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It is said that Switzerland is a country where residents book appointments to do laundry in their own homes.
In other words, they leave little for chance.
But when the unexpected intruded on the mountain nation, the Canton – or state – of Zurich had to scramble to deal with the aftershock of the COVID pandemic.
Almost overnight, the number of applications for short-time work rose to more than 10,000 – up from 10 in the months before.
In a three month stretch, 30,000 payments had to be processed – a task that previously took 25 minutes per imbursement.
In normal times, an applicant would have had to download an Excel file, fill out certain parts by hand, and send it out by mail. The form would then be scanned and uploaded to a 30-year-old document management system with a complex interface.
Even then, much of the data was inaccurate or incomplete.
The result-oriented Swiss were not about to revert to these flawed methods when so much was at stake. The flurry of applications would have required the canton to hire an additional 70 full-time employees – a near-impossible undertaking when so much of the country was locked down.
But what if humans weren’t brought on?
What if the Canton of Zurich turned to robotics instead?
Human ingenuity and automated efficiency
With a population of more than 1.5 million, the Canton of Zurich is considered the heart of Switzerland’s economy. And as the global center of banking and finance, the city of Zurich is the canton’s de facto capital.
As in the rest of Switzerland, citizens appear to be obsessed with getting things right.
Determined not to make any mistakes as it developed the short-time work application and payment solution, the canton began working with enterprise resource planning (ERP) software leader SAP. SAP’s Business Technology Platform (BTOP) would handle basic and backend functionalities, while SAP’s Intelligent Robotic Process Automation (iRPA) provided the software robots and digital workers.
Working under a tight deadline, SAP Services and Support mobilized a versatile, global team specializing in flexible problem-solving. Once targets were agreed upon each morning, the iRPA developers began coding various parts of the application.
The iRPA was linked to two older legacy systems, eliminating the need to create expensive and time-consuming interfaces.
Every evening, business experts conducted application tests, delivering feedback to the developers and project team.
The platform faced close scrutiny when it was deployed in April 2020. Within two weeks, the processing time per application had decreased from 25 minutes to 30 seconds. How’s that for Swiss precision?
Two bots took on the primary responsibilities for automating the applications and payments, as well as ensuring that most data was digitally authenticated according to local business rules.
Payments were received in less than two weeks.
In total, the canton was able to rely on an automation level of 85%, with just 15% of the documents having to be revalidated by a live human being.
No additional staff members needed to be recruited and employed during a period when most Swiss citizens were working from home.
Without the solution, “we would never have managed to process and pay the enormous number of short-time working compensations,” observed Christian Truog, CFO of the Canton of Zurich’s labor authority.
Most importantly, the canton now understands the fine points of developing a modern iRPA application – knowledge that can be called upon to meet the next challenge.
As a result, the office of information technology at the Canton of Zurich’s department of finance received a 2022 SAP Innovation Award, based on the pragmatic project approach, swift implementation, business benefits and positive feedback on the new platform. You can get the details on what they accomplished to earn this coveted award in their pitch deck.
Despite the pressures and the quick turnover, the solution managed to embody everything about the Swiss character – a culture where, as the adage goes, spontaneity is considered wonderful, so long as it’s planned.
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Generative AI models for businesses threaten to upend the world of content creation, with substantial impacts on marketing, software, design, entertainment, and interpersonal communications. These models are able to produce text and images: blog posts, program code, poetry, and artwork. The software uses complex machine learning models to predict the next word based on previous word sequences, or the next image based on words describing previous images. Companies need to understand how these tools work, and how they can add value.
Large language and image AI models, sometimes called generative AI or foundation models, have created a new set of opportunities for businesses and professionals that perform content creation. Some of these opportunities include:
How adept is this technology at mimicking human efforts at creative work? Well, for an example, the italicized text above was written by GPT-3, a “large language model” (LLM) created by OpenAI, in response to the first sentence, which we wrote. GPT-3’s text reflects the strengths and weaknesses of most AI-generated content. First, it is sensitive to the prompts fed into it; we tried several alternative prompts before settling on that sentence. Second, the system writes reasonably well; there are no grammatical mistakes, and the word choice is appropriate. Third, it would benefit from editing; we would not normally begin an article like this one with a numbered list, for example. Finally, it came up with ideas that we didn’t think of. The last point about personalized content, for example, is not one we would have considered.
