This is a case study describing how we moved an intranet that was not working for its employees into a successful website.
The objectives were to "lead with the need,' to determine how current employees want their information organized and what should be emphasized first. Our goals were to redesign the intranet site, focusing on the navigation and organization (overall information architecture); make the site usable; especially when it comes to finding things; and to make the site attractive and understandable to employees.
A card sort seemed the best solution because we had 2 sites that needed to be unified and that had grown too small for the additional information that kept getting added year in and year out. We had an IA that wasn’t working, and we wanted to discover how employees – the principal users of the site – wanted their information organized.
We chose a open card sort because we wanted participants to tell us how they wanted the main categories of the site named (as opposed to us naming the categories for them).
Physical and Online Card Sorts: A Practical Overview and Case StudyBob Thomas
This is a practical case study where I worked with an educational testing and assessment company to help them redesign their information architecture for their corporate intranet, using an open card sort.
So many companies build corporate intranets and then don’t do anything with them, so they just languish and are ignored by employees.
The company clearly saw the benefit of a corporate intranet and wanted to improve the site for its employees. It saw this as a competitive advantage.
Set the Hiring Managers’ Expectations: Using Big Data to answer Big Questions...Textkernel
Presentation by Abdel Tefridj at Textkernel's Conference Intelligent Machines and the Future of Recruitment on 2 June 2016 in Amsterdam.
Abdel shares some client scenarios when data was the key element in the decision making process for recruitment challenges. You can become a better partner with hiring managers when they are informed about the latest trends in the marketplace using supply, demand and compensation data. Learn how to use big data to make you a stronger leader and contributor.
How semantic search changes recruitment - Glen CatheyTextkernel
Presentation by Glen Cathey, SVP Talent Strategy and Innovation at Kforce, at Textkernel's conference Intelligent Machines and the Future of Recruitment on 2 June at the Beurs van Berlage in Amsterdam. At the end of this slide deck, you can also find the YouTube recording.
Without semantic search, recruiters searching for potential candidates only see a fraction of available and relevant results and unknowingly exclude qualified candidates unless they understand and employ advanced methods of manual information retrieval. In this keynote, Glen Cathey will explain how semantic search has specifically impacted recruitment today and how further advancements will impact recruitment in the future.
How can you design your organisation to make sense of data for better strategic decision making? In today’s Industry 4.0, many organisations aim to leverage upon vast amounts of data they are exposed to. This session harnesses the power of design thinking to give audiences the opportunity to realise the potential this methodology has regardless of the scale of data.
What does it_takes_to_be_a_good_data_scientist_2019_aim_simplilearnPraj H
Over the years, the term ‘data scientist’ has evolved greatly. From describing a person who handles data, to a professional who leverages machine learning — this definition has seen a great deal of change. Now, circa 2019, there are numerous blogs, Reddit pages and Quora threads dedicated to the discussion about “how to become a good data scientist”.
Intuition's Fall from Grace - Algorithms and Data in (Pre)-Selection by Colin...Textkernel
On 2 June during Textkernel's conference Intelligent Machines and the Future of Recruitment, Colin Lee presented his work on the automated preselection of applicants. For this research he used data from Connexys from 441,768 applicants at 48 companies, in combination with Textkernel parsing and normalization, to develop an algorithm that predicts which applicants get invited to a job interview. Colin explains the logic behind his approach and discusses potential future applications.
Data visualization has become increasingly more important and sits at the center of how people learn about and experience the world. We process information about politics, business insights and every day decisions through “visual soundbites”. As data journalists, we have incredible power to both positively influence as well as misguide conversations with the choices that we make when presenting graphical results.
In this presentation, we will share some of the best practices that help deliver stories that matter and avoid creating those that mislead.
Physical and Online Card Sorts: A Practical Overview and Case StudyBob Thomas
This is a practical case study where I worked with an educational testing and assessment company to help them redesign their information architecture for their corporate intranet, using an open card sort.
So many companies build corporate intranets and then don’t do anything with them, so they just languish and are ignored by employees.
The company clearly saw the benefit of a corporate intranet and wanted to improve the site for its employees. It saw this as a competitive advantage.
Set the Hiring Managers’ Expectations: Using Big Data to answer Big Questions...Textkernel
Presentation by Abdel Tefridj at Textkernel's Conference Intelligent Machines and the Future of Recruitment on 2 June 2016 in Amsterdam.
Abdel shares some client scenarios when data was the key element in the decision making process for recruitment challenges. You can become a better partner with hiring managers when they are informed about the latest trends in the marketplace using supply, demand and compensation data. Learn how to use big data to make you a stronger leader and contributor.
How semantic search changes recruitment - Glen CatheyTextkernel
Presentation by Glen Cathey, SVP Talent Strategy and Innovation at Kforce, at Textkernel's conference Intelligent Machines and the Future of Recruitment on 2 June at the Beurs van Berlage in Amsterdam. At the end of this slide deck, you can also find the YouTube recording.
Without semantic search, recruiters searching for potential candidates only see a fraction of available and relevant results and unknowingly exclude qualified candidates unless they understand and employ advanced methods of manual information retrieval. In this keynote, Glen Cathey will explain how semantic search has specifically impacted recruitment today and how further advancements will impact recruitment in the future.
How can you design your organisation to make sense of data for better strategic decision making? In today’s Industry 4.0, many organisations aim to leverage upon vast amounts of data they are exposed to. This session harnesses the power of design thinking to give audiences the opportunity to realise the potential this methodology has regardless of the scale of data.
What does it_takes_to_be_a_good_data_scientist_2019_aim_simplilearnPraj H
Over the years, the term ‘data scientist’ has evolved greatly. From describing a person who handles data, to a professional who leverages machine learning — this definition has seen a great deal of change. Now, circa 2019, there are numerous blogs, Reddit pages and Quora threads dedicated to the discussion about “how to become a good data scientist”.
