Instruction is in the file
write a recommendation memo for Agoda
W17429
AGODA: PEOPLE ANALYTICS AND BUSINESS CULTURE (A)
Ken Mark wrote this case under the supervision of Professor Kenneth T. Goh solely to provide material for class discussion. The
authors do not intend to illustrate either effective or ineffective handling of a managerial situation. The authors may have disguised
certain names and other identifying information to protect confidentiality.
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Copyright © 2017, Richard Ivey School of Business Foundation Version: 2017-07-19
INTRODUCTION
On a typically hot day in Bangkok, Thailand in early March 2016, Robert Rosenstein, chief executive
officer (CEO) of Agoda Company Pte. Ltd. (Agoda), was having a morning coffee with Peter Allen, vice-
president of People and Organization Development. Agoda, an online accommodation service, was the
Asia-based subsidiary of The Priceline Group, Inc. (Priceline). Rosenstein observed to Allen,
We are a global leader in using data and analytics to optimize our e-commerce platform, but how
advanced are we in terms of data and analytics in the people function? We know that this is
central to the people department mission, but we need to make sure, as we do with our platform,
we can correlate investment with outcomes, while also staying true to our culture. How far along
are we, Peter?
Allen replied, “We’ve implemented Workday, a human resource (HR) information system that provides a
lot of data, which we’ve been studying, and we are investing in customization of that platform so it can
serve our specific needs.” The challenge was how incremental investments could—or should—be
justified. Allen noted:
In particular, we’re also installing Greenhouse, a new applicant tracking system for recruitment
that will provide us with additional insights into how effectively we are recruiting. We are
starting to look at the recruiting data much more as we look at conversion on our core platform,
finding areas of opportunity and developing best practices.
Helping Allen and his team make this vision a reality was Jeffrey Lee, Agoda’s director of Operations and
Compensation. Lee had spent the past year overseeing the development and introduction of a number of
software tools to assist managers in compensation and other areas of operations. The next stage of the
operation team’s plan was to oversee the implementation of Greenhouse.
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Rosenstein challenged Allen:
We need to be sure these tools provide insights for managers to manage talent more effectively.
We need managers to own the outcomes of talent management rather than delegate that
responsibility to the people team. We need to be very careful about any unforeseen cultural
changes: the last thing we want is to put a system in place that moves us in the wrong direction
from a management philosophy perspective. If managers think that the people team needs to own
more as the result of this new system, we will have done something wrong.
In 2016, Priceline and Expedia, Inc. dominated the global online travel agency market, serving consumers
with millions of properties under contract.1 Through online sites such as Booking.com, Agoda,
Priceline.com, OpenTable, Rentalcars.com, and KAYAK, Priceline was the leader in worldwide online
accommodation reservations. Priceline customers could use the group’s services to book hotel stays,
rental cars, airline tickets, vacation packages and cruises, and even restaurant reservations. In 2015,
Priceline generated US$2.6 billion2 in net income from $9.2 billion in revenues and $55.5 billion in gross
bookings, employing 15,500 people in total.3 Priceline’s success was remarkable—especially considering
that in the early 2000s, it had suffered near-catastrophic losses. Fortunately, the firm had retained enough
cash—raised from investors during the dot-com boom of the late 1990s—to reinvent itself.
Priceline’s turning point was a 2002 decision by Jeffery H. Boyd, then the company’s new CEO, to focus
on accommodations, offering great terms to hotels—the company’s suppliers—and the strategy of
expanding by acquiring strong regional online travel agency brands. Priceline paid $133 million for
Netherlands-based Bookings in 2005, and two years later, the renamed Booking.com grew from a small
base to account for half of Priceline’s bookings.
A focus on expansion in Asia led Priceline to purchase Agoda in 2007 for $16 million in cash and up to
$142 million in performance incentives.
Rosenstein had travelled to Southeast Asia as a backpacker in 1991. Returning in 1998, he invested in an
online hotel reservation business. Along with a co-founder, in 2002, he formed a partnership that would
ultimately launch Agoda in 2005. He led the firm as president and chief operating officer, and managed it
through the acquisition by Priceline, becoming CEO in 2010. By 2016, Agoda had grown from a small
startup with a handful of employees to a multinational with 40 offices in 31 countries, and over 2,500
employees. Agoda, headquartered in Singapore and with a significant presence in Bangkok, served
consumers globally (see Exhibit 1).
With its inventory of more than one million accommodations, Agoda’s business was remarkably
complex. For example, for each hotel listing, there were typically at least 10 available room types (e.g.,
1 Dennis Schaal, “Priceline vs Expedia: By the Numbers in First Quarter 2015,” Skift, May 8, 2015, accessed November 1,
2016, https://skift.com/2015/05/08/priceline-vs-expedia-by-the-numbers-in-first-quarter-2015/.