Overall, it provides a good illustration of the potential value of these AI models for businesses. They threaten to upend the world of content creation, with substantial impacts on marketing, software, design, entertainment, and interpersonal communications. This is not the “artificial general intelligence” that humans have long dreamed of and feared, but it may look that way to casual observers.
Generative AI can already do a lot. It’s able to produce text and images, spanning blog posts, program code, poetry, and artwork (and even winning competitions, controversially). The software uses complex machine learning models to predict the next word based on previous word sequences, or the next image based on words describing previous images. LLMs began at Google Brain in 2017, where they were initially used for translation of words while preserving context. Since then, large language and text-to-image models have proliferated at leading tech firms including Google (BERT and LaMDA), Facebook (OPT-175B, BlenderBot), and OpenAI, a nonprofit in which Microsoft is the dominant investor (GPT-3 for text, DALL-E2 for images, and Whisper for speech). Online communities such as Midjourney (which helped win the art competition), and open-source providers like HuggingFace, have also created generative models.
These models have largely been confined to major tech companies because training them requires massive amounts of data and computing power. GPT-3, for example, was initially trained on 45 terabytes of data and employs 175 billion parameters or coefficients to make its predictions; a single training run for GPT-3 cost $12 million. Wu Dao 2.0, a Chinese model, has 1.75 trillion parameters. Most companies don’t have the data center capabilities or cloud computing budgets to train their own models of this type from scratch.
But once a generative model is trained, it can be “fine-tuned” for a particular content domain with much less data. This has led to specialized models of BERT — for biomedical content (BioBERT), legal content (Legal-BERT), and French text (CamemBERT) — and GPT-3 for a wide variety of specific purposes. NVIDIA’s BioNeMo is a framework for training, building and deploying large language models at supercomputing scale for generative chemistry, proteomics, and DNA/RNA.OpenAI has found that as few as 100 specific examples of domain-specific data can substantially improve the accuracy and relevance of GPT-3’s outputs.
To use generative AI effectively, you still need human involvement at both the beginning and the end of the process.
To start with, a human must enter a prompt into a generative model in order to have it create content. Generally speaking, creative prompts yield creative outputs. “Prompt engineer” is likely to become an established profession, at least until the next generation of even smarter AI emerges. The field has already led to an 82-page book of DALL-E 2 image prompts, and a prompt marketplace in which for a small fee one can buy other users’ prompts. Most users of these systems will need to try several different prompts before achieving the desired outcome.
Then, once a model generates content, it will need to be evaluated and edited carefully by a human. Alternative prompt outputs may be combined into a single document. Image generation may require substantial manipulation. Jason Allen, who won the Colorado “digitally manipulated photography” contest with help from Midjourney, told a reporter that he spent more than 80 hours making more than 900 versions of the art, and fine-tuned his prompts over and over. He then improved the outcome with Adobe Photoshop, increased the image quality and sharpness with another AI tool, and printed three pieces on canvas.
Generative AI models are incredibly diverse. They can take in such content as images, longer text formats, emails, social media content, voice recordings, program code, and structured data. They can output new content, translations, answers to questions, sentiment analysis, summaries, and even videos. These universal content machines have many potential applications in business, several of which we describe below.
These generative models are potentially valuable across a number of business functions, but marketing applications are perhaps the most common. Jasper, for example, a marketing-focused version of GPT-3, can produce blogs, social media posts, web copy, sales emails, ads, and other types of customer-facing content. It maintains that it frequently tests its outputs with A/B testing and that its content is optimized for search engine placement. Jasper also fine tunes GPT-3 models with their customers’ best outputs, which Jasper’s executives say has led to substantial improvements. Most of Jasper’s customers are individuals and small businesses, but some groups within larger companies also make use of its capabilities. At the cloud computing company VMWare, for example, writers use Jasper as they generate original content for marketing, from email to product campaigns to social media copy. Rosa Lear, director of product-led growth, said that Jasper helped the company ramp up our content strategy, and the writers now have time to do better research, ideation, and strategy.
Kris Ruby, the owner of public relations and social media agency Ruby Media Group, is now using both text and image generation from generative models. She says that they are effective at maximizing search engine optimization (SEO), and in PR, for personalized pitches to writers. These new tools, she believes, open up a new frontier in copyright challenges, and she helps to create AI policies for her clients. When she uses the tools, she says, “The AI is 10%, I am 90%” because there is so much prompting, editing, and iteration involved. She feels that these tools make one’s writing better and more complete for search engine discovery, and that image generation tools may replace the market for stock photos and lead to a renaissance of creative work.