Intuition's Fall from Grace - Algorithms and Data in (Pre)-Selection by Colin...Textkernel
On 2 June during Textkernel's conference Intelligent Machines and the Future of Recruitment, Colin Lee presented his work on the automated preselection of applicants. For this research he used data from Connexys from 441,768 applicants at 48 companies, in combination with Textkernel parsing and normalization, to develop an algorithm that predicts which applicants get invited to a job interview. Colin explains the logic behind his approach and discusses potential future applications.
Data visualization has become increasingly more important and sits at the center of how people learn about and experience the world. We process information about politics, business insights and every day decisions through “visual soundbites”. As data journalists, we have incredible power to both positively influence as well as misguide conversations with the choices that we make when presenting graphical results.
In this presentation, we will share some of the best practices that help deliver stories that matter and avoid creating those that mislead.
You Can Hack That: How to Use Hackathons to Solve Your Toughest ChallengesBooz Allen Hamilton
“Hackathon” has become a trendy word in today’s business vernacular, and for good reason. The word “hackathon” comes from both “hack” and “marathon.” If you think of a “hack” as a creative solution and “marathon” as a continuous, often competitive event, you’re at the heart of what a hackathon is about. Hackathons enable creative problem solving through an innovative and often competitive structure that engages stakeholders to come up with unconventional solutions to pressing challenges. Hackathons can be used to develop new processes, products, ways of thinking, or ways of engaging stakeholders and partners, with benefits ranging from solving tough problems to broader cultural and organizational improvements.
This playbook was designed to make hackathons accessible to everyone. That means not only can all kinds of organizations benefit from hackathons, but that all kinds of employees inside those groups—executives, project managers, designers, or engineers—should participate and can benefit, too. Use this playbook as a reference and allow the best practices we outline to guide you in designing a hackathon structure that works for you and enables your organization to achieve its desired outcomes. Give yourself anywhere from six weeks to a few months to plan your hackathon, depending on the components, approach, number of participants, and desired outcomes.
Contact Director Brian MacCarthy at MacCarthy_Brian2@bah.com for more information about Booz Allen’s hackathon offering.
“Where the Rubber Meets the Road: Applying HR Technology to Solve Real-world Problems,” from LBi Software, brings the insight and wisdom of seven of HR's most recognized thought leaders to one topic: how to use today's powerful HR technology to focus on the people in your organization and become a more strategic business partner.
Our engaging e-book draws on the experience and knowledge of some of the most recognized thought leaders in HR today, including Steve Boese (HR Technology Conference & Expo), Ron Thomas (Human Capital Institute), Lisa Rosendahl (WomenofHR.com), Robin Schooling (HR Schoolhouse.com) and Matt Stollak (True Faith HR).
This e-book gives you succinct and revealing insight into how HR can better understand and rise to daily challenges, such as:
-Assuming too much about what employees think and feel.
-Meeting the increasing demand for workforce transparency and accuracy.
-Understanding the essential characteristics of employees, beyond job skills and goals
-Building your rewards program on your organization's culture
-Adapting to cultural developments and trends
-Using social media to assess the employee experience
-Embracing data to prove HR effectiveness
-Getting real-world use out of the newest HR technology
UX STRAT Online 2020: Victoria Sosik, VerizonUX STRAT
Demand for UX insights is higher than ever--as UX Researchers, we’ve become “victims of our own success.” While a cause for celebration, with it comes challenges managing bandwidth, prioritizing work, and being viewed as a bottleneck in the design process. For this reason, we began exploring a program to democratize Design Research at Verizon. In this talk, I’ll walk through our approach, our decisions around which types of research to democratize, and how we’re striking the balance between democratization and control. I’ll also reflect back on our early experiences with the program and where we plan to go in the future.
Real-life Data Visualization - guest lecture for McGill INSY-442Mike Deutsch
Guest lecture given to McGill University undergrad class on Business Intelligence & Analytics, April 2014. Narrative: Data Visualization defined; What *good* visualization is; Visualization in business; a final Exercise in visualizing Higher Education Research data.
Get a quick introduction to data science with python. What is Data Science? Where is data science used? How is data Science used? Where is the future of Data Science.
Big Data is big buzz at the present.
There's so much press, but so little clarity about what "big data" actually is (and what it can do for HR).
This presentation is an introduction to big data and data analytics. With no techno-babble, find out:
> What is big data?
> What do I really need to know?
> What can it do?
> How does it apply to Human Resources / HR?
> What are some examples of big data being used in the HR "space"?
> How will big data change HR in general?
Highly relevant for anyone involved in people management, human resources, organisational design and change management.
科技在许多层面改变了我们的生活,这里先从实际的故事来观察学习与培训方式的变化,指出当今人力发展地图上的重要方向,例如社会学习、非正式学习、效能支持、移动学习,接著探讨高管应如何管理与掌握多元样貌的学习行为,去对齐趋近组织目标。利用数据作决策在商业竞争中胜出,人力发展也应该如此。Experience API (xAPI) 就是为这目的而产生的新学习标準。目前 xAPI 实施案最多落在两大类需求: 整合跨系统的历程数据、加强销售绩效。
Technologies have changed many aspects of our society, the landscape of learning and development has been changed a lot. What are important directions on the map? What are social learning, informal learning, performance support & mobile learning and their impacts? With such paradigm shifts, you can’t manage what you don’t measure. Many business competitions are won by data-driven solutions and decisions, so shall talent development management. That led to the introduction of Experience API (xAPI).
Copy of a presentation delivered at the 3rd HR Analytics, Metrics and Measurement Conference, sharing some of the key lessons, tips and mistakes I have learned during two decades managing Human Resources, Workforce Planning and HR Analytics programs.
[Studienergebnisse 2015] Big Data - Status Quo in der HR in Deutschland. LinkedIn D-A-CH
Das ist Ihre Chance sich jetzt als Big Data Profi im Unternehmen zu positionieren und die Erkenntnisse wirksam umzusetzen. LinkedIn bietet Ihnen bereits ein Fülle von relevanten Daten, die Sie heute einsetzen können.