2 All currency amounts are in U.S. dollars unless otherwise specified.
3 EDGAR Online, Inc., Form 10-K (Annual Report), The Priceline Group Inc., 38, accessed November 1, 2016,
http://files.shareholder.com/downloads/PCLN/2762914235x0xS1075531-16-84/1075531/filing ; The Priceline Group,
accessed November 1, 2016, www.pricelinegroup.com/.
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single, double, with or without breakfast, refundable, and non-refundable rates), and each room required
its own web page and selling features. To complicate matters further, each page had to be accessible on
multiple platforms (desktop and mobile, in particular) and translated into 30 languages, with pricing
converted in real time to dozens of different currencies. The technology required to manage this
complexity was a core feature of Agoda’s business.
Despite its success, Agoda continually faced threats from new entrants; regulatory changes; competitors
that consistently adopted the latest technologies to improve customer experience and operations; and
startups like Airbnb, Inc., which sought to disrupt entire business models. To thrive in this rapidly
changing and highly competitive landscape, it was crucial for Agoda to remain nimble. It not only had to
keep abreast of the latest technological advances that could affect the business, but also attract and retain
top talent from around the world.
I like the combination of high natural intelligence, competitiveness, personal humility, and a strong
ethical foundation. That’s a winning formula for your most important people. When you find
someone who is like this who can add value to your business, be willing to pay up, take less for
yourself, or make whatever sacrifice you need to make, because that is how you make a great
business.4
Rosenstein believed that the relationship between managers and employees was critical to building the
strongest company and getting the best out of employees. Agoda was designed to encourage the manager–
employee relationship to flourish, with minimal administrative interference. From the CEO’s perspective,
traditional HR functions often impeded good management. Consequently, it was not until 2012 that
Agoda had a real HR function. Before that, the small number of HR staff had responsibilities only for
recruiting and managing payroll, and not staff development.
Rosenstein knew he needed to build recruitment, compensation, performance management, learning and
development, and talent management—traditional HR functions—for his rapidly growing company of
1,200 full-time staff. However, he was concerned that an HR bureaucracy would impede or replace good
management by taking ownership away from managers and employees. He also worried that it would
impose rules and policies that inhibited managers’ ability to make decisions that were best for the
company’s business; this was even more of a concern because of the firm’s diversity.
Agoda’s employee population comprised over 70 different nationalities working in a number of very
different functions: call centre employees, IT developers, marketing professionals, business development
professionals, and staff in finance, legal, and other areas. Rosenstein believed that an overly intrusive HR
function would damage the relationship between managers and employees, and reduce the sense of
entrepreneurship and flexibility that were core to the company. Yet some form of centralizing and
structure was necessary to help the firm operate and grow.
To ensure that his philosophy on managing talent was sustained while Agoda continued to grow, Rosenstein
turned to Peter Allen. With a PhD in humanities and MBA from The Wharton School at the University of
Pennsylvania, Allen had been a McKinsey & Company consultant in New York, founded Google
University, and worked in talent management at Standard Chartered bank. Allen took the job because he
wanted to see if he could shape the HR function to make a positive difference to this growing company.
4 Kira M. Newman, “Launch to Acquisition: Interview with CEO of Agoda (Acquired by Priceline),” Tech.Co, February 29,
2012, accessed November 1, 2016, http://tech.co/agoda-2012-02.
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RE-ENVISIONING THE HR ROLE
Allen was sympathetic to Rosenstein’s concerns about the dangers of imposing unnecessary bureaucracy.
He believed that the relationship between managers and employees was the foundation of a high-
functioning organization. As a result, Allen decided to build an HR function that would not add to the
bureaucracy, but would instead play an advisory role in supporting and enhancing the role of
management—in a sense, an internal consultancy that would help managers become more empowered in
managing talent through data and insights.
Allen explained his rationale:
Some tech firms grow out of an engineering culture in which the fundamental belief is that
managers are bad, so the less management you do, the better. Such firms prefer to minimize or
automate the business of management as much as possible. By contrast, we start with a different
fundamental assumption. We believe that the most important relationship at work is the one
between [managers and their] employees, so we want to help managers do their jobs well by
empowering and supporting them.
One of Allen’s first moves was to rename his department; he replaced the old “Human Resources” name
with a new one, “People and Organization Development” (generally known as the “people department”).
As Allen explained,
My department’s fundamental goal is to help managers manage better, not to manage on their
behalf.
Our approach is based on a few core principles:
• Managers, not HR, should define, live, and develop the company’s leadership.
• Managers, not HR, should do the hard work of managing people—hiring, evaluating,
rewarding, and disciplining employees—and managers should be evaluated on their results.
• Employees, not HR, should “manage up” and take responsibility for solving problems
directly with their managers.