DALL-E 2 and other image generation tools are already being used for advertising. Heinz, for example, used an image of a ketchup bottle with a label similar to Heinz’s to argue that “This is what ‘ketchup’ looks like to AI.” Of course, it meant only that the model was trained on a relatively large number of Heinz ketchup bottle photos. Nestle used an AI-enhanced version of a Vermeer painting to help sell one of its yogurt brands. Stitch Fix, the clothing company that already uses AI to recommend specific clothing to customers, is experimenting with DALL-E 2 to create visualizations of clothing based on requested customer preferences for color, fabric, and style. Mattel is using the technology to generate images for toy design and marketing.
GPT-3 in particular has also proven to be an effective, if not perfect, generator of computer program code. Given a description of a “snippet” or small program function, GPT-3’s Codex program — specifically trained for code generation — can produce code in a variety of different languages. Microsoft’s Github also has a version of GPT-3 for code generation called CoPilot. The newest versions of Codex can now identify bugs and fix mistakes in its own code — and even explain what the code does — at least some of the time. The expressed goal of Microsoft is not to eliminate human programmers, but to make tools like Codex or CoPilot “pair programmers” with humans to improve their speed and effectiveness.
The consensus on LLM-based code generation is that it works well for such snippets, although the integration of them into a larger program and the integration of the program into a particular technical environment still require human programming capabilities. Deloitte has experimented extensively with Codex over the past several months, and has found it to increase productivity for experienced developers and to create some programming capabilities for those with no experience.
In a six-week pilot at Deloitte with 55 developers for 6 weeks, a majority of users rated the resulting code’s accuracy at 65% or better, with a majority of the code coming from Codex. Overall, the Deloitte experiment found a 20% improvement in code development speed for relevant projects. Deloitte has also used Codex to translate code from one language to another. The firm’s conclusion was that it would still need professional developers for the foreseeable future, but the increased productivity might necessitate fewer of them. As with other types of generative AI tools, they found the better the prompt, the better the output code.
LLMs are increasingly being used at the core of conversational AI or chatbots. They potentially offer greater levels of understanding of conversation and context awareness than current conversational technologies. Facebook’s BlenderBot, for example, which was designed for dialogue, can carry on long conversations with humans while maintaining context. Google’s BERT is used to understand search queries, and is also a component of the company’s DialogFlow chatbot engine. Google’s LaMBA, another LLM, was also designed for dialog, and conversations with it convinced one of the company’s engineers that it was a sentient being— an impressive feat, give that it’s simply predicting words used in conversation based on past conversations.
None of these LLMs is a perfect conversationalist. They are trained on past human content and have a tendency to replicate any racist, sexist, or biased language to which they were exposed in training. Although the companies that created these systems are working on filtering out hate speech, they have not yet been fully successful.
One emerging application of LLMs is to employ them as a means of managing text-based (or potentially image or video-based) knowledge within an organization. The labor intensiveness involved in creating structured knowledge bases has made large-scale knowledge management difficult for many large companies. However, some research has suggested that LLMs can be effective at managing an organization’s knowledge when model training is fine-tuned on a specific body of text-based knowledge within the organization. The knowledge within an LLM could be accessed by questions issued as prompts.
Some companies are exploring the idea of LLM-based knowledge management in conjunction with the leading providers of commercial LLMs. Morgan Stanley, for example, is working with OpenAI’s GPT-3 to fine-tune training on wealth management content, so that financial advisors can both search for existing knowledge within the firm and create tailored content for clients easily. It seems likely that users of such systems will need training or assistance in creating effective prompts, and that the knowledge outputs of the LLMs might still need editing or review before being applied. Assuming that such issues are addressed, however, LLMs could rekindle the field of knowledge management and allow it to scale much more effectively.
We have already seen that these generative AI systems lead rapidly to a number of legal and ethical issues. “Deepfakes,” or images and videos that are created by AI and purport to be realistic but are not, have already arisen in media, entertainment, and politics. Heretofore, however, the creation of deepfakes required a considerable amount of computing skill. Now, however, almost anyone will be able to create them. OpenAI has attempted to control fake images by “watermarking” each DALL-E 2 image with a distinctive symbol. More controls are likely to be required in the future, however — particularly as generative video creation becomes mainstream.
Generative AI also raises numerous questions about what constitutes original and proprietary content. Since the created text and images are not exactly like any previous content, the providers of these systems argue that they belong to their prompt creators. But they are clearly derivative of the previous text and images used to train the models. Needless to say, these technologies will provide substantial work for intellectual property attorneys in the coming years.