You Can Hack That: How to Use Hackathons to Solve Your Toughest ChallengesBooz Allen Hamilton
“Hackathon” has become a trendy word in today’s business vernacular, and for good reason. The word “hackathon” comes from both “hack” and “marathon.” If you think of a “hack” as a creative solution and “marathon” as a continuous, often competitive event, you’re at the heart of what a hackathon is about. Hackathons enable creative problem solving through an innovative and often competitive structure that engages stakeholders to come up with unconventional solutions to pressing challenges. Hackathons can be used to develop new processes, products, ways of thinking, or ways of engaging stakeholders and partners, with benefits ranging from solving tough problems to broader cultural and organizational improvements.
This playbook was designed to make hackathons accessible to everyone. That means not only can all kinds of organizations benefit from hackathons, but that all kinds of employees inside those groups—executives, project managers, designers, or engineers—should participate and can benefit, too. Use this playbook as a reference and allow the best practices we outline to guide you in designing a hackathon structure that works for you and enables your organization to achieve its desired outcomes. Give yourself anywhere from six weeks to a few months to plan your hackathon, depending on the components, approach, number of participants, and desired outcomes.
Contact Director Brian MacCarthy at MacCarthy_Brian2@bah.com for more information about Booz Allen’s hackathon offering.
“Where the Rubber Meets the Road: Applying HR Technology to Solve Real-world Problems,” from LBi Software, brings the insight and wisdom of seven of HR's most recognized thought leaders to one topic: how to use today's powerful HR technology to focus on the people in your organization and become a more strategic business partner.
Our engaging e-book draws on the experience and knowledge of some of the most recognized thought leaders in HR today, including Steve Boese (HR Technology Conference & Expo), Ron Thomas (Human Capital Institute), Lisa Rosendahl (WomenofHR.com), Robin Schooling (HR Schoolhouse.com) and Matt Stollak (True Faith HR).
This e-book gives you succinct and revealing insight into how HR can better understand and rise to daily challenges, such as:
-Assuming too much about what employees think and feel.
-Meeting the increasing demand for workforce transparency and accuracy.
-Understanding the essential characteristics of employees, beyond job skills and goals
-Building your rewards program on your organization's culture
-Adapting to cultural developments and trends
-Using social media to assess the employee experience
-Embracing data to prove HR effectiveness
-Getting real-world use out of the newest HR technology
UX STRAT Online 2020: Victoria Sosik, VerizonUX STRAT
Demand for UX insights is higher than ever--as UX Researchers, we’ve become “victims of our own success.” While a cause for celebration, with it comes challenges managing bandwidth, prioritizing work, and being viewed as a bottleneck in the design process. For this reason, we began exploring a program to democratize Design Research at Verizon. In this talk, I’ll walk through our approach, our decisions around which types of research to democratize, and how we’re striking the balance between democratization and control. I’ll also reflect back on our early experiences with the program and where we plan to go in the future.
Real-life Data Visualization - guest lecture for McGill INSY-442Mike Deutsch
Guest lecture given to McGill University undergrad class on Business Intelligence & Analytics, April 2014. Narrative: Data Visualization defined; What *good* visualization is; Visualization in business; a final Exercise in visualizing Higher Education Research data.
Get a quick introduction to data science with python. What is Data Science? Where is data science used? How is data Science used? Where is the future of Data Science.
Big Data is big buzz at the present.
There's so much press, but so little clarity about what "big data" actually is (and what it can do for HR).
This presentation is an introduction to big data and data analytics. With no techno-babble, find out:
> What is big data?
> What do I really need to know?
> What can it do?
> How does it apply to Human Resources / HR?
> What are some examples of big data being used in the HR "space"?
> How will big data change HR in general?
Highly relevant for anyone involved in people management, human resources, organisational design and change management.
科技在许多层面改变了我们的生活,这里先从实际的故事来观察学习与培训方式的变化,指出当今人力发展地图上的重要方向,例如社会学习、非正式学习、效能支持、移动学习,接著探讨高管应如何管理与掌握多元样貌的学习行为,去对齐趋近组织目标。利用数据作决策在商业竞争中胜出,人力发展也应该如此。Experience API (xAPI) 就是为这目的而产生的新学习标準。目前 xAPI 实施案最多落在两大类需求: 整合跨系统的历程数据、加强销售绩效。
Technologies have changed many aspects of our society, the landscape of learning and development has been changed a lot. What are important directions on the map? What are social learning, informal learning, performance support & mobile learning and their impacts? With such paradigm shifts, you can’t manage what you don’t measure. Many business competitions are won by data-driven solutions and decisions, so shall talent development management. That led to the introduction of Experience API (xAPI).
Copy of a presentation delivered at the 3rd HR Analytics, Metrics and Measurement Conference, sharing some of the key lessons, tips and mistakes I have learned during two decades managing Human Resources, Workforce Planning and HR Analytics programs.
[Studienergebnisse 2015] Big Data - Status Quo in der HR in Deutschland. LinkedIn D-A-CH
Das ist Ihre Chance sich jetzt als Big Data Profi im Unternehmen zu positionieren und die Erkenntnisse wirksam umzusetzen. LinkedIn bietet Ihnen bereits ein Fülle von relevanten Daten, die Sie heute einsetzen können.
Delivering Results: How Do You Report User Research Findings? Bob Thomas
The long, textual written report is dead, isn’t it? So how do you deliver your findings to your clients? Is it PowerPoint? An e-mail? A spreadsheet? Post-it notes? And what do you include? Positive findings? Screenshots with callouts? Just issues? Or recommendations as well? Are they prioritized?
If you ask our panelists, some of us have developed templates that we use and modify for each research activity, and others change the deliverable based on the activity and client.
Jen McGinn, Principal Usability Engineer, Oracle
Eva Kaniasty, Founding Principal, RedPill UX
Dharmesh Mistry, Usability Specialist, Acquia
Kyle Soucy, Founding Principal, Usable Interface
Carolyn Snyder, Founding Principal, Snyder Consulting
Delivering Results: How Do You Report User Research Findings?Bob Thomas
The long, textual written report is dead, isn’t it? So how do you deliver your findings to your clients? Is it PowerPoint? An email? A spreadsheet? Post-it notes? And what do you include? Positive findings? Screenshots with callouts? Just issues? Or recommendations as well? Are they prioritized? If you ask our panelists, some of us have developed templates that we use and modify for each research activity, and others change the deliverable based on the activity and client.