We’ve also tried to hire the smartest and most talented people we can find, regardless of whether
they have traditional HR backgrounds. Results so far have been promising.5
Allen’s focus in the people department was to empower frontline managers to make many of the decisions
traditionally carried out by HR. Naturally, for a data-driven company, a large part of the empowerment
would come from providing those managers with the data to make those frontline decisions. The question
was what data to collect, and how to collect, analyze, and present it in a way that empowered managers to
make better decisions.
Data of all kinds was core to Agoda’s business. With millions of customers around the world, Agoda
needed to keep innovating in its business not by hunches or by intuition, but by solid data wherever
possible. Like other information technology (IT) firms, Agoda relied extensively on data to garner
5 Peter L. Allen, “Toward a New HR Philosophy,” McKinsey Quarterly, April 2015, accessed November 1, 2016,
www.mckinsey.com/business-functions/organization/our-insights/toward-a-new-hr-philosophy.
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insights into its customers. The objective was to do a better job of targeting prospective customers and
retaining existing ones.6
Allen knew that unless the people department operated in the same way as the rest of the company, it
would not have the credibility it needed to help managers make the best possible decisions. However,
when he joined the company, he found that most personnel information was kept on hundreds of
spreadsheets on the computers of different members of the old HR team. Further, performance reviews
were done on paper and kept (though hardly ever consulted) in physical files in the team room. There was
no way to stay up to date, aggregate information, protect employee security, build accurate organizational
charts, or support good management without the kind of information other departments had at Agoda.
For Allen, improving the way the people department worked with managers and other stakeholders was a
priority. His vision was not just about ensuring data could be digitized, centralized, and available in real
time; it involved a fundamental change in the organizational role of the HR department—from one that
established, monitored, and enforced HR policy to one that empowered managers to manage better.
To initiate this transformation of Agoda’s people department, Allen made a number of changes. One such
change was to persuade the company to adopt best-in-class information systems like Greenhouse and
Workday, and be in a position to customize where needed. These changes would require technical
resources. More importantly, Allen needed to hire great people who would share his philosophy, work
within the culture, and be very comfortable with data. In particular, he knew he would need someone to
take the lead and demonstrate how this new system could empower managers.
This person was Jeffrey Lee, a former McKinsey & Company consultant whom Allen recruited to be the
director of Operations and Compensation. Lee had a wealth of international experience that was relevant
to Agoda’s international presence. He grew up in Singapore and joined the U.S. Department of State as an
analyst providing coverage of Asia. After completing his MBA at The Wharton School, Lee was recruited
by McKinsey & Company, where he consulted on operations strategy with multinational clients around
the world. Allen thought that Lee’s consulting experience would place him in a strong position to lead the
people department to develop data-driven insights that would empower managers in managing the talent.
Lee was excited about Allen’s vision of enabling managers with data but realized this was going to be a
challenging undertaking. “When I arrived, we were conducting performance evaluations with one-
megabyte macro-enabled Excel sheets that were emailed to managers around the world.” In addition to
the technical issues of integrating a new human capital management system, Lee had to persuade
managers and his team in the people department to rethink how data was collected, analyzed, interpreted,
and presented. These changes were necessary to be consistent with Allen’s vision of the people
department as an enabler of managers, rather than a policy-setting and compliance-monitoring unit. Allen
and Lee worked with their team to bring the firm’s people practices up to speed by focusing on three
areas: compensation and benefits; performance evaluation and promotion; and recruitment.
6 Gil Press, “A Very Short History of Big Data,” Forbes, May 9, 2013, accessed November 1, 2016,
www.forbes.com/sites/gilpress/2013/05/09/a-very-short-history-of-big-data/2/#6dead6a51af0.
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In many organizations, the HR function determined salary bands and compensation policies for different
roles and positions. At Agoda, managers were encouraged to make compensation decisions based on their
unit’s needs. Allen explained the principle underlying this unconventional approach:
We believe that managers should be able to hire the best people for their roles, without following
arbitrary salary limits. Agoda hires employees from all over the world. Without compensation
flexibility, it would be impossible to hire, say, senior IT talent from Silicon Valley into Thailand.
As a result, giving managers the freedom to compensate employees appropriately was a key to the
company’s success.
To empower managers in deciding on compensation, Lee implemented a system to collect real-time
market rates on compensation, presenting the information to managers in a user-friendly format.
Managers were also shown correlations between performance and bonuses in their departments so they
could make informed decisions about allocating bonus payments (see Exhibit 2).
According to Allen, managers were prompted to look at these correlations and see where there were any
discrepancies:
These correlations should generally be positive. If they are not, it is possible that the bonus
allocations are out of sync. Another possibility is that there could be other reasons for the way
bonuses were allocated: sometimes there are specific individual circumstances, or broader
changes in market conditions of which managers are aware, which then alerts us to consider
adjusting compensation across the organization as a whole. The people team provides data and
advice—but does not override or overrule managers, who, after all, are responsible for the
performance of their own teams.