From these few examples of business applications, it should be clear that we are now only scratching the surface of what generative AI can do for organizations and the people within them. It may soon be standard practice, for example, for such systems to craft most or all of our written or image-based content — to provide first drafts of emails, letters, articles, computer programs, reports, blog posts, presentations, videos, and so forth. No doubt that the development of such capabilities would have dramatic and unforeseen implications for content ownership and intellectual property protection, but they are also likely to revolutionize knowledge and creative work. Assuming that these AI models continue to progress as they have in the short time they have existed, we can hardly imagine all of the opportunities and implications that they may engender.
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Acquisition Allows Company to Expand Digital-Transformation Services Deeper into the Automotive Industry
ATLANTA, Oct. 25, 2022 /PRNewswire/ — Docufree, a leading provider of enterprise information management (EIM) and digital business process services, announced today the acquisition of DealerDOCX, a leading provider of secure end-to-end, cloud-based document-management solutions for the automotive industry.
Founded in 2014, DealerDOCX is a proven and established intelligent document management company poised to continue its growth in the auto-dealer market as well as adjacent verticals such as auto services. As part of the acquisition, Docufree will also be adding several key patents to our IP portfolio including unique business-intelligence software that is integrated into dealer Enterprise Resource Planning (ERP) systems to create fast, secure, high-quality, and cloud-based document management.
“With its strong recurring revenue model, blue-chip clients and very low customer churn, the acquisition of DealerDOCX presents Docufree with a multitude of opportunities,” said Brad Jenkins, CEO of Docufree. “This acquisition also expands Docufree’s deep expertise in software engineering and cloud services, along with domain insight into automobile sales and operations. Additionally, there are several innovative technology components that seamlessly complement and integrate with our existing technology suite of offerings—giving us a tremendous growth trajectory involving smart, agile enterprise solutions that result in successful digital transformations.
DealerDOCX’s document-intelligence proprietary cloud solution, delivered via a Software-as-a-Service (SaaS) model, is powered by the company’s patented automated audit-compliance analytics engine – which streamlines compliance engagements by analyzing client-specific documents and leverages artificial intelligence (AI) to generate audit scorecards and document bundles. The platform enables auto dealerships to effectively navigate compliance requirements with sales reps and auditing staff to ensure time-saving and cost-efficient practices without the need for external auditors. This solution helps dealerships avoid costly government or Original Equipment Manufacturer (OEM) incentive-based compliance violation fines and find room for revenue improvement.
The DealerDOCX platform maintains strong strategic partnerships with dominant industry Dealer Management System (DMS) providers, such as Dealertrack Technologies, CDK Global, and Reynolds & Reynolds, to provide full integration utilizing its predictive-analytics capabilities into their respective dealer systems. DealerDOCX has built a strong base of more than 350 customers across multiple states and markets.
“We look forward to maximizing their technology in our content-enabled vertical applications while empowering channel partners with many new opportunities to grow their digital transformation suite and recurring cloud revenue models,” said David Winkler executive vice president and chief product officer of Docufree. “DealerDOCX is helping dealerships across the country accelerate their digital transformation objectives, by capturing unprotected physical documents, reducing on-site labor and storage expenses, providing easy and secure digital access to deal jackets, repair orders, invoices, and other sensitive files, while assuring compliance. With this acquisition we’re bringing together the power of our content services platform with their specialized automotive expertise to further drive innovation for both existing and future customers.”
Docufree is a leading provider of enterprise information management and digital business process services. Services include large-volume document capture, data extraction and integration, intelligent process automation, cloud-based document management, and digital mailroom services. Since 1999, Docufree has securely managed and modernized how people and the systems they use daily interact with data and each other. Today, over 1,000 enterprises and government agencies rely on Docufree to empower their workforce by ensuring processes are executed with speed, accuracy, and compliance from wherever work needs to happen. For more information, visit www.docufree.com. Follow us on LinkedIn and Twitter @Docufree then like us on Facebook.
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Today’s consumer has a lot of control. They can do their own research and make purchases. The dramatic rise in information and data availability over the past decades has meant that information users often find themselves in a difficult position to make meaningful decisions.
The latest research report provides a complete assessment of the Medical Document Management Systems market for the forecast year 2023-2033, which is beneficial for companies regardless of their size and revenue. This survey report covers the major market insights and industry approach towards upcoming years. The Medical Document Management Systems market report presents data and information on the development of the investment structure, technological improvements, market trends and developments, capabilities, and comprehensive information on the key players of the Medical Document Management Systems market. The worldwide market strategies undertaken, with respect to the current and future scenario of the industry, have also been listed in the study.