Presentation from WebDU 2008 in Sydney, where I attempt to give developers and designers some insight into what IA is and how it works, so they can integrate it into their own practices or just work more effectively with IA/UX practitioners
The Emerging Role of Data Scientists on Software Developmen.docxarnoldmeredith47041
The Emerging Role of Data Scientists
on Software Development Teams
Miryung Kim
UCLA
Los Angeles, CA, USA
[email protected]
Thomas Zimmermann Robert DeLine Andrew Begel
Microsoft Research
Redmond, WA, USA
{tzimmer, rdeline, andrew.begel}@microsoft.com
ABSTRACT
Creating and running software produces large amounts of raw data
about the development process and the customer usage, which can
be turned into actionable insight with the help of skilled data scien-
tists. Unfortunately, data scientists with the analytical and software
engineering skills to analyze these large data sets have been hard to
come by; only recently have software companies started to develop
competencies in software-oriented data analytics. To understand
this emerging role, we interviewed data scientists across several
product groups at Microsoft. In this paper, we describe their educa-
tion and training background, their missions in software engineer-
ing contexts, and the type of problems on which they work. We
identify five distinct working styles of data scientists: (1) Insight
Providers, who work with engineers to collect the data needed to
inform decisions that managers make; (2) Modeling Specialists,
who use their machine learning expertise to build predictive mod-
els; (3) Platform Builders, who create data platforms, balancing
both engineering and data analysis concerns; (4) Polymaths, who
do all data science activities themselves; and (5) Team Leaders,
who run teams of data scientists and spread best practices. We fur-
ther describe a set of strategies that they employ to increase the im-
pact and actionability of their work.
Categories and Subject Descriptors:
D.2.9 [Management]
General Terms:
Management, Measurement, Human Factors.
1. INTRODUCTION
Software teams are increasingly using data analysis to inform their
engineering and business decisions [1] and to build data solutions
that utilize data in software products [2]. The people who do col-
lection and analysis are called data scientists, a term coined by DJ
Patil and Jeff Hammerbacher in 2008 to define their jobs at
LinkedIn and Facebook [3]. The mission of a data scientist is to
transform data into insight, providing guidance for leaders to take
action [4]. One example is the use of user telemetry data to redesign
Windows Explorer (a tool for file management) for Windows 8.
Data scientists on the Windows team discovered that the top ten
most frequent commands accounted for 81.2% of all of invoked
commands, but only two of these were easily accessible from the
command bar in the user interface 8 [5]. Based on this insight, the
team redesigned the user experience to make these hidden com-
mands more prominent.
Until recently, data scientists were found mostly on software teams
whose products were data-intensive, like internet search and adver-
tising. Today, we have reached an inflection point where many.
The Emerging Role of Data Scientists on Software Developmen.docxtodd701
The Emerging Role of Data Scientists
on Software Development Teams
Miryung Kim
UCLA
Los Angeles, CA, USA
[email protected]
Thomas Zimmermann Robert DeLine Andrew Begel
Microsoft Research
Redmond, WA, USA
{tzimmer, rdeline, andrew.begel}@microsoft.com
ABSTRACT
Creating and running software produces large amounts of raw data
about the development process and the customer usage, which can
be turned into actionable insight with the help of skilled data scien-
tists. Unfortunately, data scientists with the analytical and software
engineering skills to analyze these large data sets have been hard to
come by; only recently have software companies started to develop
competencies in software-oriented data analytics. To understand
this emerging role, we interviewed data scientists across several
product groups at Microsoft. In this paper, we describe their educa-
tion and training background, their missions in software engineer-
ing contexts, and the type of problems on which they work. We
identify five distinct working styles of data scientists: (1) Insight
Providers, who work with engineers to collect the data needed to
inform decisions that managers make; (2) Modeling Specialists,
who use their machine learning expertise to build predictive mod-
els; (3) Platform Builders, who create data platforms, balancing
both engineering and data analysis concerns; (4) Polymaths, who
do all data science activities themselves; and (5) Team Leaders,
who run teams of data scientists and spread best practices. We fur-
ther describe a set of strategies that they employ to increase the im-
pact and actionability of their work.
Categories and Subject Descriptors:
D.2.9 [Management]
General Terms:
Management, Measurement, Human Factors.
1. INTRODUCTION
Software teams are increasingly using data analysis to inform their
engineering and business decisions [1] and to build data solutions
that utilize data in software products [2]. The people who do col-
lection and analysis are called data scientists, a term coined by DJ
Patil and Jeff Hammerbacher in 2008 to define their jobs at
LinkedIn and Facebook [3]. The mission of a data scientist is to
transform data into insight, providing guidance for leaders to take
action [4]. One example is the use of user telemetry data to redesign
Windows Explorer (a tool for file management) for Windows 8.
Data scientists on the Windows team discovered that the top ten
most frequent commands accounted for 81.2% of all of invoked
commands, but only two of these were easily accessible from the
command bar in the user interface 8 [5]. Based on this insight, the
team redesigned the user experience to make these hidden com-
mands more prominent.
Until recently, data scientists were found mostly on software teams
whose products were data-intensive, like internet search and adver-
tising. Today, we have reached an inflection point where many.
An effective intranet design is one that is perceived as being of value by both employees and stakeholders. There is a significant amount of planning involved when designing an intranet experience no matter if it is a new build, redesign or new feature. It typically requires cross-department collaboration, management of a multidisciplinary team and implementation, marketing/communication and training plan.