As a check, Rosenstein reviewed compensation for all departments at least once a year. The outcome was
that while salaries were not consistent, even within a single department, managers were able to hire,
reward, and retain the talent they needed most.
Lee also applied analytics to track employee benefit use. As an online travel agency, Agoda provided
employees with a travel benefit: 12 times per year they were able to use discounted rates on personal
accommodation booked through the Agoda website. While there were guidelines about using these
discounts, there were no clear penalties for excessive use. The question was how the company could
prevent employees from abusing their benefits without over-policing.
The people department monitored employee behaviour. However, rather than establishing blanket policies
for dealing with employees found to have abused their benefits, the department brought each case to
managers to resolve. In one case, for example, an employee was found to have used employee discounts
for stays worth more than half his salary. The people team presented data around excess bookings and, in
some cases, the person’s compensation to make the point that it was highly probable the employee was
reselling the discount. The manager then acted to rectify the problem. While the outcome may have been
the same as it would have been if HR managed the process, Agoda’s approach required managers to take
ownership of the problem and resolve it themselves.
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Performance evaluation at Agoda was conducted through peer evaluations of employees’ work habits,
cognitive abilities, and interpersonal skills (see Exhibit 3). Ratings for each employee were collated and
shared with the employee, the manager, and the departmental head (see Exhibit 4). In order for this data
to empower managers, Lee encouraged his team in the people department to constantly look for ways to
identify and collect data that was relevant to managers. Allen explained:
We initially didn’t know where to begin, so we started with a 50-question survey. Then, we ran
correlations on the responses to see if there were any key questions that drove the results.
Identifying these questions allowed us to pare the survey down to a handful of questions to make
it easier for employees completing the surveys and for managers.
From his prior consulting experience, Lee was aware that employees in each department performed
different kinds of work and needed to be measured differently. For instance, call centre employees were
managed on actual behaviours, such as the number and duration of calls handled. In contrast, employee
performance in partner marketing could only be measured after a longer period of time. Therefore,
managers in each of these units required different criteria for evaluating employee performance. Rather
than simply applying a common set of criteria to evaluate all employees, Lee regularly engaged with
managers to refine performance measures so they were the most useful to managers.
With this information, managers could help employees with their developmental needs and deploy them
to areas that suited their strengths. By tracking employees’ improvements in developmental needs over
time, department heads could use this information as another indication of their managers’ consistency
and effectiveness in managing, rather than rely solely on profit and loss numbers. Lee stated, “Many of
our departments award bonuses annually. Some want to award them monthly, and we are developing the
flexibility to provide these managers the tools with which to assess their employees’ performance,
allowing them to use key performance indicators to award bonuses.”
Once again, the people department had to find the right positioning—it wanted to give managers the
information required to make and own good management decisions, but it did not want to take over the
responsibility of managing from them. The principle remained the same: ask managers what information
they needed, get good data, analyze it, provide that data to managers in ways that would help them
manage better, and then follow up with them for feedback on the changes.
Lee remarked,
A typical HR department operates like a government monopoly. There’s no competition for its
services. You have to take what it provides. Moreover, you have to comply with its rules. We
look at our people department in a different way. We want to be useful to managers. We won’t
spend time developing tools or processes they don’t want. Managers are thinking about how we
can help them immediately. If we want our people department to be relevant, if we want a seat at
the table, we’re going to have to earn managers’ trust and give them tools, services, and data that
they need. Otherwise, they’ll find other ways to collect and use data and cut us out of the loop.
Having made some headway in giving managers the data they needed to manage their staff, Allen and Lee
saw the next step as developing Agoda’s analytics capabilities in recruiting talent. To sustain Agoda’s fast
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pace of growth, there was a constant need for new talent—both local and foreign experts—in critical
areas like programming, product management, design, learning and development, and finance. Allen and
Lee were convinced that getting recruitment to work, and work well, was critical to the company’s growth
and continued success.
Despite a growing recruitment team and a multi-million dollar annual recruitment budget, the company
had limited insight into the effectiveness of its recruiting efforts. The people team hoped to gain insights
such as the following:
• Which universities, agencies, and other sources were producing the candidates most likely to be
hired/successful?
• Were managers interviewing candidates efficiently and effectively?
• Were there managers who could consistently identify top performers?
• How long did the recruiting process typically take? How could Agoda expedite this process?
• Should the recruiting function sit inside the department, reporting directly to the business heads?
• Did candidates’ experience affect the company’s reputation and its ability to attract top talent?
• Was the internal referrals program effective?
Agoda sent out a People Team Survey with the objective of learning about the likelihood of employees
referring potential employees (see Exhibit 5). To gain insight into Agoda’s recruitment efforts, Allen and
Lee envisioned an applicant tracking system that would enable the people department to track, collate,
analyze, and present data about applicants. In addition to ensuring that job applications were reviewed
and acted on in a timely manner, such a system could potentially give managers feedback on successful
recruitment practices and hiring decisions. However, Lee’s experience in implementing a people analytics
platform made him sensitive to some of the challenges and drawbacks that were important to consider.
