Automation’s role in digital transformation is nothing new, but the disruptions of recent years have exposed the limitations of our efforts to this point. Does that feel familiar? If so, you’re not.   We’re seeing so many companies double down on the development and deployment of automation as quickly and broadly across their organizations as possible. In other words, hyperautomation.   These efforts include adopting automation platforms with flexible, contingent workflow solutions that drive efficiencies and greater data integrity across multiple complex, data-intensive processes.   To learn more, watch our webinar – featuring guest speaker Maureen Fleming, Program Vice President for IDC's Intelligent Process Automation research, and Andrew Hayden, Sr. Product Marketing Manager at Precisely.   Maureen will share recent research and insights from IDC on the importance of process automation to digital transformation, along with predictions for the future. Andrew will then share some of the challenges we’re hearing from our customers around automating complex, data-intensive business processes, and the features you should look for in an automation platform.   You can expect to come away with insights into:   ·         How digital transformation and automation are evolving ·         How to avoid the key challenges with automation that slow down transformation benefits ·         Market perspective from the automation provider’s point of view ·         How a complete automation platform supports hyperautomation success

1. The Future of
Automation:
Insights from IDC and
Precisely
Andrew Hayden, Sr. Product Marketing Manager, Precisely
Maureen Fleming, Program Vice President, AI and
Automation Research, IDC

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3. Today’s speakers
Andrew Hayden
Sr. Product Marketing Manager,
Precisely
Maureen Fleming
Program VP, AI and Automation
Research, IDC

4. Maureen Fleming
Program VP, AI and Automation
November 2023
The Future of Business Automation

5. 5
© IDC |
Agenda
1. Shifting to data- and insights-driven planning and execution
2. Orchestrating automation end-to-end
3. Transforming automation with GenAI

6. 6
© IDC |
Business controls more than half of new software purchasing
• By 2027, businesses will control 73% of application purchasing
and 53% of investments in business automation, database
management, AI, and analytics*
Transformation is technologically enabled
• Technology is more strategic
• Growing percentage of operating costs
As businesses fund technology projects, they have questions
• If we migrate our ERP, what is the ROI?
• Cloud was supposed to lower our costs. What happened?
• If task automation increases productivity, why hasn’t that improved
our bottom line?
Business Control over New Software Investments Shifts Focus to Accountability
*Source: IDC Worldwide IT Spending Guide 2023
10%
19%
71%
Decreasing focus on automation
because of difficulty tracking business
value delivered
Not critical. Satisfied with automation
success
This has become a top priority and
concern
How important is it to your automation strategy to tie
automation to business value delivered?**
**Source: IDC Worldwide Automation and Process Improvement Survey, 2023. Executive respondents N=300

7. 7
© IDC |
Skills Are Needed to Align Automation Improvements with Business Value
Automation efforts are tied to business process improvement.
They are also tied to value stream initiatives to improve the
delivery of service to customers
• Improve productivity
• Decrease cycle times
• Enforce compliance
• Increase quality
• Improve customer satisfaction and competitiveness
Metrics provided out-of-the-box with automation platforms do
not align with the top objectives of process improvement
They do not generate the set of KPIs that align with process
improvement objectives
Top 3 challenges in automation
43%
38%
38%
Building the metrics
to demonstrate
success
Too expensive,
making it difficult to
justify many business
cases
It is sometimes too
difficult to spot
automation
opportunities
Source: IDC Worldwide Automation & Process Improvement Survey, 2023; N=300
Without useful metrics to show concrete value, automation
programs struggle to scale their efforts

8. 8
© IDC |
Refocusing Technology Investments on Outcomes
Data Capture & Analysis Documentation & Design Business Observability
Process Mining Task Mining
Simulation Improvement
KPI Definitions
BPMN Modeling
Improvement
Design
Process Definition
Document
Process Design
Document
Monitoring
Reporting
Predictive Analytics
Notifications
DMN Modeling
Policies
Closed Loop
Metrics
KPI Performance Assessment
Improvement
Pipeline
Business value engineering is a data and insights driven methodology and set of tools for
process planning and continuous improvement.
• Built on a BPM foundation, value engineering replaces a technology-first approach to automation and process improvement
by aligning technology selection with purpose
• Delivers a metrics-based business case with closed loop measurement as improvements move into production
• Spots business problems quickly for rapid improvement
• Early detection of process inefficiencies

9. 9
© IDC |
Agenda
1. Shifting to data- and insights-driven planning and execution
2. Orchestrating automation end-to-end
3. Transforming automation with GenAI

