#guide Archives - Page 4 of 8

WHAT’S NEW IN SOLUTIONS?

Posted on 12/04/202015/06/2021 by Tushar

Dell, HP, IBM have all tried to transform themselves from being box sellers to solution providers. Then, in the world of Uber, many traditional products are fast mutating into a service. At Walmart, it is no longer about grocery shopping. Their pick and go service tries to understand more about your journey as a customer, and grocery shopping is just one piece of the puzzle.

There’s a certain common thread that run across all three examples. And it’s about how to break through the complexity of your end customer’s life. Statistics, machine learning, artificial intelligence can’t maketh the life of store managers at over 2000 Kroger stores across the country any simpler. It sounds way too complex.

Before I get to the main point, let me belabor a bit and humor you on other paradigms floating around. Meta software, Software as a Service, cloud computing, Service as a Software… Err! Did I just go to randomgenerator dot com and get those names out? I swear I did not.

The cliché in the recent past has been about how industries are racing to unlock the value of big data and create big insights. And with this herd mentality comes all the jargons in an effort to differentiate. Ultimately, it is about solving problems.

In the marketplace abstraction of problem solving, there’s a supply side and a demand side.

The demand side is an overflowing pot of problems. Driven by accelerating change, problems evolve really fast and newer ones keep popping up. Across Fortune 500 firms, there are very busy individuals and teams running businesses the world over, grappling with these problems. Ranging from store managers in a retail store, to trade promotion manager in a CPG firm, a district sales manager in a pharma firm, a decision engineer in a CPG firm and so on. For these individuals, time is a very precious commodity. Analytics is valuable to them only when it is actionable.

On the supply side, there are complex math (read algorithms), advanced technology and smart people to interpret the complexities. And, for the geek in you, this is a candy store situation. But, how do we make these complex math – machine learning, AI and everything else – actionable?

To help teams/individuals embrace the complexity and thrive in it, nature has evolved the concept of solutions. Solutions aim to translate the supply side intelligence into simple visual concepts. This approach takes intelligence to the edge, thereby scaling decision making.

So, how do solutions differ from products, from meta-software, service as a software and the gibberish?

Fundamentally, a solution is meant to exist as a standalone atomic unit – with a singular purpose of making the lives of decision makers easy and simple. It is not created to scale creation of analytics.
For example a solution created to detect anomalies in pharmacy billing will be designed to do just that. The design of this solution will not be affected by the efficiency motivation to apply it to a fraud detection problem as well. Because the design of a solution is driven by the needs of the individual dealing with the problem, it should not be driven by the motivation to scale the creation of analytics. Rather, it should be driven by the motivation to scale the consumption of analytics; to push all the power of machine learning and AI to the edge.

In Anteelo you have a partner who can execute the entire analytical value chain and deliver a solution at the end. No more running to the IT department with a deck/SAS/R/Python code, asking them to create a technology solution. Read more about our offerings here.

Making Change Management Work for You

Posted on 11/04/202015/06/2021 by Tushar

“The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.”

– Alvin Toffler

“Times have changed.” We’ve heard this statement ever so often. Generations have used it to exclaim “things are so complicated (or simple) these days,” or expressing disdain – “oh, so they think they are a cool” generation. Whichever way you exclaim, change has been truly the “constant”.

This change is bolstered by a tech-enabled world where the speed at which machines are learning is accelerating – the speed of light.

Let me set this in context with an example from the book of Sales. Unlike in the past, today sales reps are not gauged by the amount of sweat trickling down their foreheads. While they continue to be evaluated in terms of business development and lead conversions, it is not all manual and laborious. Technology advancements have made the process of identifying, prioritizing, scheduling, conversing and converting agile and real-time.

But just knowing change, gathering data and appreciating technology will not suffice. The three will need to be blended seamlessly to yield transformation. Applied to deeper organizational context, “Change” needs to be interpreted – its pace needs to be matched, or even better, its effect needs to be contextualized for differentiation.

Change management in this sense is the systematization of the entire process; right from the acceptance of change to its adoption and taking advantage of it to thrive in volatile times.

But what would it take for complex enterprises, that swear by legacy systems, to turbo charge into the Change Management mode?

To answer this, I will humanize enterprise change management with the Prosci-developed ADKAR Model.

Awareness (getting into the race) – Where can I set up the next retail store, what is the most optimal planogram, how do I determine the right marketing mix, what is my competition doing different, how do I improve customer experience, how do I ensure sales force effectiveness – the questions are ample. By the time you realize and start strategizing, a competitor has dislodged your market position and eaten a large portion of your pie. And while these business problems seem conventional, volatility in the marketplace cry foul. Compound this with high dependencies on dashboards, applications, and the likes for insights, and you’ve seen the side-effects – established enterprises biting the dust.