First, Allen and Lee recognized that the effective use of analytics for managing talent boiled down to
employees’ deeply ingrained beliefs about the role of the HR function in the organization. “The
perception of the HR function as adding to the bureaucracy is so ingrained, even within the people
department,” remarked Lee. “We’re working hard to change the perception that HR departments serve a
‘command and control’ function. We need to constantly remind ourselves that our job is to deliver value
to managers by empowering them with data.”
However, this philosophy was not always easy to embrace. For example, some of Lee’s analysts in the
people department were concerned that the constant iteration and customization of surveys for different
business units created analytical challenges. Not only was it difficult to track performance over time, but
it was also difficult to benchmark performance across units. From Lee’s perspective, this trade-off was
very clear: empowering managers with data, even at the cost of consistent benchmarking, was the main
role of the people department.
Second, most managers believed themselves to be good at what they did. While providing managers with
evidence about their successes reaffirmed these beliefs and would be received positively, their reactions
to evidence about their shortcomings were more unpredictable. Managers could become defensive and
more resistant to change, or misinterpret the data, resulting in unexpected behaviours.
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For example, providing data showing that a longer orientation program resulted in happier, more
productive employees could prompt managers to simply lengthen their orientation programs without
paying attention to the quality of those programs, or the trade-offs they might require. Similarly,
collecting employee feedback on a proposed new change (championed by the manager) could result in
managers electing not to share information about new initiatives in the future. Another risk was that
managers would “teach to the test” by behaving in ways that might make employees happy in the short
term but might not improve their performance.
The opportunity to gain a competitive advantage through data had to be tempered with the fact that many
companies still had not become competent at leveraging the data they were collecting. Agoda had
advanced systems, including people technology infrastructure, to manage its workforce (see Exhibit 6).
However, a recent commentary by Brendan Marr, an author focused on data, analytics, metrics, and
improving business performance, caught Allen’s eye:
[I]n the rush to avoid being left behind, I also see that many companies risk becoming data rich
but insight poor. They accumulate vast stores of data they have no idea what to do with, and no
hope of learning anything useful from.
To add to the problem, a lot of data has a lifespan. At some point in time, it becomes no longer
relevant, inaccurate or outdated. But often it is held onto anyway in the mistaken belief that
someday it might come in useful.
It is important to remember also that collecting and storing data costs money—data requires
storage, electricity to power it, and, if the information is sensitive (including customer records),
attention to be spent on security and data compliance.7
Third, there were concerns about data collection methods. If employees were being asked for their
opinions through online surveys, how could the people department ensure that appropriate questions were
being asked? How would it know if the surveys were sent out in the right frequency? Too little data
would not be informative, but survey fatigue was a risk, too.
Allen and Lee also expressed concern about how something as subjective as employee performance could
be measured accurately. “It’s much more complex and difficult to pin down employee performance than
dealing with financial transactions. Money you can count; performance—high or low—is a little more
difficult to determine,” said Allen. “How do we decide what makes a good manager and create a program
that develops these attributes?”
Fourth, Lee wondered how the information should be presented: “Should we send out our conclusions
and back them up by providing managers with the raw data? Or should a summary page be sufficient?
And, frankly, what would make managers actually pay attention and act on the information they
received?” If the goal was to have managers make decisions based on data, the question was how to
encourage managers to pay attention and use the data as a basis for change, rather than just treat it as a
report to be perused, or worse, ignored.
Lee toyed with the idea that the people department should implement a “league review” format,
comparing the hiring and management performance of managers with each other. “My dream state is that
7 Barnard Marr, “Big Data Overload: Why Most Companies Can’t Deal with the Data Explosion,” Forbes, April 28, 2016,
accessed November 23, 2015, www.forbes.com/sites/bernardmarr/2016/04/28/big-data-overload-most-companies-cant-
deal-with-the-data-explosion/#383d1b7c3920.
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each hiring manager has his or her own ‘baseball card.’ There would be statistics on it, a manager’s
scorecard if you will, and managers’ results would be available for all to see.” But what kind of
consequences would such a scorecard have? Rating systems had worked before in getting managers to
complete performance evaluations; what else could they be extended to?
Fifth, Lee wondered about privacy concerns. Was the overall effort to monitor and track employees too
intrusive? How would these efforts at data collection affect Agoda’s organizational culture, productivity,
and innovation?
Sixth, Allen and Lee had to overcome practical and technical challenges. The people department managed
a significant amount of employee testing, evaluation, performance, and feedback data. There were weekly
pulse surveys, a 60-question online employee engagement survey administered annually, and exit
interviews. There was semi-annual performance review data, other survey information, and data from a
new learning management system on the way. These groups of data were housed in six different datasets.
