data suggests. The finish line is to
generate real business value from analytics investments, but many
businesses are never reaching it, or struggle with the so-called
'last mile' of implementing, operationalizing and putting analytics
to work."
Jim Goodnight, CEO of SAS, said:
"This is because data doesn't drive an organization, decisions do.
And we know analytically-driven decisions are better. Analytical
models can detect credit-card fraud, manage banking risk, improve
marketing accuracy and so much more. SAS knows how to work with
companies to finish this last mile and put their analytics, AI and
data investments to work."
Running the last mile with SAS
As organizations
accelerate adoption of AI and machine learning, analytical assets
and models are rapidly multiplying. In recent years model
development has become more prevalent to solve business problems,
but deployment and governance remains the final hurdle. SAS helps
organizations across the entire analytics lifecycle – from
automated model development that is not only transparent, but
customizable, to model explainability in plain English, to model
deployment.
"Most companies struggle to move past the experimentation phase
to unlock real value. Our research tells us that
implementation challenges, integrating AI into the company's roles
and functions, data issues (e.g., data privacy, accessing and
integrating data), cost of AI technologies/solution development and
lack of skills are the top challenges faced by early
adopters. To help clients accelerate the adoption of AI,
Deloitte has made significant investments, including establishing
Centers of Excellence, to educate, deliver, scale and manage AI and
Analytics solutions in a cost-effective manner," said Nat D'Ercole,
partner at Omnia AI, Deloitte
Canada's Artificial Intelligence practice.
Norwegian telecommunications company Telenor has also
seen success with fast, effective model deployment with SAS.
Serving Scandinavia and Asia,
Telenor has an incredible amount of customer data. But the company
needed help using this data to create a personalized customer
experience. Together with SAS, Telenor Norway uses 10-20 predictive
models to calculate the customers likelihood to buy relevant
offers. Armed with this analysis, SAS and Telenor Norway developed
and implemented a guided tool, called Automated Sales Tips (AST).
AST puts analytics into action, determining in half a second the
best offers for each customer contacting Telenor utilizing the
scores from the predictive models. The models are managed and
monitored using SAS Model Manager, providing a way to monitor the
quality of the models over time and a report used as a basis for
their monthly model management meeting.
SAS also enabled the marketing division of Germany's Commerzbank to deploy
data-driven models that improved the customer experience. While
analytics is used daily in business, now it can be integrated in
all customer-centered decisions – inbound and outbound – for every
touchpoint with Commerzbank's customers, in real-time, at
scale.
Customer-centricity is equally important in an evolving retail
landscape. Connect Financial Services (CFS), a subsidiary of
the JD Group and Pepkor, the largest non-grocery retailer in
South Africa, use SAS to gain the
competitive edge. The JD Group, with more than 850 stores operating
across four countries, receives a large number of customer credit
applications each day. By automating much of the credit decisioning
process with machine learning and advanced analytics, CFS can make
relevant offers to customers while still mitigating risk to the
retailer.
"SAS allows us to make intelligent decisions," said Eugene Ehlers, CFS Credit Executive at
Pepkor. "Internally, we refer to 'SAS as the brain.' We can
quickly deploy changes and additions to our credit decisioning
models in real-time, which allows us to ensure that the right
amount of credit is offered to the customer when and where the
customer needs it."
Moving organizations forward with ModelOps
According
to McKinsey, the total annual value generated by analytics and
AI is between $9.5 trillion and
$15.4 trillion. But without the
ability to push analytical models into production, much of this
potential value is lost. ModelOps is where analytical
models move from the data science "lab" into IT production, with a
regular cadence of updates and deployments as these models are
managed, scaled, monitored and retrained as needed. In the race to
realize value from analytics, ModelOps is a winning ingredient that
only a few companies are using.
SAS ModelOps meets the need for model management software paired
with advisory services that can be tailored to meet a customer's
specific requirements. The offering will help customers to
jumpstart their implementation, use and adoption of SAS Model
Manager so that they can operationalize analytics in a consistent,
continuous manner. SAS ModelOps also enables customers to monitor
the performance of all champion models to ensure relevance as data
and market conditions changes over time.
SAS believes that to finish the last mile, analytics needs to
emulate the applications-development community's approach to
collaboration – DevOps – and adopt practices that will accelerate
model creation and deployment. The ModelOps Handbook, available for
download later this year, is a technology-agnostic handbook that
helps organizations accelerate the analytics life cycle through
repeatable best practices. With a focus on building collaboration
and processes to facilitate the handoff between the development and
deployment phases, the goal of the ModelOps Handbook is to reduce
the time to deployment and increase organizational capacity to
create, train and refine analytical models.
Because deployment of analytical models is both challenging and
valuable, SAS is also introducing a new service, ModelOps Health
Check Assessment. Through an on-site workshop, organizations can
determine their level of maturity and readiness to successfully
deploy and manage analytical models. The assessment also provides
recommendations to move the company forward to make better
decisions.
To learn more about how SAS can help organizations conquer the
last mile of analytics, visit sas.com/discover or follow the
conversation on social media using the hashtag #DiscoverSAS.
* IDC's Advanced and Predictive Analytics survey and
interviews, n = 400, 2017 – 2019.
About SAS
SAS is the leader in analytics. Through innovative software and
services, SAS empowers and inspires customers around the world to
transform data into intelligence. SAS gives you THE POWER TO
KNOW®.
SAS and all other SAS Institute Inc. product or service names
are registered trademarks or trademarks of SAS Institute Inc. in
the USA and other countries. ®
indicates USA registration. Other
brand and product names are trademarks of their respective
companies. Copyright © 2019 SAS Institute Inc. All rights
reserved.
Editorial Contact:
Ashley
Binder
ashley.binder@sas.com
919-531-3575
sas.com/news
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