The study brings a perfect bridging between qualitative and statistical data of Medical Document Management Systems Market. The study provides historical data (i.e. Consumption & Value) from 2017 to 2022 and forecast till 2033. The market report additionally has information concerning the supply-demand, market growth and improvement factors, business earnings and loss, economic grade, and certain strategic tips all mentioned. The numerical statistics are copied with statistical tools, collectively with SWOT assessment, BCG matrix, and PESTLE assessment. Statistics are provided in graphical form to provide easy expertise of the facts and figures. To get the exact yearly growth variance and the Y-O-Y growth rate, Download PDF Sample Report!
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Figure: The below figure indicated a graphical representation of the report along with market value (USD In Mn) & Y-O-Y growth rate:
Competitive Spectrum – Top Companies leveraging Medical Document Management Systems Market:
Allscripts Healthcare Solutions
Nextgen Healthcare Information Systems
Siemens Medical Solutions USA
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7. Their weaknesses
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Medical Document Management Systems Market Segments Evaluated in the Report:
Document Scanning Software
Document Management Software
Classified Applications of Medical Document Management Systems:
Hospitals And Clinics
Key regions divided during this report:
– The Middle East and Africa Medical Document Management Systems Market (Saudi Arabia, United Arab Emirates, Egypt, Nigeria, South Africa)
– North America Medical Document Management Systems Market (United States, Canada, Mexico)
– Asia Pacific Medical Document Management Systems Market (China, Japan, Korea, India, Southeast Asia)
– South America Medical Document Management Systems Market (Brazil, Argentina, Colombia)
– Europe Medical Document Management Systems Market (Germany, UK, France, Russia, Italy)
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The Medical Document Management Systems market research is sourced for experts in both primary and developed statistics and includes qualitative and quantitative details. The analysis is derived from Manufacturers’ experts work around the clock to recognize current circumstances, such as COVID-19, the possible financial reversal, the impact of a trade slowdown, the importance of the limitation on export and import, and all the other factors that may increase or decrease market growth during the forecast period.
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Medical Document Management Systems market research report will be sympathetic for:
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Q5. What is the total market value of Medical Document Management Systems market report?
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Q7. Who are the key players in Medical Document Management Systems market?
Q8. Which region has the highest growth in Medical Document Management Systems Market?
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Chapter 1. Introduction
The Medical Document Management Systems research work report covers a brief introduction to the global market. this segment provides opinions of key participants, an audit of Medical Document Management Systems industry, an outlook across key regions, financial services and various challenges faced by Medical Document Management Systems Market. This section depends on the scope of the study and report guidance.
Chapter 2. Outstanding Report Scope
This is the second most important chapter, which covers market segmentation along with a definition of Medical Document Management Systems. It defines the entire scope of the Medical Document Management Systems report and the various facets it is describing.
Chapter 3. Market Dynamics and Key Indicators
This chapter includes key dynamics focusing on drivers[ Includes Globally Growing Medical Document Management Systems Prevalence and Increasing Investments in Medical Document Management Systems, Key Market Restraints [High Cost of Medical Document Management Systems], opportunities [Emerging Markets in Developing Countries] and also presented in detail the emerging trends [Consistent Launch of New Screening Products] growth challenges, and influence factors shared in this latest report.
Chapter 4. Type Segments
This Medical Document Management Systems market report shows the market growth for various types of products marketed by the most comprehensive companies.
Chapter 5. Application Segments
The examiners who wrote the report have fully estimated the market potential of key applications and recognized future opportunities.
Chapter 6. Geographic Analysis
Each regional market is carefully scrutinized to understand its current and future growth, development, and demand scenarios for this market.
6.1 North America: insight study
6.2 Europe: serves complete insight study
6.4 Rest of the World
Chapter 7. Top Manufacturing Profiles
The major players in the Medical Document Management Systems market are detailed in the report based on their market size, market service, products, applications, regional growth, and other factors.
Chapter 8. Pricing Analysis
This chapter provides price point analysis by region and other forecasts.
Chapter 09. North America Medical Document Management Systems Market Analysis
This chapter includes an assessment of Medical Document Management Systems product sales across major countries of the United States and Canada along with a detailed segmental outlook across these countries for the forecasted period 2022-2031.
