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SwiftEnterprise 5.0 brings to you Team Dynamics – Emotional Intelligence Analytics – that gives you powerful insights into your team’s emotional health and its impact on team and project performance, based on their interaction on various project tasks! We have also started our journey of AI-based assistance by going conversational. Now, using Slack, talk to our Chatbot to get quick information about your work and perform routine actions right from your Slack channel.

We have a lot more new features and enhancements in this release, visit the below link to know more: https://www.digite.com/swiftenterprise/announcing-swiftenterprise-5-0/

The post SwiftEnterprise 5.0 is Here appeared first on Digité Blog.

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The world is rapidly moving towards of AI and ML-based transformation in all fields and domains. Software products are first to adopt and in fact lead such transformation. At Digité, we are thrilled to be doing our bit!

As a provider of software tools for Lean/ Agile project management, especially with large customers who run large and complex projects for their enterprise customers and have 10s of thousands of users working on our products, we generate a large amount of project performance and delivery data. Large swaths of transaction data get added to our project databases every day. This includes both structured and unstructured data, including team member conversations and comments as well as customer comments and feedback, and as such has a great potential for applying AI/ ML techniques.

The application of AI and ML techniques to this data has the potential to provide organizational insights to underlying patterns, hitherto unseen and enable them to make data-driven decisions far more effectively than what traditional metrics and measurements allowed them to.

At Digité, have started our journey in this direction with our products and this capability has been extend to all of our products over the several months.

Is your team happy? (And why you should care!)

There are several areas where we can implement AI and ML features in our products. We have selected one of the most interesting and challenging use cases that touch upon the emotional state of the team.

A number of studies in the public domain establish a direct correlation between a team’s happiness and productivity. To find intrinsic motivation, it is very important to find out the current emotional level of each and every team member.

We chose to tap into this and build something that can provide real-time team sentiment analysis. There have been many attempts to manually collect team members’ state of emotions and capture them on a day-to-day basis. Many Agile teams are known to manually track their Niko-Niko calendar that shows with an emoji the “happiness level” of each team member. We decided to automate this and other related aspects using AI/ ML techniques. To that end, we are thrilled to introduce our ‘Team Dynamics’ product.

What is your Team’s Dynamic?

To understand the underlying emotions of team members, we need to look deep into the nature of interaction and collaboration at the work-item level. To capture and analyze this, we use card (work-item) level description and comments data on each card, right from Portfolio Themes to the team level User Stories. The more the data and comments, the better the accuracy of the analysis done by the Team Dynamics module to reveal the emotional state of Team Members.

There are several aspects of a Team’s emotional state that cannot be easily plotted in a single view. Keeping this in mind, we have designed multiple components that will help you identify the various dimensions of team emotions.

Here are some of the components we have introduced.

1. Robert Plutchik’s psycho-evolutionary theory of emotion is one of the most influential classification approaches for general emotional responses. Emotions are classified into eight primary categories — anger, fear, sadness, disgust, surprise, anticipation, trust, and joy. For the manager to analyze this in detail, we have built a metric called “Time Spent in Emotion”.

This chart helps you understand the emotions that your team is expressing at the work-item level and provides a consolidated view of how much of the work was performed in each emotion category. A large bubble of a negative emotion is a red flag.

On the chart, you can click on any emotion bubble and it will show you the list of cards that were worked up in that emotion. This can help you to immediately identify issues that require your attention. Shown below is the sample image of this metric.

2. Happier teams give higher productivity. To help track this, we have introduced ‘Happiness Index’. This is a measure of the team’s happiness over the duration of the project. Shown below is a sample image. It helps you analyze the issues where the team members are in disagreement for a long period of time. If the team is not able to arrive at a consensus, it could have a long-term impact on teams’ collaboration and productivity.

3. One of the major factors that reduce happiness is disagreements. This chart helps you analyze the issues where team members disagreed for long periods of time. As mentioned earlier, if the team is not able to arrive at a consensus, it will have a long-term impact on the team’s collaboration and productivity. Shown below is a sample image of the “Disagreement Index”.

4. High performing teams are often high trust teams too. The Trust Network helps you see this. The chart has a mesh topology, where every pair of individuals in the team that converses with each other is depicted with a connector. When individuals disagree with each other, those connectors are marked red. The darker the shade of the green colour, the better the trust within the team.

These are few samples of the insights that Team Dynamics provides.

The above metrics will provide you insight into the overall team emotions. In addition, it is also important to know the work items that were impacted by the negative emotions of people working on them. There will always be a few work items that generate negative emotions, perhaps causing issues or delays with those work items. There can be several reasons for the negative emotions, such as the Product Owner (PO) not providing a complete spec, disagreements between team members and PO on the scope, dependency on other teams, etc. These could lead to work-item spill-overs across sprints and low productivity which impact the committed PI scope negatively. It could potentially reduce business value delivered to the business in the PI.

To help understand such issues, we provide meaningful insights at the work-items level as well.

Based on the “Circumplex Model” of emotion developed by James Russell, we provide the measure of the valence and arousal of the work items to find the underlying emotions. A sample image of the Valence Arousal Dominance Trend that you will see on each work-item is shown below.

Based on the recent emotions and overall VAD values, there is a Risk Score assigned to each item. This is displayed on work item list view and helps the Manager focus on higher risk items. Shown below is a sample snapshot of the list view.

We hope you find the Team Dynamics capabilities intriguing – enough to connect with us! If you’d like to learn more, just contact us here! Or write a mail to sales@digite.com

The post How are your Team Dynamics? (AI-driven Enterprise Agility in action!) appeared first on Digité Blog.

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The world is rapidly moving towards of AI and ML-based transformation in all fields and domains. Software products are first to adopt and in fact lead such transformation. At Digité, we are thrilled to be doing our bit!

As a provider of software tools for Lean/ Agile project management, especially with large customers who run large and complex projects for their enterprise customers and have 10s of thousands of users working on our products, we generate a large amount of project performance and delivery data. Large swaths of transaction data get added to our project databases every day. This includes both structured and unstructured data, including team member conversations and comments as well as customer comments and feedback, and as such has a great potential for applying AI/ ML techniques.

The application of AI and ML techniques to this data has the potential to provide organizational insights to underlying patterns, hitherto unseen and enable them to make data-driven decisions far more effectively than what traditional metrics and measurements allowed them to.

At Digité, have started our journey in this direction in our built-for-SAFe® (Scaled Agile Framework from SAI) product, SwiftEASe! Over the next several weeks, this capability will extend to all our products.

Is your team happy? (And why you should care!)

There are several areas where we can implement AI and ML features in SwiftEase. We have selected one of the most interesting and challenging use cases that touch upon the emotional state of the team.

A number of studies in the public domain establish a direct correlation between a team’s happiness and productivity. SAFe®’s one of the core principles: “Unlock the intrinsic motivation of knowledge workers” is in-line with this. To find intrinsic motivation, it is very important to find out the current emotional level of each and every team member.