Employer Branding and Staff Attraction strategies in international ITO companiesKseniia Udovitskaia
Case study of two players in the international outsourcing domain - EPAM and Luxoft. Summary includes:
- Term paper structure
- Problem statement
- Missing pieces
- Theoretical part description
- Methodology
- Findings
Highlights and summary of long-running programmatic research on data science; practices, roles, tools, skills, organization models, workflow, outlook, etc. Profiles and persona definition for data scientist model. Landscape of org models for data science and drivers for capability planning. Secondary research materials.
This presentation was given at the KM Singapore conference in Singapore on 15 Aug 09. I introduced a governance cycle and presented 4 key areas of governance: information organisation, publishing, collaboration and apps.
UX STRAT 2018 | Flying Blind On a Rocket Cycle: Pioneering Experience Centere...Joe Lamantia
After Oracle acquired Endeca, we all had to figure out what to do next. This case study describes building a learning-driven strategy capability to guide an adventurous product development group focused on the new domains of big data analytics and machine intelligence. I’ll share the outcomes of our efforts to launch new products chartered directly around customer experience value; outline the methods, tools, and perspectives that powered product discovery and strategic planning; share a framework and patterns for identifying and understanding emerging domains; and review the application of this toolkit to new situations.
Defining the future role of client-side market research and insightsRay Poynter
The world is changing, we have more types of data, more suppliers of information, and business is moving at ever faster speeds. Client-side market research and insight teams need to adapt to these changes or they will become irrelevant. In this 30-minute session, Naoki Takahashi from Nissan will give a presentation on the issues and then Ray Poynter and Mr Takahashi will discuss the implications for client-side teams, before throwing the topic open to questions and suggestions from the audience.
Similar to From Card Sort to Redesigned Intranet Site: A Success Story (20)
Discover the innovative and creative projects that highlight my journey throu...dylandmeas
Discover the innovative and creative projects that highlight my journey through Full Sail University. Below, you’ll find a collection of my work showcasing my skills and expertise in digital marketing, event planning, and media production.
Recruiting in the Digital Age: A Social Media MasterclassLuanWise
In this masterclass, presented at the Global HR Summit on 5th June 2024, Luan Wise explored the essential features of social media platforms that support talent acquisition, including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok.
What is the TDS Return Filing Due Date for FY 2024-25.pdfseoforlegalpillers
It is crucial for the taxpayers to understand about the TDS Return Filing Due Date, so that they can fulfill your TDS obligations efficiently. Taxpayers can avoid penalties by sticking to the deadlines and by accurate filing of TDS. Timely filing of TDS will make sure about the availability of tax credits. You can also seek the professional guidance of experts like Legal Pillers for timely filing of the TDS Return.
Implicitly or explicitly all competing businesses employ a strategy to select a mix
of marketing resources. Formulating such competitive strategies fundamentally
involves recognizing relationships between elements of the marketing mix (e.g.,
price and product quality), as well as assessing competitive and market conditions
(i.e., industry structure in the language of economics).
At Techbox Square, in Singapore, we're not just creative web designers and developers, we're the driving force behind your brand identity. Contact us today.
Cracking the Workplace Discipline Code Main.pptxWorkforce Group
Cultivating and maintaining discipline within teams is a critical differentiator for successful organisations.
Forward-thinking leaders and business managers understand the impact that discipline has on organisational success. A disciplined workforce operates with clarity, focus, and a shared understanding of expectations, ultimately driving better results, optimising productivity, and facilitating seamless collaboration.
Although discipline is not a one-size-fits-all approach, it can help create a work environment that encourages personal growth and accountability rather than solely relying on punitive measures.
In this deck, you will learn the significance of workplace discipline for organisational success. You’ll also learn
• Four (4) workplace discipline methods you should consider
• The best and most practical approach to implementing workplace discipline.
• Three (3) key tips to maintain a disciplined workplace.
Digital Transformation and IT Strategy Toolkit and TemplatesAurelien Domont, MBA
This Digital Transformation and IT Strategy Toolkit was created by ex-McKinsey, Deloitte and BCG Management Consultants, after more than 5,000 hours of work. It is considered the world's best & most comprehensive Digital Transformation and IT Strategy Toolkit. It includes all the Frameworks, Best Practices & Templates required to successfully undertake the Digital Transformation of your organization and define a robust IT Strategy.
Editable Toolkit to help you reuse our content: 700 Powerpoint slides | 35 Excel sheets | 84 minutes of Video training
This PowerPoint presentation is only a small preview of our Toolkits. For more details, visit www.domontconsulting.com
RMD24 | Retail media: hoe zet je dit in als je geen AH of Unilever bent? Heid...BBPMedia1
Grote partijen zijn al een tijdje onderweg met retail media. Ondertussen worden in dit domein ook de kansen zichtbaar voor andere spelers in de markt. Maar met die kansen ontstaan ook vragen: Zelf retail media worden of erop adverteren? In welke fase van de funnel past het en hoe integreer je het in een mediaplan? Wat is nu precies het verschil met marketplaces en Programmatic ads? In dit half uur beslechten we de dilemma's en krijg je antwoorden op wanneer het voor jou tijd is om de volgende stap te zetten.
VAT Registration Outlined In UAE: Benefits and Requirementsuae taxgpt
Vat Registration is a legal obligation for businesses meeting the threshold requirement, helping companies avoid fines and ramifications. Contact now!
https://viralsocialtrends.com/vat-registration-outlined-in-uae/
Putting the SPARK into Virtual Training.pptxCynthia Clay
This 60-minute webinar, sponsored by Adobe, was delivered for the Training Mag Network. It explored the five elements of SPARK: Storytelling, Purpose, Action, Relationships, and Kudos. Knowing how to tell a well-structured story is key to building long-term memory. Stating a clear purpose that doesn't take away from the discovery learning process is critical. Ensuring that people move from theory to practical application is imperative. Creating strong social learning is the key to commitment and engagement. Validating and affirming participants' comments is the way to create a positive learning environment.
Personal Brand Statement:
As an Army veteran dedicated to lifelong learning, I bring a disciplined, strategic mindset to my pursuits. I am constantly expanding my knowledge to innovate and lead effectively. My journey is driven by a commitment to excellence, and to make a meaningful impact in the world.