Chapter 10. Latin America Medical Document Management Systems Market Analysis
Major countries of Brazil, Chile, Peru, Argentina, and Mexico are assessed apropos to the adoption of Medical Document Management Systems.
Chapter 11. Europe Medical Document Management Systems Market Analysis
Market Analysis of Medical Document Management Systems report includes insights on supply-demand and sales revenue of Medical Document Management Systems across Germany, France, United Kingdom, Spain, BENELUX, Nordic and Italy.
Chapter 12. Asia Pacific Excluding Japan (APEJ) Medical Document Management Systems Market Analysis
Countries of Greater China, ASEAN, India, and Australia & New Zealand are assessed and sales assessment of Medical Document Management Systems in these countries is covered.
Chapter 13. The Middle East and Africa (MEA) Medical Document Management Systems Market Analysis
This chapter focuses on Medical Document Management Systems market scenario across GCC countries, Israel, South Africa, and Turkey.
Chapter 14. Research Methodology
The research methodology chapter includes the following main facts,
14.2 Secondary Research
14.3 Primary Research
Chapter 15. Conclusion
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Cloud-based project management software has revolutionized how companies manage their workflows, time-tracking, and communications for years now. They can even aid in forecasting future growth. In short, gone are the days of keeping track of umpteen email threads and Slack chats to stay on top of your team’s progress.
That is unless you’ve yet to upgrade to a project management app, in which case you’re still stuck with the hassles of managing projects across multiple locations.
If that’s the case, it’s worth trying to convince your company to make the switch (you can even show them this article or our other articles on project management software) to one centralized platform to save vast amounts of time and money.
Yet, how do you know which project management software tool to recommend?
That’s why I’ve put together all these comparison articles to let you know which platform will work best for your needs and budget.
Not all project management tools are created equally, with some offering more features and functionality which appeal to enterprise-level companies. However, small businesses and entrepreneurs often prefer more basic tools that offer superior ease of use due to their simplicity.
Today, Trello and Monday.com, two of the leading project management programs, are getting put to the ultimate test by comparing their features, customer support, and pricing structures.
Read on to discover which one of these task management powerhouses is right for your company.
Trello was the brainchild of New York software company Glitch in 2011 before launching as its own company in 2014. Three years later, in 2017, Trello was purchased by Australian software company Atlassian, best known for being the creator of Jira, another project management software.
What’s the primary appeal of Trello for its users?
The software rose to prominence because of its intuitive use of kanban boards to visualize workflows, tasks, and projects. In a nutshell, it works like this; a Trello board represents an entire project, a list represents the workflow (the order tasks need to be completed), and a card represents an individual task.
Cards contain task due dates, instructions, attachments, and notes, making it easy to outline what a team member needs to do to complete their work correctly. For instance, if a task has complicated instructions, you can attach a Word file to the card that explains the work in more detail.
The biggest appeal of Trello is how easy it is to use, with most being able to jump in and start using the program on day one. Besides that, there’s a free version that’s perfect for freelancers and entrepreneurs that want to keep track of their daily tasks but don’t want to spend money on a monthly subscription.
Where Trello tends to fall short for larger teams is its need for advanced project management features. For instance, Asana and other programs offer Gantt charts, calendar views, and time-tracking, whereas Trello does not (unless you pay for power-ups, but more on that in a bit).
Tel-Aviv-based company Monday.com launched in 2014 as a workplace operating system, or WorkOS for short. It’s a cloud-based platform that enables users to track projects and workflows, visualize data, and collaborate with teams.
Unlike Trello, which thrives on its user-friendly layout, Monday.com is a far more robust and extensive project management system with advanced features. For this reason, larger teams and enterprise-level companies use Monday for its wide range of features, templates, automation capabilities, and dashboards.
It’s also far easier to keep track of complex projects and multiple teams using Monday.com than Trello — with handy features like its shared team calendar — where you can view progress on all active projects across all your teams.
Users can also switch between multiple views, including:
As you can see, you can visualize your project data in a wide variety of ways using Monday.com, which you can’t get with Trello. Monday.com also features no-code automation, a document editor, and the ability to attach any file type to a project.
While there technically is a free version of Monday.com, it’s more of a tech demo to see if the program is a good fit for you, as it only contains 3 boards and 2 team members (although you do get unlimited docs). The platform really starts to spread its wings in the Standard Plan, which is still affordable ($10 per month billed annually) and includes all of its most impressive features.
Now that you’re a bit more familiar with each platform let’s take a more in-depth look at the primary features of both Trello and Monday.com. That way, you’ll get a feel for how they both handle data visualization, task management, team collaboration, automation, and any additional bells and whistles.