We chose to tap into this and build something that can provide real-time team sentiment analysis. There have been many attempts to manually collect team members’ state of emotions and capture them on a day-to-day basis. Many Agile teams are known to manually track their Niko-Niko calendar that shows with an emoji the “happiness level” of each team member. We decided to automate this and other related aspects using AI/ ML techniques. To that end, we are thrilled to introduce our ‘Team Dynamics’ module in SwiftEASe.

What is your Team’s Dynamic?

To understand the underlying emotions of team members, we need to look deep into the nature of interaction and collaboration at the work-item level. To capture and analyze this, we use card (work-item) level description and comments data on each card, right from Portfolio Themes to the team level User Stories. The more the data and comments, the better the accuracy of the analysis done by the Team Dynamics module to reveal the emotional state of Team Members.

There are several aspects of a Team’s emotional state that cannot be easily plotted in a single view. Keeping this in mind, we have designed multiple components that will help you identify the various dimensions of team emotions.

Here are some of the components we have introduced.

1. Robert Plutchik’s psycho-evolutionary theory of emotion is one of the most influential classification approaches for general emotional responses. Emotions are classified into eight primary categories — anger, fear, sadness, disgust, surprise, anticipation, trust, and joy. For the manager to analyze this in detail, we have built a metric called “Time Spent in Emotion”.

This chart helps you understand the emotions that your team is expressing at the work-item level and provides a consolidated view of how much of the work was performed in each emotion category. A large bubble of a negative emotion is a red flag.

On the chart, you can click on any emotion bubble and it will show you the list of cards that were worked up in that emotion. This can help you to immediately identify issues that require your attention. Shown below is the sample image of this metric.

2. Happier teams give higher productivity. To help track this, we have introduced ‘Happiness Index’. This is a measure of the team’s happiness over the duration of the project. Shown below is a sample image. It helps you analyze the issues where the team members are in disagreement for a long period of time. If the team is not able to arrive at a consensus, it could have a long-term impact on teams’ collaboration and productivity.

3. One of the major factors that reduce happiness is disagreements. This chart helps you analyze the issues where team members disagreed for long periods of time. As mentioned earlier, if the team is not able to arrive at a consensus, it will have a long-term impact on the team’s collaboration and productivity. Shown below is a sample image of the “Disagreement Index”.

4. High performing teams are often high trust teams too. The Trust Network helps you see this. The chart has a mesh topology, where every pair of individuals in the team that converses with each other is depicted with a connector. When individuals disagree with each other, those connectors are marked red. The darker the shade of the green colour, the better the trust within the team.

These are few samples of the insights that Team Dynamics provides.

The above metrics will provide you insight into the overall team emotions. In addition, it is also important to know the work items that were impacted by the negative emotions of people working on them. There will always be a few work items that generate negative emotions, perhaps causing issues or delays with those work items. There can be several reasons for the negative emotions, such as the Product Owner (PO) not providing a complete spec, disagreements between team members and PO on the scope, dependency on other teams, etc. These could lead to work-item spill-overs across sprints and low productivity which impact the committed PI scope negatively. It could potentially reduce business value delivered to the business in the PI.

To help understand such issues, we provide meaningful insights at the work-items level as well.

Based on the “Circumplex Model” of emotion developed by James Russell, we provide the measure of the valence and arousal of the work items to find the underlying emotions. A sample image of the Valence Arousal Dominance Trend that you will see on each work-item is shown below.

Based on the recent emotions and overall VAD values, there is a Risk Score assigned to each item. This is displayed on work item list view and helps the Manager focus on higher risk items. Shown below is a sample snapshot of the list view.

We hope you find the Team Dynamics capabilities intriguing – enough to connect with us! If you’d like to learn more, just contact us here! Or write a mail to sales@digite.com

SAFe® and Scaled Agile Framework® are registered trademarks of Scaled Agile, Inc.

The post How are your Team Dynamics? (SAFe Implementation powerd by AI!) appeared first on Digité Blog.

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We are back with another release packed with several enhancements in the area of Agile, STaRT, and Mobile App. Filtering cards of different card types on the Execution Board has now become easier through the availability of common and card type specific attributes in the filter panel. Batch Editing of tasks is a breeze with the introduction of column level filters and improved batch edit capability. And you can now update the remaining effort against your Tasks & ToDos via Homepage as well as the Mobile App.

Powerful Filter Panel on Execution Board

Finding relevant cards on the Execution Board becomes easier with the powerful new Filter panel. Now, you can filter cards based on the attributes that are not only common across the card types but also specific to each of the card types on the board.

Define Filters for Your Team

You can now store the filter criteria with a name so that it is available for reuse to you as well as other team members. Similarly, it can be modified and deleted when not required.

Filter Tasks in STaRT Plans

You can now swiftly view as well as update the required set of tasks in your STaRT Task plan with the column based filtering being made available just like it is on workitem list.

Batch Editing of STaRT Tasks made Simpler

It’s now easier to select and edit the multiple tasks in the STaRT Task plan with the help of checkbox and a separate icon to apply the new value provided against the attribute.

Update Remaining Effort for Your Tasks & ToDos

You can now update the Remaining Hours for the Tasks & ToDos via the Time Entry in-line action on your Homepage. This is applicable for Web and Mobile App.

Integration Adaptor Enhancements
  • Unassign resources from a project with the “TeamUnassignmentInt” adaptor.
  • Build master list relationships and modify the parent & child association between the master list values at organization, process template, and project level.
Other Enhancements
  • Field slots preserved for eForm fields when imported afresh.
  • Import Log UI enhanced to show the field slot mismatch warnings if any.
  • Know the changes by viewing Version Difference against the activity log itself.
  • Classification between team members and virtual users in resource group view.
  • Parent details shown on click of workitem ID in Parent column in timesheet view.

Mobile App Enhancements
  • Time Entry grid enhanced to be in-line with timesheet module.
  • Reason for disabled timesheet cell shown by tapping on it.
  • ADFS Authentication is now supported for the Mobile App.

Stay tuned for the webinar.

The post SwiftEnterprise 4.5 is here! appeared first on Digité Blog.

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Digital Transformation (DX) is one of the, if not the, most crucial initiatives that many organizations have undertaken or are taking up. The perfect storm of a wide range of technologies such as SaaS, Mobile, Robotics, IoT (Internet of things), Virtual Reality (VR), etc. is playing a crucial role in the Digital Transformation (DX) of companies. However, it is our belief that Artificial Intelligence (AI) and Machine Learning (ML) will be the key technologies that will propel organizations through the Digital Transformation.

Thinking about Artificial Intelligence (AI) may seem like thinking of a futuristic world akin to those in science fiction movies, but in actuality, the lines between reality and fiction have blurred. AI is changing the world and the lives of people and is becoming the engine of growth of economies and organizations. Whether it is a simple Google Search, a conversation with Amazon Alexa or Google Home or Apple’s Siri, or a simple Chatbot on some website you visited, you may already be interacting with AI/ ML driven tools and – well – bots – in many of your daily activities!  This, without a doubt, is changing the way we perform our daily activities, organize our work, our business and how we take decisions in our everyday lives.

