#digite

What is Business Agility? Business agility is a management approach that empowers organizations to develop, succeed, and prosper by responding quickly to changes and opportunities with innovative and streamlined processes. Agile originated in IT, where organizations use it to break big projects into smaller chunks, ensuring faster and more sustainable software delivery. Slowly, it gained popularity outside of IT, particularly in marketing where the same principles have been adapted to fit the needs of that field. Now, there’s a trend of Agile spreading to adjacent departments such as sales, finance, and HR. The 5th State of Agile Marketing Report reveals that 33% of sales teams use Agile practices, followed by 20% in finance, and 16% in HR. This is driven by a key fact uncovered in the same report: Agile teams overwhelmingly prefer working with other Agile teams. In other words, the more Agile the organization, the merrier the teams within it. Agility empowers individuals, teams, and companies to innovate, experiment, satisfy customers’ changing needs, and adapt to market shifts. As a result, organizations can stay competitive and relevant by streamlining their processes, emphasizing frequent delivery using fewer resources, being adaptive, and focusing on the value they provide. How to Have a Successful Business Agility Transformation? No matter the industry you’re in, Agile is likely to become a bigger part of what you do in the near future. So, to get yourself prepared, here are six things you can do now to start embracing the Agile mindset. 1. Create Self-Organizing Teams 2. Flatten the Hierarchy 3. Build a Queue 4. Visualize the Work 5. Limit Work in Progress 6. Establish a culture of continuous improvement

Like in much of life, there is a serious paradox tearing at the very heart of teamwork. In today’s Volatile, Uncertain, Complex and Ambiguous business world (VUCA for short), being an Agile business is not an option but an existential necessity. In this backdrop, when we look at work in teams and organizations, especially knowledge work, the divide between methods, versus flexibility, is as paradoxical as day and night. This is especially a challenge for large, established and successful companies. Policies and Autonomy – Uncomfortable Bed Fellows? Let us look at some implicit assumptions about rules and policies in an organization. For one, it dumbs down the ability of the individual employee and downgrades/ degrades her identity. For example, we could argue that by having an HR policy for leave or work place/ hours, you have implicitly downgraded the employee’s judgment and ownership. Perhaps, by doing this, you have also inadvertently increased the divide between us (employees) and them (management). Not the ideal nurturing environment we want in organizations. In the ideal world, we would expect the employee to take leave in a way that doesn’t negatively impact any deliverables or commitments that the company has made to its customers. You don’t require a five-page policy for this. Another way to think about this – it would be bizarre for a family to have a well-documented and defined policy for when the parent takes a day off/ vacation from taking care of children or home. When a parent needs to take time off, the rest of the family members pick up the slack and this happens without any written rule or policy. Much of the behavior of the family is determined by context and circumstances. The family operates on some broad implicit unwritten rule and context; in this case, it may be that they are going to work towards taking care of the kids and working in the family’s best interest.

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 extended to all of our products over the several months.

Agile methodologies have come a long way since the 2001 manifesto, which was primarily aimed at software teams and considered subversive at the time. Although most companies still haven’t fully adopted Agile, the business world is waking up to its merits far beyond software development. According to a recent survey, roughly 80 percent of businesses are now using Agile – at least to some extent – throughout major lines of business like customer service, marketing, sales, and R&D. Furthermore, “Agility Masters” who leverage the principle across their entire organization report 60 percent higher revenue and profit growth than their peers. How is a development philosophy built for technical teams and considered risky until recent years now turning into a reigning best practice – a signifier of innovation and versatility in crowded, competitive markets? Why Agile Works? In case it’s been a while since you read up on the tenets of agile, here’s an overview. Agile is a product development approach that drives progress in short, repeatable iterations run by self-organizing, cross-functional teams. Instead of a master plan with milestones, Agile focuses on smaller segments of work and continuous adaptation. Instead of a product manager, responsibilities are distributed among the team. Overall, the goal is to get a working product out the door as quickly as possible, then test and learn.