“We want to have an integrated platform that allows us to collect and analyze employee data. We are
aiming to invest in a unified system in the next few months,” said Lee. However, consolidating data
would require a significant investment of resources. Was it worth the cost and effort when the team was
already overstretched? What additional insights could be gained? How else might managers be
empowered, and how might this impact be quantified? How could the people department encourage—not
force—managers to behave in ways that would have better outcomes?
CEO Robert Rosenstein’s questions returned to the fore: How could Agoda correlate data and system
investment with outcomes, and what would it take to make this system work? How would the people
team persuade managers to use it—and what would be the implications for Agoda culture if they did?
This process of shaping the culture and changing behaviour—without creating resentment or taking away
managers’ independence—was a crucial one, and both Rosenstein and Allen knew it.
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EXHIBIT 1: AGODA GROWTH SINCE 2007
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This document is authorized for use only by Shiyao Zhao in ISTM654 Spring 2022 Lazarikos, Koeppel, Machrowicz taught by Tad Machrowicz, Pepperdine University from Dec 2021 to Jun
2022.
Page 12 9B17C024
EXHIBIT 2: CORRELATION BETWEEN BONUS AND PERFORMANCE AT AGODA
Source: Company files.
For the exclusive use of S. Zhao, 2022.
This document is authorized for use only by Shiyao Zhao in ISTM654 Spring 2022 Lazarikos, Koeppel, Machrowicz taught by Tad Machrowicz, Pepperdine University from Dec 2021 to Jun
2022.
Page 13 9B17C024
EXHIBIT 3: AGODA DEPARTMENTAL EVALUATION
Source: Company files.
For the exclusive use of S. Zhao, 2022.
This document is authorized for use only by Shiyao Zhao in ISTM654 Spring 2022 Lazarikos, Koeppel, Machrowicz taught by Tad Machrowicz, Pepperdine University from Dec 2021 to Jun
2022.
Page 14 9B17C024
EXHIBIT 4: SAMPLE REPORT FROM AGODA EMPLOYEE ENGAGEMENT SURVEY 2015
Notes:
Employee engagement is about more than just satisfaction. It is a mutually beneficial relationship
between the employee and organization. Engagement is a good indicator of how connected employees
are to the company and to helping it to achieve its goals.
Top 3 highest-scoring questions against Agoda overall:
• Q49. Senior managers are available and accessible when employees need them
• Q48. Senior management provides effective leadership
• Q54. Agoda has clear processes and systems to help me contribute ideas for improvement
Top 3 highest-scoring questions:
• Q59. I understand what would be considered discrimination or harassment in the work place
• Q60. I understand when I should go to my manager with problems versus when I should go to the
Legal and Compliance team with problems
• Q1. I have a clear understanding of the goals and objectives of my team
Source: Company files.
For the exclusive use of S. Zhao, 2022.
This document is authorized for use only by Shiyao Zhao in ISTM654 Spring 2022 Lazarikos, Koeppel, Machrowicz taught by Tad Machrowicz, Pepperdine University from Dec 2021 to Jun
2022.
Page 15 9B17C024
EXHIBIT 5: AGODA PEOPLE TEAM SURVEY (RECRUITING)
Source: Company files.
EXHIBIT 6: AGODA PEOPLE TECHNOLOGY INFRASTRUCTURE
Source: Company files.
For the exclusive use of S. Zhao, 2022.
This document is authorized for use only by Shiyao Zhao in ISTM654 Spring 2022 Lazarikos, Koeppel, Machrowicz taught by Tad Machrowicz, Pepperdine University from Dec 2021 to Jun
2022.
THE GLOBAL ONLINE TRAVEL AGENCY INDUSTRY
AGODA BACKGROUND
Explaining the importance of talent, Rosenstein stated,
IMPLEMENTING PEOPLE ANALYTICS
Compensation and Benefits
Performance Evaluation and Promotion
Recruitment
CHALLENGES IN IMPLEMENTING ANALYTICS
CONCLUSION
Source: Company files.
Source: Company files.
Source: Company files.
Source: Company files.
Source: Company files.
Page1 of 7
A recommendation memo is a routinely used document in leading firms, and you may be writing such
memos to executive leadership to “sell” or elevate an initiative. Therefore, it is essential that you gain
some practice at writing them. The purpose of a recommendation memo is to concisely recommend a
course of action and provide rationale supporting the recommendation. This note describes how your
team should approach writing a recommendation memo for the case assignments. The second part of
this note gives you a sample memo that you should use to write your own memos for these assignments.
Note that the format of the memos may vary from company to company. Therefore, while following the
memo format as given in this note, bear in mind that the goal here is to expose you to memo writing
rather than force a memo format on you.
WHAT IS A RECOMMENDATION MEMO?
The recommendation memo is a one-two page document (not including exhibits) that
recommends your course of action and rationale. This format promotes a concise and clear
strategic thought process. Equally importantly, it mimics managerial practice. If your memo
exceeds 2 pages, it is TOO long!