According to International Data Corporation (IDC), by the end of 2018, at least 40% of organizations will have a fully staffed Digital Leadership Team versus a Single DX Executive Lead to accelerate enterprise-wide DX initiatives. And by 2019, 40% of all DX initiatives will be related to AI. By 2020, web interfaces will be quite diversified, with 30% of all web browsing sessions will be done using Augmented Reality (AR) and about 50% of all new mobile applications will have voice as their main interface for people to use them.

The Resurgence of AI

Artificial Intelligence is not something new. To trace the origins of this concept that sounds so innovative, we have to go back to the year 1956. During the summer of 1956, a group of scientists met in the University of Dartmouth, New Hampshire and coined the term ‘Artificial Intelligence (AI)’. These researchers worked for two months with a clear objective: to find a way to introduce the behaviors of human rational logic into machines. 62 years have passed and there has been many investigations, some successes and some failures, in the effort to get machines to think like humans.

Image Source: Nvidia

Interest in AI began to revive in the late 90s when IBM’s Deep Blue Supercomputer defeated the great Russian chess master Gary Kasparov. Kasparov detailed this experience in his book “Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins“.

Deep Blue beat G. Kasparov in 1997 - YouTube

In an interview with PRI.org recently, Kasparov said, “If I had to think whether this was a blessing or a curse that I became world champion when machines were really weak, and I ended my professional career when computers were unbeatable, I think it’s more like a blessing, I was part of something unique.” He says, “The difference today is that machines are going after people with college degrees, political influence and Twitter accounts. But this is normal. Any industry that isn’t under pressure from technology is in stagnation.” Kasparov believes that AI will have a positive impact on society in the coming days.

Since that game between Deep Blue and Kasparov, there have been many technological advancements in AI. One such achievement was the RoboCup (Soccer) in 1997, featuring matches with 40 teams of interacting robots and over 5000 spectators. A group of scientists created Robocup with the intention of using AI and robotics to promote science & technology.

All these advancements and many such developments in AI have led us to develop something extraordinary to aid the humans. In the last 10 years, advances in both computing technology and software, and access to large amounts of data, (thanks to the Internet and SaaS/ Cloud-based systems) are enabling the resurgence of AI. Hardware and software are increasingly powerful, less expensive and easier to access. This allows the processing of large datasets quickly and cost-effectively. The amount of data we produce is expected to double every two years for the next decade, according to InsideBigData. This data is essential to help AI systems learn and make decisions. The more information is available for processing, the more the AI systems can learn and the more accurate their predictions and decisions will be.

But, what is Artificial Intelligence (AI)?

According to Accenture Research, “AI is the collection of multiple technologies that allow machines to detect, understand, act and learn either on their own or to augment human activities”. They will have many of the capabilities of a human being – the ability to learn and distinguish between things.  But they also have a great advantage over humans – they do not need to rest to function! The same Accenture study reveals that AI could double annual economic growth rates by 2035 by changing the nature of work and create a new relationship between Man and Machines, increasing labor productivity by up to 40%.

Artificial Intelligence (AI) is already present in many of the services we use every day, even when we may not be aware of them. For example, when Amazon suggests products you might want to buy, it is using a system based on AI to suggest a product based on your previous purchases and what other people have bought after buying what you are buying (Suggested Products). AI is beginning to mature to the point where it can learn without human interactions.

AI tools are becoming an integral part of many organizations, both in the public and private sectors. It is being applied to help in the improvement of performance of Government agencies, in their service levels and accountability and develop solutions focused on the well-being of Citizens.

Applications of AI in Real World

Artificial Intelligence processes are applied in real systems in a wide variety of sectors. Here are few examples:

  • IT and Security: The most popular use of AI in business lies in these areas. About 44% of 835 companies surveyed by Tata Consultancy Services are already using AI to detect and prevent intrusions. 41% use it to solve technical problems of users, 34% to reduce the workload and automate their processes in the Production area. Gartner predicts that, by 2020, at least 75% of security Software tools will include predictive and prescriptive analytics based on heuristics, AI-based skills, and machine learning algorithms.
  • Customer Service: Companies know how important this area is and how much it can affect the brand. And in-spite of that, sometimes, mistakes are inevitable. The Microsoft State of Global Service 2016, found that 60% of consumers stopped interacting with a company, just because they had a bad experience of customer service. People do not like to wait for hours in the line to be served, tapping numeric keys and being transferred a number of times until they can communicate with the right person. The solution to overcome these issues are “AI Chatbots”. These bots can process and analyze customer information from the first contact point and get them to the right place much faster. Data collected from their interactions provide you with useful perspectives on how to serve your customers.
  • Business Operations and Decision Support: AI can help many activities related to the running of a business, such as scheduling conferences, team meetings and business trips. Very soon, AI will be able to aid us in decision making. IBM estimates that by 2025, data-based decision making tools market will be $2 trillion.
  • Finance and Accounting: Accenture predicts that 80% of finance and accounting tasks will be automated in the coming years.
  • Human Resources: This is another area where AI will be able to aid businesses. Artificial Intelligence can help streamline many of the HR processes. There are many ways of applying AI to the processes such as hiring, prepare interview schedules, filtering candidates or finding the most appropriate profiles for the positions that are offered etc. In a recent article published on Forbes, Jeanne Meister states that “HR leaders need to experiment with all facets of AI to deliver value to their organization.”

So, what implications does AI bring to the Workplace?

Can you imagine arriving at your office desk and a machine lists out your tasks and meetings for the day? Well, that’s where technology is taking us with this fourth industrial revolution, led by Digital Transformation (DX).

While Artificial Intelligence, automation and Machine Learning break barriers in all industries, businesses will have to embrace these technologies and understand that they are a source of multiple benefits. As AI becomes an integral part of work processes, the overall benefits will become clearer. By automating tasks, companies will be able to free human capital to focus on more interesting aspects of the projects. Implementing smarter and more compatible business processes with AI will allow humans to focus on more important challenging and creative aspects. Highly qualified people are the backbone of any organization and reducing their time in repetitive/ mundane work can be achieved through the implementation of AI-processes.

Giants like Google, Microsoft, Facebook, Amazon etc. are investing 100s of millions of dollars in the development of Artificial Intelligence solutions.  To showcase what’s coming, Google recently unveiled a virtual assistant called Duplex which can talk/ act like a real human and help you get your daily chores done.

Google’s Duplex Assistant phone call blew my mind! - YouTube

In the work environment, AI will allow us to work more efficiently, reduce human errors, and automate processes with the help of assisted intelligence, such as Chatbots and Natural Language Processing (NLP) tools that can simulate human conversation, answer questions or personalize learning experiences.

Artificial intelligence (AI) is increasingly being embedded into the day-to-day lives of everyone, not just in the personal sphere, but also in corporate/ business decision-making across the enterprise.