DevOps has been instrumental in transforming IT responsiveness to business, as is evident by the fact that we have enterprises from all walks of life including Banks adopting DevOps. It’s certainly not a thing that hip web companies do now. However, with this rush to “do” DevOps comes the noise associated with it and hence, the confusions. I’ve been asked quite a bit off late we’re practicing Lean Kanban already how would DevOps help us? or even Do we need to do DevOps when we’re practicing lean? This blog is an attempt at two things, at showing how DevOps borrows Lean principles and it’s really not an either/or equation between these practices as they complement each other. DevOps While there are many definitions of DevOps the one I like to stick to is: "A cultural and professional movement that stresses communication, collaboration and integration between software developers and IT operations professionals while automating the process of software delivery and infrastructure changes". While there wasn’t necessarily anything more to DevOps than an observe and solve sort of cycle initially. Over the years we’ve had a more formalised way of working in DevOps. I’d still say most of it is common sense but then creating a structure or nomenclature does help majority of human beings to identify better. DevOps therefore has certain principles that make up most of what we know as DevOps today. Lean Most of us would know Lean well enough; the classic definition in IT industry context is "Lean IT applies the key ideas behind lean production to the development and management of IT products and services". And to know more about Lean Production you can start from here. Let’s look at the lean principles before I elaborate on this blog’s theme. 1. Define value precisely from the perspective of the end customer 2. Identify the entire value stream for each service, product or product family and eliminate waste 3. Make the remaining value-creating steps flow 4. As flow is introduced, let the customer pull what the customer wants when the customer wants it 5. Pursue perfection

DevOps is the acronym given to the combination of Development and Operations. It refers to a collaborative approach to make the Application Development team and the IT Operations team of an organization to seamlessly work with better communication. It is a philosophy that encourages adopting iterative software development, automation, and programmable infrastructure deployment and maintenance. DevOps emphasizes building trust and better liasioning between developers and system administrators. This helps the organization in aligning technological projects to business requirements. Changes rolled out are usually small and reversible, which the entire team begins to comprehend. DevOps is visualized as an infinite loop comprising the steps: plan, code, build, test, release, deploy, operate, monitor, then back to plan, and so on. While the visualization helps us understand how DevOps works, let us try to dig a little deeper to figure out which are the different DevOps tools, and how they help an organization. 1. Build Automation 2. Continuous Integration and Continuous Deployment 3. Infrastructure as Code 4. Configuration Management 5. Orchestration 6. Monitoring 7. Microservices Once you start following DevOps methodologies, it finds one way or the other to make the software act in a similar way right from development to production, via testing. It deploys changes individually, thus making bugs easily visible. These, once discovered, lead to code improvements through investigations and constant feedback channels. While developers run live software and IT Ops are involved in design meetings – both of them, along with other specialists, can contribute to investigations and feedback channels, which help foster a DevOps culture. With the cycle time from ideation to software going live reduced, your organization can capitalize on market opportunities, thus providing you with a competitive advantage for your business. Evolution of DevOps Originally coined by Patrick Debois, DevOps has become a critical discipline for realizing the benefits of Agile that ensures that rapid, iterative code development results in rapid, iterative code deployment! While Agile’s gained popularity, often at cross-purposes with the more formal and “heavy” ITIL methods popular with IT in the early and mid-2000s, DevOps resonated with both sides. Organizations that have adopted ITIL can also implement DevOps, especially for Cloud-based applications. Starting with The Phoenix Project, by Gene Kim, DevOps has steadily gained popularity and supporters and is seen today as a crucial element of any Agile technology organization. Consequently, large corporations and all sorts of technology vendors now support DevOps. DevOps jobs have become ever more popular – and the norm – in Hitech organizations. With the emergence of AI and ML in all aspects of the software lifecycle, AI for DevOps is starting to make DevOps even more smart, fast and seamless – tho’ a lot remains to be done.

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. Let’s dive in: 1. What is Artificial Intelligence (AI)? 2. The Resurgence of AI 3. Applications of AI in Real World 4. Implications of AI in Workplace 5. What’s Ahead? 6. Digité & Artificial Intelligence 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), 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. 40% of all DX initiatives will be related to AI. 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. 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. https://www.digite.com/blog/digital-transformation-and-artificial-intelligence/