From Card Sort to Redesigned Intranet Site: A Success Story
1. From Card Sort to Redesigned Intranet:
A Success Story
Elke Oberg, Electronic Marketing Coordinator, Measured Progress
Bob Thomas, Manager of User Experience, Liberty Mutual
Katelyn Thompson, Usability Analyst, Staples
June 9, 2010
2. Scope, Objectives, and Goals
Company Mission
“Our mission is to improve teaching and learning by providing
customized assessment products and educational services.”
Objective
Make it easier for Measured Progress employees to find
information on the intranet, i.e., to “lead with the need.”
Measured Progress, a not-for-
profit located in Dover, NH, is
a leading developer of
educational testing and
assessment programs
3. Home HR Policies & Procedures
The goal was to unite the separate Insite and HR Policies and Procedures sites, each
created with different software applications.
Participants commented they would like to use Search and Site Map features. These
were available only on the home page.
4. “You’d think the [Accident and Injury Report] form is under InForm.”
InService > HR > Policy Guide > General Administration > Operational Policies > Safety > Accident Reporting and
Investigation Plan > [Text… Scroll Down Page] … Accident Report Form (7 clicks)
“A person could bleed to death before the form is even located!”
InService InForm
5. Original Navigational Hierarchy
Insite:
broad and shallow
Job Request Form:
InForm > Job Request Forms > Form (2 clicks)
Safety Form:
InService > HR > Policy Guide > General Administration >
Operational Policies > Safety > Accident Reporting and
Investigation Plan > [Text] … Accident Report Form (7 clicks)
HR Policies and Procedures:
narrow and deep
6. Original Navigational Hierarchy
I always disliked the confusing, supposedly clever navigation
scheme on the old site. It was a guessing game to find content. I
never remembered what was where and always had to start the
hunt all over.
—Mary, Measured Progress Employee
7. Card Sorts
“Card sorting is excellent for situations where you want the
users’ mental model to drive the information architecture of the
product.”
—Courage & Baxter (2005), “Understanding Your Users”
“Open sorts are used for discovery. Closed sorts are used for
validation.”
—Rosenfeld & Morville (2006), “Information Architecture for the
World Wide Web”
8. Card Sorts
Users
Recruited users who had used the intranet site for a long
time, as well as new hires
Methodology
Open card sort
Analysis
More information to sift through with open card sorts
Dendrograms to see common groupings
9. Methodology for the Card Sort
Created and ran an open
card sort with 15
Measured Progress
employees, including
follow-up interviews
Analyzed quantitative
and qualitative data
Made recommendations
for a new navigational
hierarchy and structure
10. Open Card Sort
# Card name
1 Corporate Graphics
2 Floor Plans
3 Facilities and Locations
4 Contacts
5 Employee Directory
6 Corporate Travel
7 Glossary and Acronyms
8 Mission and Philosophy
9 Safety
10 Reimbursement
11 Payroll
12 Purchasing and Requisitions
13 Workplace Policies
14 Hiring and Employment
15 Benefits
16 Work Schedules
17 Personnel Records
18 Shipping and Distribution
19 Printing and Copying
20 Helpdesk
21 Forms
22 Computer and Networks
23 Corporate Marketing and Branding
24 Information Technology
25 Phone and Conferencing
26 Contracts
27 Wellness Programs
28 Diversity
29 In/Out Board
30 News and Announcements
31 Photo Gallery
32 Corporate Events
33 Department Sites
34 For New Employees
35 Workplace Conduct
36 Recognition and Accomplishments
11. Participant Demographics
All 15 participants had experience using Insite.
Participants from 9 different departments
4 men and 11 women
P# Gender Department Used Insite?
0-5 6-10 IE Firefox Word processing Emailing Web Browsing
1 F Testing Services Y x x x x x
2 F Human Resources Y x x x x
3 M Client Services Y x x x x x
4 F Human Resources Y x x x x x
5 F Testing Services Y x x x x x
6 F Office of Technology Y x x x x x
7 F Finance Y x x x x x
8 M Testing Services Y x x x x x
9 F Client Services Y x x x x x
10 F Operational Services Y x x x x x
11 M Scoring Y x x x x x
12 F Process Coordination Y x x x x x
13 F Marketing Y x x x x x
14 F Client Services Y x x x x x
15 M Marketing Y x x x x x
Hours Per Week Web Browser for Insite? What Do You Do on a Computer?
12. Sample Open Card Sort Results:
Major Navigation Categories
WHAT I WANT TO USE
Home page
Contracts
Forms
WHAT I WANT TO REFER TO
Department sites
Employee directory
Working at Measured Progress
Helpdesk
13. Analysis of Results
We began to see trends after five card sorts on the first day.
Main categories among first five participants
14. Analysis of Results
We started with 106 original categories from all 15 participants,
and applied consistent naming conventions.
Standardized categories derived from original categories
15. Analysis of Results
Second, we combined similar standardized categories and
arrived at a total of 13 standardized categories.
Final list of 13 standardized categories
0.67
18. Analysis of Results
“Mental image the user forms to understand how software
works and how to operate it”
—Arnowitz et al (2007), “Effective Prototyping for Software
Makers”
In the case of Insite, many participants in our card sorts could
not express a mental model of the website beyond the use of
“In” headings. But many did express their mental model of the
ideal Measured Progress intranet:
“There’s stuff there that people need to do their jobs. They need
a reference library for working at the company . . . a big
bookshelf of benefits and other [information].”
19. Analysis of Results
Use a navigation hierarchy of medium depth and breadth
Use a primary navigation hierarchy of no more than 8 or 9
categories
Go 3 or 4 levels deep
Put search at the top of every page
Put site map link on every page
22. Where I Didn’t Listen to Bob
Three-column
design on
second-level
pages
Third-level
sub-navigation
Home on main
navigation bar
Search at top
right of page
23. Employees’ Reactions
. . . terrific and very user-friendly. And it’s easy on the eyes!