Here are some practical applications of AI that have already been implemented successfully in many SMEs (Small and Medium Enterprises)

Source: TCS & HBR 

By 2020, human-digital interfaces will be diversified, with 25% of the technical teams using augmented reality and about 50% of new mobile applications will have voice as the main interface. Companies are implementing AI for a variety of business drivers. Here are the latest findings from McKinsey’s analysis of 400 use cases on AI across 19 industries:

Source: McKinsey

What’s Ahead?

The predictions made by IDC clearly suggest that Digital Transformation (DX) with the help of AI is the way to move forward. This creates an urgency to redefine a new AI-based operating model, organizational structure, roles and communication strategy to manage change effectively. In 2019, 40% of all Digital Transformation (DX) initiatives and 100% of all effective IoT efforts will be supported by AI capabilities. This is because the data that comes from IoT devices and DX initiatives will have limited value without Artificial Intelligence technologies that are able to find valuable information from the data.

To respond to the challenges of the DX economy, companies will have to grow their AI/ ML teams faster. Artificial Intelligence involves teams with synchronous communications, process automation and advanced analytics, so professional profiles are required in each of these fields, which are combinations of knowledge of Telecommunications, Computer Science, Mathematics, Statistics and Engineering. (Roles of AI teams) If you are a company that is considering implementing AI technology, it is advisable to start as soon as possible prepare the processes of your company for the correct exploitation of AI models.

How is Digité preparing for the Artificial Intelligence/ Machine Learning Challenge?

We, at Digite, are always looking out for ways to improve our product that can make a positive impact to our end user.  Our tag-line ‘How work Really gets done!” says it all!

We have been at the forefront of helping knowledge teams in IT, software and a variety of business functions, such as Marketing, HR, Procurement and others, work more effectively, collaborate contextually and make decisions easily by providing them the right project information at the right time, in the context of what they are doing.

As outlined above, we believe AI and ML will have – in fact, are already having – a profound effect on how people work, collaborate and deliver on their customer commitments. Assisted by Artificial Intelligence, Machine Learning and Big-Data technologies, they will be able to deliver more creative and innovative solutions to their customers.  Thanks to the vast amounts of enterprise-wide project delivery data collected over the past decade or more, we believe AI/ ML tools and techniques will help them detect project risks faster, perform what-if analysis much wider and deeper and make recommendations for corrective actions in a much more impactful manner than ever before. Our cognitive technologies will help business leaders get deeper and faster insights into how their people are performing and how satisfied their customers are with their performance, and proactively support them in areas where they might need help.

We are building and launching a range of embedded AI tools and related services to our customers.  AI-driven Enterprise Agility for successful Digital Transformation – that is our mantra. Our AI/ ML tools and services will help in Predictive planning, development, testing and operations. Our products – SwiftEnterprise, SwiftKanban and SwiftEASe will power the next generation AI-driven Enterprise Agility platform to accelerate our customers’ Digital Transformation (DX) initiatives. Connect with us to learn more about how we can help your AI/ ML and DX initiatives with our products and consulting services.

In Summary

Artificial Intelligence (AI) is here to stay and is leading an industrial revolution to make organizations more competitive and efficient. AI has already become a strategic factor to generate sustained growth and provide a competitive advantage to organizations. The challenge for all of us is how we manage the changes needed in organization structure, management culture and the investment needed in the development of skills so that the workforce has the capability to adapt to this global trend that we already find in our professional and personal lives.

If you need any help with your Digital Transformation (DX) initiatives, our specialists are just an email away! Get in touch (sales@digite.com) with us and see how we can help you Digitally transform your enterprise.

The post Digital Transformation & Artificial Intelligence: Is your Organization ready? appeared first on Digité Blog.

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Digital Transformation (DX) is one of the, if not the, most crucial initiatives that many organizations have undertaken or are taking up. The perfect storm of a wide range of technologies such as SaaS, Mobile, Robotics, IoT (Internet of things), Virtual Reality (VR), etc. is playing a crucial role in the Digital Transformation (DX) of companies. However, it is our belief that Artificial Intelligence (AI) and Machine Learning (ML) will be the key technologies that will propel organizations through the Digital Transformation.

Thinking about Artificial Intelligence (AI) may seem like thinking of a futuristic world akin to those in science fiction movies, but in actuality, the lines between reality and fiction have blurred. AI is changing the world and the lives of people and is becoming the engine of growth of economies and organizations. Whether it is a simple Google Search, a conversation with Amazon Alexa or Google Home or Apple’s Siri, or a simple Chatbot on some website you visited, you may already be interacting with AI/ ML driven tools and – well – bots – in many of your daily activities!  This, without a doubt, is changing the way we perform our daily activities, organize our work, our business and how we take decisions in our everyday lives.

According to International Data Corporation (IDC), by the end of 2018, at least 40% of organizations will have a fully staffed Digital Leadership Team versus a Single DX Executive Lead to accelerate enterprise-wide DX initiatives. And by 2019, 40% of all DX initiatives will be related to AI. By 2020, web interfaces will be quite diversified, with 30% of all web browsing sessions will be done using Augmented Reality (AR) and about 50% of all new mobile applications will have voice as their main interface for people to use them.

The Resurgence of AI

Artificial Intelligence is not something new. To trace the origins of this concept that sounds so innovative, we have to go back to the year 1956. During the summer of 1956, a group of scientists met in the University of Dartmouth, New Hampshire and coined the term ‘Artificial Intelligence (AI)’. These researchers worked for two months with a clear objective: to find a way to introduce the behaviors of human rational logic into machines. 62 years have passed and there has been many investigations, some successes and some failures, in the effort to get machines to think like humans.

Image Source: Nvidia

Interest in AI began to revive in the late 90s when IBM’s Deep Blue Supercomputer defeated the great Russian chess master Gary Kasparov. Kasparov detailed this experience in his book “Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins“.

Deep Blue beat G. Kasparov in 1997 - YouTube

In an interview with PRI.org recently, Kasparov said, “If I had to think whether this was a blessing or a curse that I became world champion when machines were really weak, and I ended my professional career when computers were unbeatable, I think it’s more like a blessing, I was part of something unique.” He says, “The difference today is that machines are going after people with college degrees, political influence and Twitter accounts. But this is normal. Any industry that isn’t under pressure from technology is in stagnation.” Kasparov believes that AI will have a positive impact on society in the coming days.

Since that game between Deep Blue and Kasparov, there have been many technological advancements in AI. One such achievement was the RoboCup (Soccer) in 1997, featuring matches with 40 teams of interacting robots and over 5000 spectators. A group of scientists created Robocup with the intention of using AI and robotics to promote science & technology.

All these advancements and many such developments in AI have led us to develop something extraordinary to aid the humans. In the last 10 years, advances in both computing technology and software, and access to large amounts of data, (thanks to the Internet and SaaS/ Cloud-based systems) are enabling the resurgence of AI. Hardware and software are increasingly powerful, less expensive and easier to access. This allows the processing of large datasets quickly and cost-effectively. The amount of data we produce is expected to double every two years for the next decade, according to InsideBigData. This data is essential to help AI systems learn and make decisions. The more information is available for processing, the more the AI systems can learn and the more accurate their predictions and decisions will be.