ELEMENTS OF A RECOMMENDATION MEMO
1. FIRST PARAGRAPH
This paragraph expresses your intent or action (This recommends……).
● Topic overview (the “what”, not “when” or “how”): costs, funding, etc.
● Ends with the hook: selling idea, the “why” or payoff: this part reveals the author’s point of view.
Checklist
● Is there a clear purpose, objective?
This paragraph explains why we are talking about this today. It lays out the story.
● Historical: not “new” news (i.e., none of your case analysis will appear here).
● Highlights what brought us to this moment, why we are in this position, what brought about the
need to make this decision.
● Dimensionalize the importance to the organization (e.g., important profit goal).
● Constraints – such as budget, capacity, technology, people, etc.
● This section is both brief and factual.
Checklist
● Is the background clear, concise, and easy to follow?
● Does it explain why action is needed now?
● Does the appropriate sense of urgency come across?
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Here, you detail what to do, when to do it and how to do it.
● The details of “what”, “when”, and “how”. NO “why”.
● This section should be very specific (100% clear). It must be actionable (How much will it cost, when,
how, who). The reader should be able to read this and know how to carry out this recommendation.
● Some cases will require more than one recommendation.
Checklist
● Is the recommendation clear and actionable? Could someone else implement it?
Here the reader learns WHY each recommendation is the UNIQUE right thing to do.
● 2-3 solid reasons are typical. Any other action should seem less appealing.
● This section flows from the opening “hook”; links to the original recommendation.
● Support includes impact on profit, share, AND anything else affecting long-term business goals.
● Analysis should address applicable quantitative issues such as NPV, break even analysis, pro
forma statement of project budget, sensitivity analysis; as well as qualitative issues, such as,
technology consistency, architectural conformance, innovation potential, etc.
● Appeals to precedent and anecdotal evidence in absence of data, but only in limited, carefully
constrained manner.
● Shows how the recommendation will put the firm at a competitive advantage or is simply a
competitive necessity.
● The goal is to read the basis and conclude the recommendation.
Checklist
● Is the recommendation an inescapable conclusion of the basis?
● Does the basis for recommendation appropriately consider:
1. Core competencies and consistency with mission?
2. External customers and internal clients?
3. Competitors?
4. Attractiveness – quantitative measures if applicable (e.g., NPV, ROI, break-even,
payback)?
● Are all assumptions explicitly stated (e.g., needs, technology trends)?
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● Outline other alternatives not selected.
● Discuss risks and key assumptions (use full disclosure, reference Options Grid) of your
recommendation.
● When you give a precise number or range, you must support the basis as well.
Checklist
● Is the analysis thorough with key alternatives fairly considered (see the attachment Options
Grid)?
● Risks associated with recommendation are properly addressed?
● Orient to the reader
● Specify date and action needed (what will be done, by whom, and by when)
Checklist
● Clear follow-up/next steps?
● If appropriate, lay out timeline with key milestones to implement recommendation.
● An Exhibit can be a graph, grid, or simple table (more than four lines).
● List assumptions used in calculations. Do not assume that the reader can read between the
lines. So, make every assumption explicit.
● Exhibits should have Title, sources, footnotes to calculation. The point of the Exhibit should
be instantly clear to the reader.
● Exhibits should be cited in the proper order (i.e., do not cite Exhibit 4 first in your Memo
and then Exhibit 2).
Checklist
● Is the analysis precise, accurate, and data-based?
● Are the exhibits clearly laid out, titled, and referenced in the memo?
● Is every assumption explicitly listed?
NOTE: Every memo may not include every element described above. The specific case will
dictate what must be included. An example is attached.
Page 4 of 7
SAMPLE MEMO FORMAT
To: (Name of supervisor goes here)
From: Your team designation/title/cohort and number
Date:
SUBJECT: NAME OF CASE AND RECO TOPIC
This recommends
Implementation will take place within days of approval. Improved sales, reliability, profitability,
productivity, and/or reduced costs will result from these actions (state specifics). Sales (Name),
Finance (Name), and Manufacturing (Name) concur (If applicable).
Background
● These key facts help explain why we are thinking about this situation today.
● At times, the background paragraph is a good place in a recommendation memo to document the gap
between the “real” and the “ideal”. When you use it this way, be sure it sets up each of the reasons in
the “Basis for Recommendation” section of the memo.
● Do not include obvious or unnecessary facts. Do not include information found while looking into the
situation. This is for information that caused us to look into the situation.
● It is best to simply tell a simple and concise story.
Recommendation
● This describes what we are going to do and how we intend to do it. Limit this section to major points.
Implementation details and caveats are discussed in the “Discussion” section following the “Basis for
Recommendation” section.
