The only dedicated B2B publication focused squarely on the ...PREVIEW EDITION WHO WE ARE: RPA Today...

- Media Kit -PREVIEW EDITION

The only dedicated B2B publication focused squarely on the IA, RPA and AI space.

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R P A T o d a y . n e t | PG. 2


PREVIEW EDITIONWHO WE ARE:

RPA Today is the only dedicated B2B publication focused squarely on the IA, RPA and AI space. We launched the online publication in July of last year & our weekly newsletter soon followed in August. Our website now attracts approximately 400+ visits per day, our subscriber base has grown to nearly 6,000 readers in the last year and our focused content is open and viewable to any visitor.

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CIO HANDBOOK | WHITE PAPERPG. 6

RPAToday .net

Anticipate Teams’ Needs

Waiting for ideas to come in from all corners of an organizations is a good start, but it will not be sufficient to avoid the issues that can arise from employees accessing technology they feel they need but are not getting from their IT department.

Even more trust can be generated by anticipating those needs. This is really an extension of open lines of communication Richard says he has tried to establish. Conversations need to reach down to the conceptual level where IT can draw their own conclusions about what technology or what process might be automated to serve the overarching goals of a department, without actually getting direct suggestions.

“All our departments provide different strategic value to the organization,” he explains. “My role is to understand what all the different departments are working on. Then I go back to my team and, because our platform gives us the ability to build something quickly, we can ‘straw-man’ an application we think will solve a certain problem in the service of a strategic goal of a certain department. Then we can present them with the framework of a project they never asked for, but that could get them started on automating a process they hadn’t been thinking about.”

Richard then lets the department take ownership of the process and hopefully improve on the start IT gave them.

Iterative Learning

As a company adds features to their automation technology platform—RPA, AI, natural language processing, optical character recognition, automatic document processing,

Nuts and Bolts Application: Richard

points to a training management program

as an example of anticipating and

supporting the needs of the organizations.

Without a request from LIUNA’s Education

Department, his team saw the process and

understood the improvements that could

be made by rebuilding it in Appian.

“We looked at the old application they

were using and stood up a straw man

of what that system could look like in

Appian,” he tells. “Once that was built we

brought in the Education Department for

feedback and quickly iterated through a

few releases and got it into production.”

When I signed on with LIUNA eight years ago, I had a small budget and a small staff and I needed a technology

solution to get a lot done

“

“

CIO HANDBOOK | WHITE PAPERPG. 3

RPAToday .net

Matthew Richard, CIO

Matt Richard is CIO of the Laborers’ International Union

of North America (LIUNA). LIUNA has represented

construction, municipal and healthcare workers, as

well as mail handlers, in the U.S. and Canada since

1903. While labor unions are not considered bastions

of innovation, since Richard was hired to lead the IT

department eight years ago, he has committed to

automation to serve LIUNA’s members and to give

employees of LIUNA everything they need in terms of

technology solutions.

Automation software, in one form or another, has been

available for decades. As RPA and artificial intelligence

are integrated into increasingly powerful solutions, new

converts are seeking counsel from experienced CIOs.

Richard has embraced automation as a valuable tool to

advance his organization and, more importantly, the

people that comprise it.

Empowering, not replacing, people is an insight that

has informed his thinking about automation since

before he was elevated to the C-suite. Automating

complex business processes in the real world requires

technology—including RPA and AI—and people.

As a CIO considering automation, what is the roadmap

that will make it possible for an organization to

benefit from automation and RPA and buy in without

fear? What steps do you need to take to ensure that

corporate departments trust IT and do not resort to

downloading applications without your knowledge,

jeopardizing long-term security and cohesion in

exchange for short-term flexibility?