—Denise
. . . navigation makes so much more sense. If I need to look at an
HR policy or find the manager of a particular contract, it’s just a
couple of clicks away. You can view company newsletters from
2001, as well as articles about what the future might hold for our
industry—it’s all there. —Laura
. . . now they are grouped and organized in a logical way. Another
great improvement is the search feature. If I need to find anything,
I can type it in! —Heather
Being able to find what I need through multiple channel makes
Insite easy to use. —Paul
29. What We Kept
Quick access to the Employee Directory, the section
employees use the most
Corporate colors
Anything that humanizes the user experience:
Photo of the week
Kids’ art
Photo gallery
31. Conclusions
Card sort was a success because:
We involved key stakeholders from the start who clearly saw
the benefits of the corporate intranet and wanted to improve
the site for employees.
We recruited participants from all areas of the company.
We were able to understand employees’ mental models (“a
reference library,” “a bookshelf”).
We discovered how employees wanted items grouped
together and what labels made the most sense to them.
The bottom line:
Measured Progress employees created the IA for their intranet.
32. Conclusions
Redesign of the site was a success because:
We chose simplicity over cuteness (the “In” metaphor).
We unified two separate sites (Insite, HR Policies and
Procedures) that were created with two different
applications.
We built out a navigational hierarchy that replaced a broad
and shallow architecture (10 categories, 1-2 levels deep) with
an architecture of medium depth and breadth (7 categories,
3-4 levels deep).
The bottom line:
Employees can find what they need easily and quickly.
33. Thank You
Questions?
Elke Oberg, Electronic Marketing Coordinator, Measured Progress
oberg.elke@measuredprogress.org
Bob Thomas, Manager of User Experience, Liberty Mutual
robertl.thomas@libertymutual.com
Editor's Notes
A case study: describing how we moved an intranet that wasn’t working for its employees into a successful website
Measured Progress is a not-for-profit educational testing and assessment company. The company bids on contracts with different states in the U.S. to write tests and assessments that meet legislative requirements of No Child Left Behind Act: to develop academic standards in reading and math. So they work on such projects as MCAS in Massachusetts. They’re located in Dover N.H. have 400 employees – so a lot of internal people who need to access contracts, tests, and other documents for their different projects Objectives: lead with the need, to figure out how current employees want their information organized and what should be emphasized first Goals as stated by Pat Ross, Communications Manager at Measured Progress Redesign Insite, focusing on the navigation and organization (overall IA) Make the site usable: especially when it comes to finding things Make the site attractive and understandable to employees
Insite was: Launched in July 2004 2 parts to the site, both built with diff. software ON LEFT Search box is only on home page Site map is only on home page Everything is yellow is NOT clickable What’s emphasized the most is the photo, not the info ON RIGHT Built with diff. software than page on left Built on Windows Explorermodel: can only open and close one subdirectory at a time So employees have to use trial and error methods to find info
Insite mainly relies on bulleted lists. It lacks any secondary or third level navigation. So one employee and I were looking for the Accident & Injury Report form, because she’s responsible for filling them out at the company We had to go down 7 levels of the hierarchy to find the form: She finally said: “ A person could bleed to death before the form is even located!” So people need to use the site but it’s very difficult for them to find what they’re looking for
Insite is broad and shallow 10 primary navigation categories, 1-2 levels deep No secondary or 3 rd level navigation HR Policies Procedures is narrow & deep 3 primary navigation categories (mission, general administration, HR) 4-8 levels deep Insite Job Request Form: InForm > Job Request Forms > Form (2 clicks) Policies and Procedures Safety Form: InService > HR > Policy Guide > General Administration > Operational Policies > Safety > Accident Reporting and Investigation Plan > [Text] … Accident Report Form (7 clicks)
Mental model: the supposedly clever navigation scheme was the use of “In” to describe everything: Insite (the name of the site), InGeneral, InService, InForm, InPerson, and so on Take into account different types of users: employees like Mary who had tried to find documents on Insite but had either given up looking for them, or would like so many employees, call up Elke and ask where she should go on the site new hires who had to find things through trial and error
A card sort seemed the best solution b/c we had 2 sites that needed to be unified, both that had grown too small for the additional information that kept getting added year in and year out, an IA that wasn’t working, …and we wanted to discover how employees – the principal users of the site – wanted their information organized We chose a open card sort b/c we wanted participants to tell us how they wanted the main categories of the site named (as opposed to us naming the categories for them)
Users: we had users in house We recruited people who were very familiar with and frustrated with the site, as well as new employees who could compare Insite to their intranet at their previous company Recruited employees, b/c they were familiar with the language and terms used in education Analysis: you have more information to sort though with open card sorts b/c besides what we think of as the menu options in the navigation, you also have the names of the main navigation categories, and participants use different names to express the same concept (Our Company, About Us, About Our Company, and so on) tree diagram to see how frequently our participants put cards together in the same groups
HOW WE CONDUCTED IT Create and run an open card sort with 15 MP employees, including follow-up interviews Jakob Nielsen and Tom Tullis recommend 15 participants in a card sort for the best results Analyze quantitative and qualitative data quantitative: Donna Maurer’s (UX expert in IA; written a book about card sorting): used her spreadsheet to organize the categories and generate correlation statistics IBM’s EZCalc to generate dendrographs Make recommendations for a new navigational hierarchy and structure
Met with design team to determine the most important categories: which was based on analysis of the main categories of the website and what employees needed to get their jobs done We had 1 hour with each employee, including pre- and post-task interviews, so we also wanted to limit the # of cards; optimum numbers are between 30 and 75 PHYSICAL INSTEAD OF ONLINE CARD SORT We wrote the name of each of the main items on an index card. Shuffle the cards and give the deck to the participant. Have each participant read through all the cards and ask any questions about terms they don’t understand. Have participants sort the cards into piles, placing items that belong together in the same pile. Participants can make as many or as few piles as they want; some piles can be big, others small. Participants can use blank cards to write names of items they believe are missing. At the end, have participants write labels for each of the piles. OPEN CARD SORT with 36 cards Participants are creating IA and organization of the website for you
3 criteria in order or priority Participants who were familiar with the website (no learning curve; know the nomenclature) Recruit people from as many diff. Depts. as possible Get an equal number of men and women (came up short but was the least important of our 3 main criteria)
Actionable items: info you need to access WHAT I WANT TO USE Home Page Contracts Forms Reference material: background info WHAT I WANT TO REFER TO Department Sites Employee Directory Working at Measured Progress Helpdesk
Card sort over 5 days We began to see trends after the first day of testing (5 participants) Users were grouping categories in similar groups but with different names
After all 15 card sorts were completed, we standardized the main categories. We gave categories “with similar names or concepts a consistent name” and combined “groups where participants used the same basic concept but a slightly different label.” —Maurer (2007), “Instructions for Use: Card Sort Analysis Spreadsheet” Then you standardize the categories by finding patterns in the labels people use: Facility Info/Where/Facilities/Logistics So you bubble up the info to provide a label that can apply to similar groupings, like HR Facilities and Locations: standardized category for 4 different labels
Example: “Facilities & Locations.” 8 participants used this category. They put 23 cards into the “Facilities & Location” category (an average of ~3 cards per participant), and used 6 unique cards. It has an agreement number of 0.48. This means that about half - 48% - of participants put the same 3 cards in this category. Higher agreement numbers are better and let you know that more participants used this category.