10. 10
© IDC |
No one technology dominates for
automation and process improvement
projects
Priorities for 2023-24 are to increase
investments in case management, business
rules, data integration, and RPA
33% of respondents struggle with tying
together the diverse automation
technologies together
14%
17%
18%
21%
22%
24%
26%
26%
27%
28%
30%
Event brokers/messaging
Case management
Business rules
Knowledge discovery or search
Low code application platforms
Conversational AI (or chatbots)
Data integration
Workflow automation
API integration
Robotic process automation
Document automation
Mix of Automation Technologies Regularly Used
Source: IDC Worldwide Automation & Process Improvement Survey, 2023; N=300

11. 11
© IDC |
When multiple automation
technologies are used together,
automation COEs are challenged to
implement them in a coordinated
and seamless way
A new orchestration layer is
emerging that handles seamless
coordination across diverse
automation technologies
Two approaches are emerging
• Broaden single platform automation
portfolio
• Use orchestration layer to connect 3rd
party automation technologies
Solving the Hurdle of Using Multiple Automation Technologies Seamlessly

12. 12
© IDC |
Agenda
1. Shifting to data- and insights-driven planning and execution
2. Scaling automation end-to-end
3. Transforming automation with GenAI
Source: IDC Worldwide Automation & Process Improvement Survey, 2023; N=300

13. 13
© IDC |
The AI Everywhere Chapter in the Digital Business Era
AI
Everywhere
Widening
AI
Generative AI Use Case
Use Case
Use Case
Use Case
Use Case
Use Case
Use Case
Use Case
Use Case
Use Case
Business
Value
Time
2010
Multiplied
Innovation
Mobility
Cloud
Internet Social
Use Case
Use Case
Use Case
Use Case
Platforms &
Communities
Narrow AI
LLMs
APIs
XaaS
Use Case
Use Case
Use Case
Use Case
Use Case
Use Case
2035
Digital Business: Innovation at Scale
A new chapter in the Digital Business Era is
starting now – AI Everywhere.
Generative AI triggered the opening of this
new chapter because it seeks to drastically
reducing the time and long-term costs
associated with developing solutions across a
wide range of use cases associated with
automation and intelligence.
This chapter will be about how we use data as
an input and as a business outcome.

14. 14
© IDC |
Most Organizations Are Still in the GenAI Exploration Phase
Source: GenAI ARC Survey, IDC, August 2023, N=1,363, NA: 405, AP: 454, WE: 403, META 101 Data weighted by IT spend

15. 15
© IDC |
Executives see promise in using GenAI for classic
process improvement initiatives by improving customer
service, revenue growth and cycle time improvements
The ability to generate recommendations that enable
staff to make better decisions is an emerging area as
we move from business rules-based decision
automation to AI
Automation teams have begun to experiment with
GenAI. Use cases include:
• Expansion of document automation to include unstructured
use cases
• Creating specialized AI models based on regulations, code
and policies that extend automation to new use cases
• Broadening use of chat interface to interactively automation
GenAI Business Benefits, Risks and Use Cases
Top Insights On Benefits Sought by C-Suite
Top Insights On Risks That Concern the C-Suite

16. 16
© IDC |
3 Key Takeaways
Plan to executive business value engineering collaboratively, with different roles involved
with different parts of the process:
• Business analysts for all phases
• Subject matter experts for initial analysis
• Data engineers to capture the data
• IT for requirements
• Financial analysts to help build a business case
The orchestration layer for end-to-end automation will largely be available from
automation platforms supporting multiple technologies.
• Look for a comprehensive platform that can also leverage existing technology investments.
GenAI will broaden the footprint available for automation but will not replace the need
to track the value of technology investments.
• If you haven’t already started with GenAI experiments, look for areas that extend automation.
• For example, government-supplied or industry-specific references collections can fine tune foundation models to
extend automation into new areas.

17. © IDC
linkedin.com/company/idc blogs.idc.com
twitter.com/idc
IDC.com
For More Information
Maureen Fleming
mfleming@idc.com

18. The Future of
Automation
Andrew Hayden | Precisely
Insights from Precisely

19. Agenda
• Automation and digital transformation
• The value of an automation platform
• Success stories
• Artificial intelligence in automation
• Key takeaways
• Fireside Chat
• About Precisely

20. Automation,
hyperautomation
and digital
transformation
20

21. Accelerating digital transformation
Data is the fuel for decision-making today
80% of CEOs
accelerating
digital
transformation
45% of
enterprises
using SAP are
leveraging
automation
67% spending
more on
technology than
people
$60.5 billion
spent
on intelligent
automation in
2027
IDC KPMG KPMG ASUG