But, what is Artificial Intelligence (AI)?

According to Accenture Research, “AI is the collection of multiple technologies that allow machines to detect, understand, act and learn either on their own or to augment human activities”. They will have many of the capabilities of a human being – the ability to learn and distinguish between things.  But they also have a great advantage over humans – they do not need to rest to function! The same Accenture study reveals that AI could double annual economic growth rates by 2035 by changing the nature of work and create a new relationship between Man and Machines, increasing labor productivity by up to 40%.

Artificial Intelligence (AI) is already present in many of the services we use every day, even when we may not be aware of them. For example, when Amazon suggests products you might want to buy, it is using a system based on AI to suggest a product based on your previous purchases and what other people have bought after buying what you are buying (Suggested Products). AI is beginning to mature to the point where it can learn without human interactions.

AI tools are becoming an integral part of many organizations, both in the public and private sectors. It is being applied to help in the improvement of performance of Government agencies, in their service levels and accountability and develop solutions focused on the well-being of Citizens.

Applications of AI in Real World

Artificial Intelligence processes are applied in real systems in a wide variety of sectors. Here are few examples:

  • IT and Security: The most popular use of AI in business lies in these areas. About 44% of 835 companies surveyed by Tata Consultancy Services are already using AI to detect and prevent intrusions. 41% use it to solve technical problems of users, 34% to reduce the workload and automate their processes in the Production area. Gartner predicts that, by 2020, at least 75% of security Software tools will include predictive and prescriptive analytics based on heuristics, AI-based skills, and machine learning algorithms.
  • Customer Service: Companies know how important this area is and how much it can affect the brand. And in-spite of that, sometimes, mistakes are inevitable. The Microsoft State of Global Service 2016, found that 60% of consumers stopped interacting with a company, just because they had a bad experience of customer service. People do not like to wait for hours in the line to be served, tapping numeric keys and being transferred a number of times until they can communicate with the right person. The solution to overcome these issues are “AI Chatbots”. These bots can process and analyze customer information from the first contact point and get them to the right place much faster. Data collected from their interactions provide you with useful perspectives on how to serve your customers.
  • Business Operations and Decision Support: AI can help many activities related to the running of a business, such as scheduling conferences, team meetings and business trips. Very soon, AI will be able to aid us in decision making. IBM estimates that by 2025, data-based decision making tools market will be $2 trillion.
  • Finance and Accounting: Accenture predicts that 80% of finance and accounting tasks will be automated in the coming years.
  • Human Resources: This is another area where AI will be able to aid businesses. Artificial Intelligence can help streamline many of the HR processes. There are many ways of applying AI to the processes such as hiring, prepare interview schedules, filtering candidates or finding the most appropriate profiles for the positions that are offered etc. In a recent article published on Forbes, Jeanne Meister states that “HR leaders need to experiment with all facets of AI to deliver value to their organization.”

So, what implications does AI bring to the Workplace?

Can you imagine arriving at your office desk and a machine lists out your tasks and meetings for the day? Well, that’s where technology is taking us with this fourth industrial revolution, led by Digital Transformation (DX).

While Artificial Intelligence, automation and Machine Learning break barriers in all industries, businesses will have to embrace these technologies and understand that they are a source of multiple benefits. As AI becomes an integral part of work processes, the overall benefits will become clearer. By automating tasks, companies will be able to free human capital to focus on more interesting aspects of the projects. Implementing smarter and more compatible business processes with AI will allow humans to focus on more important challenging and creative aspects. Highly qualified people are the backbone of any organization and reducing their time in repetitive/ mundane work can be achieved through the implementation of AI-processes.

Giants like Google, Microsoft, Facebook, Amazon etc. are investing 100s of millions of dollars in the development of Artificial Intelligence solutions.  To showcase what’s coming, Google recently unveiled a virtual assistant called Duplex which can talk/ act like a real human and help you get your daily chores done.

Google’s Duplex Assistant phone call blew my mind! - YouTube

In the work environment, AI will allow us to work more efficiently, reduce human errors, and automate processes with the help of assisted intelligence, such as Chatbots and Natural Language Processing (NLP) tools that can simulate human conversation, answer questions or personalize learning experiences.

Artificial intelligence (AI) is increasingly being embedded into the day-to-day lives of everyone, not just in the personal sphere, but also in corporate/ business decision-making across the enterprise.

Here are some practical applications of AI that have already been implemented successfully in many SMEs (Small and Medium Enterprises)

Source: TCS & HBR 

By 2020, human-digital interfaces will be diversified, with 25% of the technical teams using augmented reality and about 50% of new mobile applications will have voice as the main interface. Companies are implementing AI for a variety of business drivers. Here are the latest findings from McKinsey’s analysis of 400 use cases on AI across 19 industries:

Source: McKinsey

What’s Ahead?

The predictions made by IDC clearly suggest that Digital Transformation (DX) with the help of AI is the way to move forward. This creates an urgency to redefine a new AI-based operating model, organizational structure, roles and communication strategy to manage change effectively. In 2019, 40% of all Digital Transformation (DX) initiatives and 100% of all effective IoT efforts will be supported by AI capabilities. This is because the data that comes from IoT devices and DX initiatives will have limited value without Artificial Intelligence technologies that are able to find valuable information from the data.

To respond to the challenges of the DX economy, companies will have to grow their AI/ ML teams faster. Artificial Intelligence involves teams with synchronous communications, process automation and advanced analytics, so professional profiles are required in each of these fields, which are combinations of knowledge of Telecommunications, Computer Science, Mathematics, Statistics and Engineering. (Roles of AI teams) If you are a company that is considering implementing AI technology, it is advisable to start as soon as possible prepare the processes of your company for the correct exploitation of AI models.

How is Digité preparing for the Artificial Intelligence/ Machine Learning Challenge?

We, at Digite, are always looking out for ways to improve our product that can make a positive impact to our end user.  Our tag-line ‘How work Really gets done!” says it all!

We have been at the forefront of helping knowledge teams in IT, software and a variety of business functions, such as Marketing, HR, Procurement and others, work more effectively, collaborate contextually and make decisions easily by providing them the right project information at the right time, in the context of what they are doing.

As outlined above, we believe AI and ML will have – in fact, are already having – a profound effect on how people work, collaborate and deliver on their customer commitments. Assisted by Artificial Intelligence, Machine Learning and Big-Data technologies, they will be able to deliver more creative and innovative solutions to their customers.  Thanks to the vast amounts of enterprise-wide project delivery data collected over the past decade or more, we believe AI/ ML tools and techniques will help them detect project risks faster, perform what-if analysis much wider and deeper and make recommendations for corrective actions in a much more impactful manner than ever before. Our cognitive technologies will help business leaders get deeper and faster insights into how their people are performing and how satisfied their customers are with their performance, and proactively support them in areas where they might need help.