Used EZCalc and USort to generate dendrographs. Beta product from IBM that’s no longer supported. But wanted something I could use quickly and that was free. In this case, we had 36 cards per participant and it worked. (I just did another card sort with 74 cards and the program crashed). The green threshold line (30%) indicates lower thresholds (users were more likely to pair any two cards together): Like corporate travel and reimbursement; shipping and distribution, and printing and copying while the pink threshold line (70%) indicates higher thresholds (users were less likely to pair them together): like For New Employees and other groupings: see HR Policies So you’re trying to look at how frequently users put two cards together in the same group. Take the results with a grain of salt but the items seem to group together Most important take-away: participants wanted to divide the HR Policies from the HR Procedures. They were really interested in the Policies having to do with payback and pay outs: payroll, purchasing and requisitions, corporate travel, reimbursement Wanted that separated out from HR Policies: wellness programs, diversity, safety, work schedules, personnel records, etc. THIS MAKES SENSE: what forms you need to get your job done vs. what documentation you need to reference
9 major categories, which allows for scalability Can put new pages under at least one of the major categories
ALSO RELIED ON QUALITATIVE DATA (USER COMMENTS) Example: many users of Amazon.com have probably formed a mental model of a department store; this is a case where conceptual and mental models match. QUALITATIVE DATA Mental model in the current IA of Insite: metaphor of including “In” at the front of each of the labels – InGeneral, InService, InPerson – a fabricated language metaphor that didn’t help users in their wayfinding NEW: they saw it as a reference library, with a big bookshelf of benefits and other information. This mental model helped us drive the new IA of the site
Participants wanted easier access to information using primary, secondary, and third-level navigation Participants wanted a consistent navigational structure, i.e., one that didn’t change. (Search, Site Map) Participants wanted “HR Policies and Procedures” broken into two separate categories: HR Forms (such as “Corporate Travel,” “Payroll,” “Requisitions”) HR Policies (such as “Diversity,” “Safety,” “Workplace Conduct”) HR Forms: reimbursement info requiring action HR Policies: reference material requiring comprehension or application Use a navigation hierarchy of medium depth and breadth Use a primary navigation hierarchy of no more than 8 or 9 categories Go 3 or 4 levels deep As recommended in the Polar Bear book on Information Architecture (Rosenfield and Morville)
A SECOND LEVEL PAGE Place the Insite logo in the upper left Add Measured Progress branding at the top: “It’s all about student learning. Period.” Add a Home category in the menu bar Add a menu bar with 8 categories: “Home,” “News & Events,” “Forms,” “Contracts,” “Departments,” “HR,” “Helpdesk,” “About Us” Add a “Search” box, which is attached to the menu bar Add “Contact Us” and “Site Map” links in the upper right Add a “Search Employee Directory” box, with a link to the “Employee Directory” Add a “Quick Links” box, which acts as a “Favorites” area Add secondary navigation on the left-hand side of the page, in this case HR Forms (such as “Benefits” and “Corporate Travel”) Add sub-menus for the secondary navigation, in this case HR Policies and Programs (such as “Compensation” and “Diversity”) Add new information and display it in the main area of the page, including updated “HR Forms” and “HR Policies and Programs” sections
Main navigation bar at the top of each page Sub-navigation options Quick links on home page and in the footer Expanded navigational hierarchy: before 5 main categories, now 7 categories Designed wider: before 760 pixels, now 920 pixels
Three-column design on second-level pages Third-level sub-navigation Home on main navigation bar Search at top right of page
We implemented a page for each department, so each department feels represented Employees can find what each department does Departments can post information they want to post
Formerly known as the Policy Guide run by separate software different look and feel different search engine and its own website. HR can still update the section on their own.
Formerly known as the Policy Guide run by separate software, with a different look and feel, a different search engine and its own website. HR can still update the section on their own.
The Help section is new and is organized by issues.
Screenshot of highest level, with folder structure in the CMS, and that it’s a mirror of the navigation Content editors can find things quickly in the CMS. The hierarchy translated to the editing level. What it can do in regards to users Generates the side bar automatically
ITERATIVE PROCESS The main issue with Insite: employees couldn’t find information, and couldn’t complete their work, because the site provides only first-level navigation. It’s missing secondary and contextual embedded navigation (Favorites). So this puts the burden on employees to find their own way thru the website (trial and error) The open card sort allowed users to group items together and create the labels they wanted – in a way that fit their mental model of a reference library…. And it allowed them to show how they wanted to navigate the website. Analysis showed that employees wanted simple, straightforward ways to get to information. MP: clearly sees benefits of their corporate intranet and wants to improve the site for its employees, putting users first BOTTOM LINE: this card sort enabled MP employees to create the IA for the site