22. Complexity is
multidimensional
Data complexity
• Complexity of SAP master
data records
• High-volume data
processes
• Challenges data
complexity creates for
manual data entry and
management processes
Presentation name
22
Process complexity
• Complex, data-intensive
business processes
involving multiple
constituents are a
challenge to automate
• Process governance and
tracking
• Human-in-the-loop
processes pose unique
challenges for
automation
Organizational
complexity
• Multi-departmental
processes
• Competing business
priorities
• Short-term gains vs
strategic initiatives

23. Be more agile
Customer needs:
Go faster Improve the quality and
integrity of your most
important data

24. Technology is a means to
an end: Data is the
currency of digital
transformation
- HfS Blog

25. Data
Process
Interdependence of process and
data
Interdependence of process and data

26. Why an automation
platform?
26

27. A complete automation platform
Excel to SAP
Exchange data with SAP
quickly and easily using
Excel
Form & Workflow
Automate and accelerate
SAP business processes
with integrated forms and
workflows
Excel Workflow
Automate and accelerate
SAP business processes
through Excel file
management workflows
Process
Automation
Data
Automation

28. Form &
Workflow
Automate account
creation with forms
and workflow across
multiple contributors
Process
Initiator
Enter basic
account
information
Contributor 1
Contributor 2
Contributor 3
Approver
Start with
create form
SAP
Automate Evolve
Outside
Contributor
Portal
Participan
t

29. Additional automation platform benefits
Connectivity
(APIs)
Governance
Low-code
development
Attended &
unattended
automation
Data quality
Cloud
deployment

30. Empowering business
teams to make an impact

31. Example
Results
Value delivered through
automating processes across the
SAP landscape
20,000
Journal entries processed during 4-
day close window
• Speed and improved data quality
• Auditability
• Team continued to work in Excel
50%-75% 90%
Reduction in time to market
• Agility and speed
• Increases competitive advantage
Reduction in cost to process
materials changes
• Lower costs
• Maintain current staffing levels
• Faster ROI
87%
Reduction in time needed to qualify
vendors and materials
• Speed
• Process visibility
• Improved productivity
97%
Reduction in time to create a
customer
• Agility and speed
• Increases competitive advantage

32. Make an impact across your business
Financial
Accounting
Controlling
Sales and
Distribution
Materials
Management
Plant
Maintenance
Asset
Management
Project
Systems
Production
Planning
Quality
Management
Human
Resources

33. Artificial Intelligence
33

34. Digital Transformation Activities
Data &
Processes
Automation
Cloud
AI/ML
Business Networks and
cross-company collaboration
User Experience
Supply Chain Digitalization
Self-service
End-to-end process
integration
Process Mining

35. AI comes in various flavors
Generative AI Predictive AI
Goal Create new content Make accurate predictions
Algorithms
Complex algorithms and deep learning
based on LLMs
Statistical algorithms based on machine
learning and observations
Output
New content such as text, images,
music, etc.
Predictions such as the likelihood of a
field value or routing destination

36. Material Master Creation
Constant new product
introductions and
changes
Highly manual, complex
process with lots of
possible data entry error
points
Create or update
products

37. Material Master Creation
To improve data
quality, companies
typically set out to
define 100s of data
validation rules
Embed your business
rules
to improve data quality

38. Challenges in establishing business
rules
Heavy reliance on
SMEs and tacit
knowledge
Gaining cross-
functional
alignment is time
consuming
What if you could eliminate the need for many of
these rules by using Artificial Intelligence?

39. Master Data Creation with AI
AI output fields are
used to pre-
populate and
validate form fields
User enters
minimum
number of input
fields
New material
creation request
AI predicts output
fields based on
delivered input
fields

40. Presentation name
AI Recommendation
Output
40

41. Benefits of AI for Automation
• Improve decision-making through recommendations
• Improve data quality through AI-based checks
• Create rules and predictions that are not possible without AI
• Reduction of hard-coded rules
• Reduce time to value

42. Automation: Takeaways
Agility Speed Improved data
quality
Business team
focus
Automation
flexibility
Scalability Proven track
record
Process visibility

43. Fireside Chat

44. Winshuttle is
now part of
Precisely,
the leader in
data
integrity

45. The global leader
in data integrity software
Our data integrity software, data
enrichment products, and strategic
services deliver accuracy,
consistency, and context to power
confident business decisions.
Brands you trust, trust us
Data leaders partner with us
of the Fortune 100
99
Customers in more than
100
2,500
employees
customers
12,000
countries
Integrate
Enrich Locate
Verify
Data
Integrity
Suite

46. Let’s continue the
conversation…
Contact us
Set up a 30-minute
personalized demo
+1-877-700-0970
“Get in touch” on
www.precisely.com
www.precisely.com
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47. Thank you!

48. Questions?