● Our objective is to
Basis for Recommendation
● We state our most important reason here. It is numbered, underlined, and stated in a full sentence. We
present data here to prove the claim made in point 1, making sure that the first sentence of this section
clearly extends from the data. The claim must be the inescapable conclusion of the data. If there are
more than four rows of data, use an exhibit (i.e. refer to Exhibit 1). Exhibits must be clearly labeled and
numbered.
● We state our second most important reason here. We present data to prove the claim made in point 2.
(3 points are typical)
Discussion:
● Here we discuss a) implementation details, and b) qualifiers, such as risks and rejected alternative
solutions.
Next Steps: Here we tell the readers exactly what we want them to do and when we want them to
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do it. We also lay out a timetable of key milestones to implement the recommendation. A throw-away
schedule should be prepared if high stakes are involved.
Page 6 of 7
ONE EXAMPLE OF ONE POSSIBLE EXHIBIT (there are many ways to
provide supportive data from the case or for an initiative)
THE OPTIONS GRID
It is important to recognize that every marketing problem has more than one solution. Our task
in marketing (in fact, in management in general) is to make educated decisions that we can communicate
to others. In doing this, it is helpful to have some tools to evaluate each option facing us. For the
marketing core, we will rely on what we call an Options Grid. You are required to complete options
grids for each of the assignments. This is so we believe that the more you use them, the more clarity you
will gain in examining alternative courses of action in any given marketing/management situation. In
addition, options grids will help you to organize your thoughts for writing up memos for the marketing
core assignments and could potentially help you in other courses as well. However, note that the options
grid and the memo are not meant to be substitutes for formats that other professors expect you to follow
for their courses.
The key areas that are included in an Options Grid are as follows:
– Description of Option:This is a brief description of what each option
entails. It is good practice to describe no more than 4 options. 3 is
optimal.
– Overall Assessment: Whether you recommend the option or not, AND WHY.
– Strategic Fit: How does this option fit with the company’s
core competencies and vision?
– Attractiveness: What is the technical attractiveness of this
option? What is the NPV or break even for the project or option (if
applicable)?
– Noteworthy Risks: For every option, we make assumptions that
we hope prove true. If they don’t, outcomes could change. Here is the
area to point out what those risks and limitations could be.
In general, we want to ‘sell’ our point of view and the Options Grid is a good place to do
that. However, in doing so, we may sometimes lose sight of objectivity. Be aware of this fallacy and be
brutally critical of your recommendation in writing up this options grid. Do not become a victim of what
psychologists call the ‘self-serving bias’.
Attached you will find an example of an Options Grid but from a marketing rather than an IS
example. When you use Options Grids for our class of course you will be focusing on IS decisions,
please use the attached general format. An options grid, when used, must be an attachment (and not in
the main memo itself) and it must not exceed ONE-PAGE.
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Example of an Options Grid
Marketing Management
Name:
Case:
OPTIONS GRID – Wal-Mart- P&G Case
Option 1 Option 2 Option 3
Description of
Option
Maintain Pampers as a
premium brand and fully
support Luvs
Discontinue support
behind Pampers and Luvs
Maintain Pampers as a
premium brand and move Luvs
into private label position
Overall
Assessment
Do not recommend because
of high B/E volume and
potential cannibalization.
Do not recommend
because of move away
from core competency
and competitive
marketplace
Recommend because of high
B/E volume, expected market
share growth from current
product and anticipated market
segmentation (provides product
to all consumers and dealers)
Strategic Fit
(Core
Competencies)
Provides innovative product
offerings and capitalizes on
marketing strengths.
Moves away from strong
brand identity. Known
for marketing strengths.
Provides superior benefit for
premium brand and relationship
with discount channels through
private label. Provides strong
financial outcome
Financial
Attractiveness
Unit B/E Volume = 11.3
million
Dollar B/E Volume =
$174.7 million
Unit B/E Volume = 11.5
million
Dollar B/E Volume =
$165.7 million
Unit B/E Volume = 10.8 million
Dollar B/E Volume =
$156.6 million
Noteworthy
Risks
• Does not identify
cannibalization.
• Ability to increase selling
prices based on superior
technology.
• Does not anticipate
competitive reaction.
• B/E is short run oriented
(1 year).
• Substantial change in
market growth of category.
• Flat to declining market
share expected.
• Does not identify
cannibalization.
• B/E is short run oriented
(1 year).
• Substantial change in
market growth of
category.
• Perceived by customer
as a move away from
premium differentiation.
• Substantial market share
increases expected.
• Does not account for
cannibalization.
• B/E is short run oriented (1
year).
• Does not anticipate
competitive reaction.
2. BACKGROUND
Checklist
3. RECOMMENDATION
Checklist
4. BASIS FOR RECOMMENDATION
Checklist
5. DISCUSSION
Checklist
6. NEXT STEPS
Checklist
7. EXHIBITS
Checklist
NOTE: Every memo may not include every element described above. The specific case will dictate what must be included. An example is attached.
Example of an Options Grid