Let’s get things started by taking a look at Trello.
Trello’s free plan grants you access to the feature it’s perfected the most — the kanban board (also called Trello board).
If you’re a fan of simplicity, you’ll love Trello’s default layout, and you won’t have to pay a dime for it. Besides lists, boards, and cards, a ton of scheduling and sorting options are included in the free version. Trello uses simple drag-and-drop controls for its boards and lists, and they’re a cinch to figure out.
Here’s an overview of what a typical Trello board looks like:
A board represents a project that consists of lists containing cards (tasks). You can name a list anything you want, but the following are the most common list names (and functions).
Pending approval. This list contains tasks that have been completed but still require editing/approval.
To-do. The to-do list contains a series of task cards that have yet to be completed. You’ll be able to see the due date for each task in the quick view – meaning you won’t have to click on the card for more details to see deadlines, which comes in handy.
Doing. This list houses all the tasks that you’re currently working on.
Done. This list contains tasks that are complete.
Each task card has a set of unique information displayed in the quick view, including:
Due date. The deadline for the task will display at the bottom of the card.
Labels. Trello allows you to color-code cards to label them however you want. The most common way to do so is to color tasks according to their priority level (i.e., green for low priority, yellow for medium priority, and red for high priority).
Team members. You can assign team members to task cards, and their picture/logo will appear next to it, so there’s no confusion on who needs to complete which tasks.
This layout is straightforward, and you probably won’t need to view any tutorials. For this reason, Trello is an excellent choice for small teams, freelancers, and entrepreneurs.
They also perfected the kanban way of doing things, beating out other programs’ kanban boards easily, including Asana and Monday.com. Overall, the Trello board is a fantastic project management and collaboration tool.
Trello also has a mobile app version to enable users to manage projects on the fly.
Trello offers users various project templates, which can be handy if you’re drawing a blank on organizing your tasks.
They even break the templates up into categories, including:
Trello does have some versatility when you get creative, as it’s entirely up to you to define what lists and cards mean. They don’t necessarily have to represent tasks and processes; those are just the most common uses. As such, looking at some of Trello’s templates can help get your creative juices flowing.
To save you from having to complete repetitive tasks over and over (such as moving cards to the done list), Trello has no-code automation built-in to every board. They call their automation assistant Butler, and you can automate just about anything with it.
Instead of using code, you’ll have a set of parameters to work with when automating actions. Here’s a quick example of how you may automate a task using Butler:
Parameter: Whenever a checklist gets completed.
Automation: Move the task to the done list.
Automation: Notify (team member) that their approval is required.
As you can see, you can set more than one automation to a parameter, which comes in handy. All-in-all, Trello has a pretty intuitive and effective automation system.
A project management tool won’t do you much good if you can’t incorporate it into your existing business workflows. Luckily, Trello integrates with over 200 apps, including:
Wrike (through Zapier)
Given the popularity of the apps it integrates with, the chances are high that you can easily incorporate Trello into your workflows. Yet, it’s important to note that some of these integrations, such as Wrike, are only possible through other integrated platforms like Zapier.
While Trello is a bit limited in its base version, there are ways to add more advanced features to it through power-ups, Trello’s version of add-ons. With these power-ups, Trello is able to catch up to some of its more advanced counterparts, such as Asana or ClickUp. With power-ups, you can add things like Gantt charts, the ability to preview Microsoft Word documents, external sharing, calendar views, time-tracking, and more in-depth automation features.
However, it’s crucial to note that most of these power-ups will require an additional monthly subscription, which will add to the overall cost of Trello. Beyond that, many of these applications are from third parties instead, and the quality of the power-ups tends to be hit-and-miss.
What’s worse is that many power-up features, like Gantt charts and time-tracking, are already included in other project management tools, like Monday.com.
Now let’s take a look at what Monday.com has to offer in terms of its primary features. It differs from Trello in that it only uses kanban boards for workspace overview purposes. Regarding the nitty-gritty of task management, Monday.com tends to rely more on lists.
At first glance, you’ll quickly notice that Monday.com is far more complex than Trello. As such, it can take some time before you can hit the ground running with the platform, which may discourage some users. Yet, if you manage large teams for an enterprise-level organization, you’ll need the more in-depth features offered by Monday.com, so it’s worth learning about the platform.