We are building and launching a range of embedded AI tools and related services to our customers.  AI-driven Enterprise Agility for successful Digital Transformation – that is our mantra. Our AI/ ML tools and services will help in Predictive planning, development, testing and operations. Our products – SwiftEnterprise, SwiftKanban and SwiftEASe will power the next generation AI-driven Enterprise Agility platform to accelerate our customers’ Digital Transformation (DX) initiatives. Connect with us to learn more about how we can help your AI/ ML and DX initiatives with our products and consulting services.

In Summary

Artificial Intelligence (AI) is here to stay and is leading an industrial revolution to make organizations more competitive and efficient. AI has already become a strategic factor to generate sustained growth and provide a competitive advantage to organizations. The challenge for all of us is how we manage the changes needed in organization structure, management culture and the investment needed in the development of skills so that the workforce has the capability to adapt to this global trend that we already find in our professional and personal lives.

If you need any help with your Digital Transformation (DX) initiatives, our specialists are just an email away! Get in touch (sales@digite.com) with us and see how we can help you Digitally transform your enterprise.

The post Digital Transformation & Artificial Intelligence: Is your Organization ready? appeared first on Digité Blog.

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This release brings you key usability enhancements in the area of Agile, Dashboard, and Mobile App. You can now assess the impact of the changing team size on the work completed in the sprints with the enhanced Sprint Velocity widget. For the work getting spilled over from the current sprint, you can create a card easily from the Execution Board itself. And you can now update your profile picture even from the Mobile App. Along with these, there are several other enhancements that make working on the dashboard, execution board and application in general whole lot easier.

See the Impact of Varying Team Size on Sprint Velocity

When your team size varies from sprint to sprint it becomes important to know how it is impacting your overall sprint velocity. To understand this, we now have an option to see the team size (as line graph) in the context of the sum of story points delivered each sprint (as bar graph). This gives additional dimension to assess the sprint velocity better.

Other Dashboard Enhancements

  • Export all widgets on the Dashboard page in Excel, Word, or PDF file.
  • Chose data label as Percentage, Value or both to be shown in the Pie Chart.
  • Track the Burndown Chart for a Sprint/Release in an Agile project’s dashboard.
Add Card for Spillover Work

The new “Add Spillover Card” option on the card not just copies the card details but lets you copy other data like Open ToDos, Attachments and Comments from the original card. Most importantly, it allows you to revise the Estimate of the original card and provide the Estimate for the remainder work on the new card.

Other Execution Board Enhancements

  • Copy an existing card to get a new card with same details.
  • Flag icons settings now available in the eForm configuration export.
Update Your Profile Picture from Mobile App

Now you can update profile picture for your account from the Mobile App. Select a photo from your mobile’s photo gallery or take a new one using your mobile.

Other Enhancements
  • New optional parameter in WORKFLOWSTAGEACTOR function to handle workflow member with timelogs.
  • Get action (A, M, C, or AC) from GETEVENTDETAILS ECR function upon XLS import of workitem(s).
  • Search Bar is now available up front and the last 10 searches are displayed on click.
  • Search for the required values in eForm column listing filter.
  • Singapore Dollar now supported for currency field type.

The post SwiftEnterprise 4.3 is Here! appeared first on Digité Blog.

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This release brings to you whole lot of usability improvements in the area of Agile, STaRT, Dashboard and Mobile App. Now, you have a visual Card Designer to define the attributes and new action icons that should be visible on the card on Execution board. Planning your tasks using STaRT Task plans has become easier with several improvements in copy/paste of tasks and bulk assignment functionality. In the Dashboard, you can copy a widget and move a widget to a different page from the re-organized contextual actions on the widget. And you now have the new timesheet module on the Mobile App so that you can log time across multiple work items and then route the timesheet for approval.

Visual Card Designer

Use the new Visual Card Designer to select the attributes and action icons to be displayed on the card for each workitem type on the Execution Board.

Gather Votes on Cards

You can now choose to gather votes on cards through the new Vote icon. The Votes field on the workitem also keeps track of the number of votes.

Highlight Cards that Need Attention

You can now choose to highlight a concern on a card by flagging it with a comment. Similarly, you can unflag it once it is resolved.

Other Agile Usability Enhancements
  • Copy an existing lane to get the same column structure easily.
  • Log time across weeks from the Time Entry option in ToDos segment.
  • Hover on the Traceability icon to know the type of workitems linked to it.

Intermediate Save for STaRT Task Plans

Earlier, the Save button on STaRT Task plan used to save as well as checkin the task plan. Now, the Save button acts as an intermediate save so that PM can decide to checkin the plan at a later stage once he is done making all the changes. Also, for better understanding, we have provided a new button ‘Checkin’ and renamed the buttons ‘Edit’ to ‘Checkout’ and ‘Undo’ to ‘Revert’.

Batch Assignment of Resources Simplified

The batch assign window for STaRT task plan shows the assigned resources on top with respective checkbox selected. Also, the selection of checkbox against the resource decides if they should be assigned or removed from the selected tasks. Perform both these actions by using the single Apply button.

Other STaRT Usability Enhancements
  • Copy multiple tasks and paste them multiple times.
  • Copied task get pasted as a sibling task below the selected task.
  • Copy/paste resources from one task to another using Ctrl+C and Ctrl+V.

Copy or Move a Widget Easily

You no longer have to reconfigure a widget from scratch to replicate it on the same or another dashboard page. The new Copy Widget and Move Widget actions help you get that done easily and quickly. The contextual actions on the widget have also been re-organized so that the primary actions are seen upfront and rest are made available under the More menu to avoid the clutter.

Add or Edit Item Filters from Widget Settings

You can now add or edit Global item filters from Item Status widget’s settings page in the Dashboard itself without navigating to the workitem’s listing page.

Mobile App Enhancements

Update Time Across Workitems and Route Timesheet for Approval

Timesheet module is now available in the Mobile App. On the top, the summary view presents the total hours logged across workitems of multiple projects followed by the list of workitems. Once you are done updating time logs across the required workitems for a week, you can route the timesheet for approval.

Change Theme

Now you can update the application’s theme from the mobile app’s drawer menu. The chosen theme is reflected in your web application account also.

Other Enhancements
  • SwiftEnterprise now supports the SVN 3.8 version.
  • Rename the file used to import the workitems as per your need.
  • View the details directly when you tap on workitem on Mobile App.
  • Field slots preserved for ECR table’s column when imported afresh.
  • Matching search keywords shown as per your last 10 global searches.
  • New master list that displays team member’s name along with Login Id.

Stay tuned for the webinar.

The post SwiftEnterprise 4.2 is here! appeared first on Digité Blog.

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We’re honored to republish this blog post ‘Beginner’s Guide to Kanban for Agile Marketing’ by Andrea Fryrear which was originally published in the Agile Sherpas blog! In this article, Andrea explains the Kanban method in detail starting from its origin to its principles and its application. She also shows you how to design your first Kanban Board, with examples. Shows how a marketing team can benefit by Visualizing work on a Kanban Board!