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Va l idat ing the Success o f RPA PG. 2

RPAToday .net

Robotic Process Automation (RPA) is smoking hot. The RPA

software market grew 63% from 2018 to 2019, according to

Gartner, reaching $846 million in sales in 2018, headed toward

$1.3 billion last year1. And, when the Covid-19 pandemic hit,

forcing businesses worldwide into survival mode, automation

solutions, including RPA, emerged as important technologies

enabling companies to maintain productivity even as they

might have been forced to reduce headcount

As businesses move past Covid and its effects, experts predict

spending on automation and RPA to continue to grow. A KPMG

report said 43% of technology executives expect to increase

spend on RPA compared to only 25% whose organizations will

invest less2.

So, despite a global economic slowdown, organizations are still

rushing to implement RPA programs. And that impatience can

create challenges. Buying the software and getting bots into

production quickly doesn’t ensure they will be effective. To

optimize return on investment (ROI), businesses must be able

to accurately measure and validate the effect RPA has on the

processes they have automated.

How productive is your RPA program, what are the metrics that

can demonstrate that productivity and how do you go about

identifying and analyzing those key performance indicators

(KPIs)?

Many organizations are not able to answer those questions on

their own.

1. Market Share Analysis: Robotic Process Automation, Worldwide, Gartner, June 20192. Enterprise reboot, KPMG and HFS, August 2020

Va l idat ing the Success o f RPA PG. 4

RPAToday .net

The Conclusions – The average optimization percentage of all the processes analyzed (88%) is at the

high end for any RPA implementation, so, overall, the pilot would be considered successful. But, the

success might not be obvious if all the company was using to evaluate the program is time saved.

The 1,395 hours released per year equates to just about two-thirds of a full-time employee (FTE)

for the bank. Although the FTE is low, however, the analysis also shows that the number of process

executions in a given period of time does not change. That suggests that the most impact this RPA

implementation had is not on the process itself, but on error reduction.

The high rate of correct executions drastically reduced the time required for bank employees to fix

errors the process resulted in.

BEECKERCO

Percentage Optimized by Process [%/Exec]Pe

rcen

tage

[%/e

xec]

0%

25%

50%

75%

100%

ProcessesBan_RPA_01 Ban_RPA_03 Ban_RPA_05 Ban_RPA_07 Ban_RPA_09 Ban_RPA_11 Ban_RPA_13 Ban_RPA_15 Ban_RPA_17 Ban_RPA_19

77%

99%99%

88%84%

95%91%

95%98%

71%

59%

71%

94%96%96%

67%

97%95%94%92%

% Average: 88.0%

BEECKERCO

Time Optimized by Process [min/exec]

Tim

e [m

in/e

xec]

0

54

108

161

215


184.0

119.1

59.1

212.0

8.4

23.818.3

23.817.6

4.23.56.2

22.528.9

19.2

3.3

27.223.823.613.8

BEECKERCO

Optimized TIME [hrs/month]

Tim

e [h

rs/m

onth

]

0

5

10

15

20

ProcesosBan_RPA_01 Ban_RPA_03 Ban_RPA_05 Ban_RPA_07 Ban_RPA_09 Ban_RPA_11 Ban_RPA_13 Ban_RPA_15 Ban_RPA_17 Ban_RPA_19

3.12.0

1.0

3.5

0.10.41.21.6

5.9

1.41.22.1

7.5

9.6

6.4

1.1

9.1

15.915.7

18.5Time Spent [hrs/month]

User Bots

116.5 9.3

Time Released [hrs/month]

107.3

Optimized Percentage

92.1 %

BEECKERCO

Optimized TIME [hrs/year]

Tiem

po [h

rs/a

ño]

0

58

115

173

230


36.823.8

11.8

42.4

1.74.814.619.1

70.6

16.914.125.0

90.1

115.6

76.7

13.3

108.9

190.6189.0

221.5Time Spent [hrs/year]

User Bots

1,514.9 120.3

Time Released [hrs/year]

1,394.5

Optimized Percentage

92.1 %

WHITE PAPER

- Validating the Success of RPA -



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