While it may seem a tad intimidating, it won’t take long to get the hang of Monday, as it is pretty intuitive despite the vast number of features. For instance, Monday makes it effortless to view the progress for multiple projects in an easy-to-read grid format that’s not available on Trello. Advanced features offered by Monday.com include resource management, Gantt charts, a document editor, file attachments, and detailed form templates.
Like Trello, Monday.com also has an Android app and an IOS app that you can use to keep track of your projects while on the go.
An advantage Monday.com has over Trello is its built-in document editor. On Trello, you can only link to or attach files from other word processors. With Monday, you can create project documents inside the program thanks to Monday Workdocs.
You can create checklists, graphs, and action items straight from the document editor. That means you’ll be able to instantly create tasks and lists without having to stop working on your document. The editor also allows you to collaborate with team members in real-time, and they can edit the document as they please. That enables you to have powerful brainstorming sessions with your team, no matter where they are in the world.
There are dozens of form templates on Monday.com to collect and manage your requests. These include:
Creative request forms
IT request forms
Legal request forms
Facilities request forms
Project request forms
HR request forms
Finance request forms
No matter what type of industry you’re in, Monday.com has a perfect form template for your business. You can easily create personalized forms for your business that you can share with critical stakeholders, such as company executives.
Monday.com is more than a project management tool; it’s an all-in-one workplace operating system, which is why it can double as a CRM (customer relationship management) tool. Instead of using Monday’s pre-built workflows, automation, and document editor to manage tasks, you can also use them to lead customers down your sales pipeline.
As such, you can use Monday.com to:
Capture leads and customer information with custom forms.
Use different views to visualize a lead’s journey down your pipeline.
Keep all data on your leads in one place for your sales team.
This type of versatility is a big reason why Monday.com is one of the leading workplace operating systems on the market.
Monday also enables automation, and it works in the same way that Trello does. With Monday.com, you can automate the following:
Due date alerts
Many more tasks
Surprisingly, Monday.com doesn’t integrate with as many apps as Trello, as it’s only compatible with 50 apps and tools. Yet, these 50 are some of the most commonly used tools, such as:
You can also integrate more apps into Monday.com by using Zapier.
Now, let’s take a look at how Trello stands up to Monday.com in terms of pricing and customer support.
Regarding support, Monday.com is the clear winner, thanks to its fantastic guides, video tutorials, and community support forums. You can also contact the team if you have any questions that you can’t find answers to anywhere else.
Trello offers some helpful guides and offers priority support to its Enterprise plan members, but its offerings are more limited.
Here’s an overview of Trello’s pricing plans:
Free version. At $0 per month, you get up to 10 boards per workspace, unlimited cards, custom backgrounds, access to both mobile apps, and two-factor authentication.
Standard Plan. At $5 per month, you get unlimited boards, advanced checklists, custom fields, unlimited storage, saved searches, and more.
Premium Plan. Billed at $10 per month, this plan includes priority support, calendar view, dashboard view, timeline view, map views, admin and security features, and unlimited workspace command runs.
Enterprise Plan. At $17.50 per month, enterprise users enjoy unlimited workspaces, organization-wide permissions, organization-visible boards, power-up administration, free SSO, and user provisioning with Atlassian Access.
Trello’s pricing plans aren’t bad, and its free plan is among the best on the market, so don’t count it out if you’re looking for basic project management software.
Here are Monday.com’s pricing plans:
Free Plan. The free version only includes 2 seats, but you gain access to up to 3 boards and can create unlimited documents.
Basic Plan. At $8 per month, you get unlimited items, prioritized customer support, and unlimited free viewers.
Standard Plan. This plan is the most popular due to its affordability ($10 per month) and the robust amount of features you get, which includes a timeline view, Gantt charts, calendar views, guest access, automation, and integrations.
Pro Plan. At $16 per month, this plan gets you private boards and docs, a chart view, time tracking, a formula column, and more.
Enterprise Plan. This plan is reserved for larger companies, and you need to contact sales to determine the pricing. It includes advanced features such as enterprise-grade security & governance, as well as advanced reporting & analytics.
Monday.com is a bit on the pricier side, but the features it includes are what make it worth the cost.
Now that we’ve compared both programs regarding features, support, and pricing, it’s time to declare the victor.
There’s no denying the versatility, usability, and effectiveness of Monday.com. It’s a true workplace OS, and you can use it as a CRM, project management tool, resource management tool, and so much more. That’s not to say that Trello isn’t a fantastic program in its own right. Its free plan is outstanding, and it’s the perfect software for smaller teams and organizations.
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