To survive, organizations will need to be knowledgeable about data that matter viz a viz the noise. They will need to interpret the data deluge in relevance and context; after all, not all data is diamond.

Desire (creating a business case for adoption) – Desire is a basic human instinct. Our insatiable urge to want something more, even better, accentuates this instinct. When it comes to enterprises, this desire is no different; to stay ahead of the curve, to make more profits, to be leaders. But there is no lock-and-key fix to achieve this mark. Realizing corporate “desire” will require a cultural and mindset shift across the organization – top-down. And so, one of the most opportune times could be when there are changes at the leadership, followed by re-organization in the rungs below.

Gamification could be a great starting point to drive adoption in such cases. Allow the scope of experimentation to creep in; invest consciously in simmer projects; give a freehand to analysts to look for the missing piece of the puzzle outside their firewall; incentivize them accordingly. Challenge business leaders to up their appreciation for the insights generated, encourage them to get their hands down and dirty when it comes to knowing their source, ask the right questions and challenge status quo – not just rely on familiarity and past experiences.

Knowledge and Ability (From adoption to implementation) – In business context, “desire” typically translate into business goals – revenue, process adoption, automation, newer market expansion, launch of a new product/solution, etc. Mere awareness of the changes taking place does not translate into achievements. It needs to be studied and change management needs to be initiated.

But how can you execute your day job and learn to change?

The trick here will be to make analytics seamless; almost second nature. Just as the message alert from the bank about any suspicious transaction made on your account, any deviation from the set course of business action needs to be alerted.

Such technology-assisted decisions are the need of today and the future. Tredence CHA solution is an example in this direction. It is intuitive, convenient and evolving, mirroring aspects of Robotics Process Automation (RPA).

Reinforcement (Stickiness will be key) – Your business problems are yours to know and yours to solve. Like my colleague mentioned in his blog, a one size fits all solution does not exist. Solving the business challenges of today requires going to the root cause of it, understanding the data sources available to you, and being knowledgeable about other data combinations (across the firewall or within) that matter. Match this stream of data with relevant tools and techniques that can give you the “desired” results.

Point to keep in mind during this drill is to ensure that you marry the old and new. Replacing a legacy system with something totally new could leave a bad taste in your mouth – with less adoption and greater resistance. Embedded analytics will be key – one that allows you to seamlessly time travel between the past, present and future.

To conclude, whether it is about time to implement change, improving customer service, reducing inefficiencies, or mitigating the negative effect of volatile markets, Change Management will be pivotal. It is a structured, on-going process to ensure you are not merely surviving, rather thriving in change.

Remote workforces kept productive by IT support automation

Posted on 06/03/202015/06/2021 by Tushar

Enterprise clients have looked to automate IT support for several years. With millions of employees across the globe now working from home, support needs have increased dramatically, with many unprepared enterprises suffering from long service desk wait times and unhappy employees.

Many companies may have already been on a gradual pace to exploit digital solutions and enhance service desk operations, but automating IT support is now a greater priority. Companies can’t afford downtime or the lost productivity caused by inefficient support systems, especially when remote workers need more support now than ever before.

Digital technologies offer companies innovative and cost-effective ways to manage increased support loads in the immediate term, and free up valuable time and resources over the long-term. The latter benefit is critical, as enterprises increasingly look to their support systems to resolve more sophisticated and complex issues. Instead of derailing them, new automated support systems can empower workers by freeing them up to focus more on high-value work.

Businesses can start their journey toward digital support by using chatbots to manage common support tasks such as resetting passwords, answering ‘how to’ questions, and processing new laptop requests. Once basic support functions are under digital management, companies can then transition to layering in technologies like machine learning, artificial intelligence and analytics among others.

An IT support automation ecosystem built on these capabilities can enable even greater positive outcomes – like intelligently (and invisibly) discovering and resolving issues before they have an opportunity to disrupt employees. In one recent example, Anteelo deployed digital support agents to help manage a spike of questions coming in from remote workers. The digital agents seamlessly handled a 20% spike in volume, eliminated wait times, and drove positive employee experiences.

Innovative IT support

IT support automation helps companies become more proactive in serving their employees better with more innovative support experiences. Here are three examples:

Remote access

In a remote workforce, employees will undoubtedly face issues with new tools they need to use or with connections to the corporate network. An automated system that notifies employees via email or text about detected problems and personalized instructions on how to fix them is a new way to care for the remote worker. If an employee still has trouble, an on-demand virtual chat or voice assistant can easily walk them through the fix or, better yet, execute it for them.