At the core of Kanban lies a paradox: by limiting the amount of work we do, we become more productive.

When you consider how much time we lose to multitasking (or, more accurately, task switching, since no one can truly multitask), you can see why this seemingly paradoxical methodology is so useful.

Compared to Scrum, Kanban is a young work-management method.

David J. Anderson best articulated its application to software development, in 2013, in the foundational book Kanban: Successful Evolutionary Change for Your Technology Business, and its adoption hasn’t been as universal as Scrum’s during the early days of Agile software development. But, for teams that chafe under the strictures of the Scrum process, Kanban can be a freeing alternative.

Origins of Kanban

Although it was adapted to knowledge work only a few years ago, the concept of kanban (lower case k) has been around for decades.

The Japanese term “kanban” translates to “signal card,” and was originally developed by Toyota in the 1940s. Inspired by grocery stores, which stock only as much product as people need, Toyota’s manufacturing teams began using cards, or kanbans, to signal to other parts of the production line that they needed more parts.

The use of kanban was part of a JIT (Just in Time) approach that enabled plants to create only as many parts as were needed at the time, and to conserve resources by not making extra.

Avoiding Waste on the Assembly Line

Let’s say my job is to put tires on a car. It’s wasteful for me to have hundreds of tires that I don’t yet need piled up behind me.

It’s efficient for the team that makes tires to produce them just in time for me to install them on a car. So once my stock reaches an agreed-upon point, say a dozen tires on hand, I put out a kanban card to spur the tire-making team to action. Throughout the assembly line, “workers at each step in the process are not allowed to do work unless they are signaled with a kanban from a downstream step.”

When applied to software development and marketing, a Kanban implementation doesn’t typically include physical signal cards that cause another worker to begin work.

Instead, the signal to pull new work is inferred from the visual quantity of work-in-progress in any given state.

For example, if I’m responsible for editing content on my marketing team, I infer from the amount of work in the “Edit ready” column that it is or isn’t time to pull a new project into my own workload. (This assumes that the number of items in progress in the “editing” column falls below the set WIP limit, enabling me to pull in additional work; more on that shortly.)

Image Credits: AgileSherpas Kanban vs. kanban

Like Scrum, a Kanban implementation requires a prioritized Backlog of work-to-be-done, from which the team pull their work.

Business owners and stakeholders are responsible for religiously maintaining and prioritizing that list, because it is the sole source of work for the marketing team.

You’ve probably seen kanban tracking boards used on all kinds of teams, but simply having a Backlog and moving work from one side of a whiteboard to another doesn’t mean you’re using Kanban. Anderson reminds us that “card walls are not inherently kanban systems. They are merely visual control systems. They allow teams to visually observe work-in-progress and self-organize, assign their own tasks, and move work from a backlog to complete without direction from a project or line manager.

However, if there is no explicit limit to work-in-progress and no signaling to pull new work through the system, it is not a kanban system.”

So, putting a bunch of cards on a wall doesn’t mean you’re using Kanban.

In fact, many Scrum teams use this type of visualization to manage their work. The primary piece that sets Kanban apart is the commitment to limiting work-in-progress (WIP).

The Cool Power of WIP Limits

Instead of using timeboxes to govern their work, as a Scrum team does, a Kanban team uses WIP limits. Each state of work has an upper limit of productive work that it can contain.

After the team exceeds that limit, waste enters the system. That upper limit then becomes a formalized piece of the Kanban process.

WIP limits vary from team to team and from one state of work to another.

For example, your team of 5 might have a WIP limit of 10 on their “Doing” column, enabling each person to work on 2 things at once. The limit on work being reviewed, however, might be different, depending on how long this piece of the workflow takes, how many people are assigned to review work, and other factors.

Routinely experiment with your WIP limits and document the outcomes, to ensure that your Kanban system functions at its highest possible level.

Five Core Properties of Kanban

WIP limits may be Kanban’s core defining feature, but it’s not all you need. Anderson defines five core properties that make for a successful implementation:

  1. Visualize Workflow
  2. Limit Work-in-Progress
  3. Measure and Manage Flow
  4. Make Process Policies Explicit
  5. Use Models to Recognize Improvement Opportunities

Unlike Scrum, Kanban doesn’t prescribe a way of managing work; it doesn’t dictate regular meetings or create unique roles within the team.

Kanban assumes that you already have some form of work-management process in place, and that you want to continuously improve it. This makes Kanban easier than Scrum for marketing teams to implement, because you can start Kanban with little educational overhead.

Kanban also adapts readily to changing contexts. No two teams — even within the same department — implement it in exactly the same way. This makes sense: the bottlenecks in each team’s workflow are distinct, so each team’s improvement strategy is distinct. For Anderson, this approach is freeing:

Kanban is giving permission in the market to create a tailored process optimized to a specific context. Kanban is giving people permission to think for themselves…You have permission to try Kanban. You have permission to modify your process. You have permission to be different. Your situation is unique and you deserve to develop a unique process definition tailored and optimized to your domain, your value stream, the risks that you manage, the skills of your team, and the demands of your customers.

If you’re new to Agility and aren’t yet ready to think for yourself, this may sound terrifying rather than freeing; you might start with a Scrum implementation before moving toward Kanban.

Visualizing Flow with Your Kanban Board

The first rule of your first Kanban board is that it reflect reality rather than the official or ideal process for completing work on your marketing team.

Your first task is to identify the start and end points for your team. Where do you take over complete control of work, and where do you hand it off to another team or department? These mark the beginning and end of your workflow visualization.

Next, fill in what happens on the team between those two points.

One way to visualize how work makes its way through the team:

think of any significant gates or gatekeepers in your workflow — such as approvals, reviews, handoffs from one person to another, or releases out into the world — and use those to define the columns of your board. Another approach is to think of parts of your workflow that have limits as to how many tasks can be in the same stage at the same time before your effectiveness in getting them all done begins to degrade.

At its simplest, a marketing Kanban board can start with five columns: To Do, Create, Review, Test, and Done.

A content team might start with one like this:

Image Credits: AgileSherpas Creating Your First Kanban Board

You may find it useful to sketch the flow organically, without trying to fit it into the vertical column view, before translating it into this format.

The first few weeks are likely to see lots of changes to your board layout, so don’t stress about getting it perfect the first time. Use a format that can easily be changed, such as dry-erase markers and sticky notes on a whiteboard.

Once you’re confident that the flow reflects your team’s flow, you can create a more permanent version with tape or software.

Depending on the type of work that your team typically does, columns just for work that has left one state and is waiting to be pulled into the next may be useful. Known as buffers, these columns can help some teams visualize bottlenecks.

Image Credits: AgileSherpas

This sample content marketing board, for example, includes columns for content that is ready to be reviewed and ready to be published.

When first setting up your Kanban board, don’t be too restrictive with the WIP limits you place on each column; make them a little higher than you need. Your workflow will be plagued by variability, waste, and bottlenecks early on, and you don’t want those problems to interfere with the introduction of a pull-based mentality.

As opportunities for improvement become clear, you can reduce WIP limits and add buffers accordingly.

Daily Standups and After Meetings

The daily standup meeting is an integral part of Kanban just as it is in Scrum, but the format deviates slightly.

The Kanban board accurately representation of all work in progress eliminates the need for team members to give daily status updates. Instead, the meeting centers on how work is flowing (or not flowing) through the system. A facilitator of some kind walks the board, usually from right to left, reviewing the cards and, when a need arises, querying team members for a status update or information that the team does not already have.

A Kanban standup focuses on blocked items (a status that indicated on the card with a flag) or on cards that haven’t changed status in several days.

This condensed style of standup is one reason that Kanban teams can be considerably larger than Scrum teams. Teams as large as 50 can complete these kinds of standups in under 15 minutes, a rate not feasible using the Scrum standup format.

Many Kanban teams also engage in what’s known as an After Meeting, an informal gathering of team members who are collaborating on their own projects.

Anderson reports that this ceremony “emerged as spontaneous behavior because team members wanted to discuss something on their minds: perhaps a blocking issue, perhaps a technical design or architecture issue, but more often, a process-related issue.” As a result, After Meetings tend to be fertile ground for ideas to improve the process and generate innovations.

Replenishing the Kanban Queue

In place of Review and Retrospectives, Kanban teams use queue-replenishment meetings to keep their backlog prioritized and refined. They must happen at regular intervals, but their cadence doesn’t need to be tied to any other cycle of Kanban.

So, even if you release new content every week, your queue replenishment might need to occur only once a month. Whatever timing you choose, make sure that it’s consistent, because “a steady cadence for queue replenishment reduces the coordination cost of holding the meeting and provides certainty and reliability over the relationship between the business” and the marketing team.

Whenever possible, include a wide variety of decision makers from the most-senior management position available in queue replenishment.

These attendees can often provide more contextual detail and make decisions where lower-level attendees would have to defer. The goal is to produce a Backlog from which the marketing team can work with the utmost confidence, so you need attendees that can make that happen during the meeting.

6 Steps for Succeeding With Kanban

If you choose Kanban as your first Agile marketing methodology, keep in mind that the “essence of starting with Kanban is to change as little as possible,” and that you want to map your existing workflow and processes before you begin the ongoing improvement efforts.

This recipe for success comes from David Anderson, who crafted it based on his experience as a new manager adopting an existing team. For marketing teams looking to adopt this methodology, these steps serve you equally well:

1. Focus on Quality: Anderson focused on this step first to cut down on the amount of time a development team spends on dealing with software defects; marketers would do well to start here too. Without a commitment to producing the highest possible quality of marketing work, it doesn’t really matter if you can enhance your productivity.

2.  Reduce Work-in-Progress: There is a direct correlation between a lower WIP limit and an increase in quality, so this second step must be implemented along with, or immediately after, Step 1. Reducing the amount of work that the team and its members do at any given time lowers the time it takes to complete work and improves its quality. Keep your WIP as low as possible. Period.

3. Deliver Often: Frequent releases of content, email, social-media posts, and pretty much any other marketing collateral that you can think of builds trust with audiences and stakeholders. They also increase the number of learning opportunities for your Agile team.

4. Balance Demand Against Throughput: In this step you’re focused on finding a rate for accepting new work into the marketing Backlog that corresponds with the rate you can deliver high-quality marketing work. This is effectively limiting the WIP for your Backlog, and it means that discussions about priorities and commitments to completing new work can happen only after some work has been released. This balance produces some slack in the team’s capacity; only those working in the bottleneck areas are constantly busy, and even they must not be given cause to feel overwhelmed. Slack is powerful, because it enables team members to focus on doing their jobs with precision and quality and gives them time to apply themselves to improving the team and its workflow. This step can be difficult, because we tend to want to optimize our workflow to use up everyone’s available time; but Kanban’s continuous improvement demands a system with some slack, which can only be achieved by balancing demand against throughput.

5. Prioritize: When you have no predictability in your team, prioritization doesn’t much matter, which is why it’s down here at Step 5. But when high-quality work is going out steadily and the team has some slack in their days, management can begin to ensure that the most valuable work is being done. Additionally, for marketing teams that lack political capital in an organization, building up confidence by showing an improved workflow may need to precede any attempt to change strategy or priorities.

6. Attack Sources of Variability to Improve Predictability: Variability is undesirable because it results in more WIP and longer release cycles. But understanding its effects and how to reduce it are advanced and difficult topics. When you’ve reached a high level of Agile maturity, you can tackle this final step by experimenting with your existing process policies.

Discovering the Agile System That’s Right For Your Team

Teams who don’t take well to the rigidity of Scrum may find freedom in a Kanban system, while those who need additional insulation from upper management may need the buffer of a Scrum Master and Product Owner.

For teams completely unused to agile methodologies, the ritual and constancy of Scrum may offer them a sense of security. Kanban is more often adopted when Scrum begins to break down, and so may be a good second iteration of agile marketing for some teams.

The important thing is not to try and force your marketing team into a system that isn’t right for them.

Agile is about constant improvement, and that goes for your processes as well as your products.

The post Beginner’s Guide to Kanban for Agile Marketing appeared first on Digité Blog.

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SwiftKanban 5.0 comes with a host of new features and key enhancements.

Here are the highlights:

Dependency Board

Leverage the newly introduced Dependency Board to keep track of the important workitems that are dependent on each other for completion and need to be executed in a synchronized manner. To know more click here

Toolbar Pinned on the Kanban Board

Now, you don’t need to hide or unhide the toolbar to get a clear view of the Kanban Board. The toolbar has been permanently pinned on the left side and the Kanban board starts after the toolbar.
Note: The toolbar for the other pages, will be pinned in the future releases.

Notification on Card Edit

We have enhanced the Notification feature so that you get notified even when the value of the custom fields in cards gets modified. You can enable such notification for the Board-wise, Lane-wise, and Team-wise event.

Facilitate a Focussed View of Kanban Board

As a Manager, you can let your team members have a focussed view of the work by deploying a specific Filter on their Board. Once you publish and share a Filter with the selected resources, they will get to see only those cards matching with the Filter criteria.

 Other Enhancements
  • Now, we have an alternative way of assigning a card to the user. Just right-click it, then click the Assign Card option and select the user.
  • Import Cards with Card Hierarchy option has now moved inside the Card Import wizard.
  • The notification mail that you receive while Importing or Exporting Board will now have detailed information of what all will be imported or exported.
  • The Analytics will now consider a card as complete when it is archived or moved to or beyond the Done column type.
  • The Column wise Average Cycle time Analysis has now been renamed to the Lanewise Average Cycle time Analysis.

We hope you like these improvements! As always, your feedback and suggestions are invaluable to us. Please share your thoughts in the comment section below.

The post SwiftKanban 5.0 is Here appeared first on Digité Blog.

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