Proactive response

The ability to proactively monitor and resolve the employee’s endpoint — to ensure security compliance, set up effective collaboration, and maintain high-performance levels for key applications and networking – has emerged as a significant driver of success when managing the remote workplace.

For example, with more reliance on the home internet as the path into private work networks, there’s a greater opportunity for bad actors to attack. A proactive support system can continuously monitor for threat events and automatically ensure all employee endpoints are security compliant.

Leveraging proactive analytics capabilities, IT support can set up monitoring parameters to match their enterprise needs, identify when events are triggered, and take action to resolve. This digital support system could then execute automated fixes or send friendly messages to the employee with instructions on how to fix an issue. These things can go a long way toward eliminating support disruptions and leave the employee with a sense of being cared for – the best kind of support.

More value beyond IT

Companies are also having employees leverage automated assistance outside of IT support functions. These capabilities could be leveraged in HR, for example, to help employees correctly and promptly fill out time sheets or remind them to select a beneficiary for corporate benefits after a major life event like getting married or having a baby.

Remote support can also help organizations automate business tasks. This could include checking on sales performance, getting recent market research reports sent to any device or booking meetings through a voice-controlled device at home.

More engaged employees

With the power to provide amazing experiences, automated IT support can drive new levels of employee productivity and engagement, which are outcomes any enterprise should embrace.

Matter of mobility to the clinician: Connected healthcare

Posted on 05/03/202015/06/2021 by Tushar

Technology experts will often talk about the benefits of mobility in healthcare, but to understand why mobility matters and how it might improve both workflow and clinical benefits for patients, it’s vital to get a user’s perspective.

As a clinician, my view of mobility is influenced by my own experiences in different medical settings. Clinicians — by which I mean doctors, nurses and other allied health professionals — work across multiple hospital wards, often across several hospitals or medical facilities, with multiple parties involved in the care of the patient. For example, a cardiologist might review a patient in the hospital’s outpatient department, in the emergency department or in the cardiology ward. As a result, the cardiologist may need access to medical records across various locations, which potentially could be sourced from multiple systems of record.

The key is being able to access those records in real-time and on the go. If clinicians are required to interrupt a patient evaluation to access information from a file or computer, valuable time can be lost, affecting the care of the patient. If clinicians can access the right information at the right time and in the right place — at the patient’s bedside, on the go, or in various locations — they are better equipped to make informed and accurate clinical decisions, enabling them to spend more time with the patient and ultimately improving patient care.

Furthermore, clinicians don’t work in isolation. Mobile access to clinical data and the ability to share information with other health professionals — for example accessing blood results from pathology or rehabilitation progress notes from a physiotherapist — give everyone involved in the patient’s care the right information as and when needed. These also ensure that clinicians make good use of their time. For example, if a doctor can see that the patient is scheduled for an X-ray at 11:45 a.m., he or she knows a midday appointment is not feasible.

Taking a holistic approach to Healthcare

We also need to realize that healthcare doesn’t happen in isolation from the rest of our lives. Most people now access information through their mobile devices. It makes sense, therefore, that clinicians would want to access clinical data in the same way.

And patients are also more connected in every way. They expect to be included in decisions driving their own healthcare. They want to understand their diagnosis and what it means. If the clinician can access the patient’s data on a mobile device, it’s much easier to have an informative bedside discussion with the patient. For example, the clinician can pull up the patient’s X-ray or blood test results on a mobile device and show the patient areas of concern or trends in the results.

The clinician might want to go further and share information about a procedure — for example, videos of a procedure or hyperlinks to information that might be helpful to the patient. Or the clinician and patient can watch the video together on the mobile device, giving the patient an opportunity to ask questions and be properly informed.

A truly mobile, integrated solution will also be able to aggregate information from multiple sources — the patient’s medical record, pharmacy record, nurses’ notes — and have it all in one place.

In an age where data security, patient privacy, and accountability are under the microscope, mobility gives healthcare systems the ability to track information. The system will show that a certain clinician has seen the results. It’s possible to also require that clinician acknowledge receipt of the information as he or she receives it.

There’s no doubt that challenges exist — technical, logistical, user-specific, and more — but the benefits are worth the pursuit of a solution. Healthcare organizations have the information required to ensure quality patient care, increase patient satisfaction and reduce the rate of mortality and morbidity. But, they want to be able to get that information about their patients in real-time and on the go. Ultimately, clinicians want mobility. After all, it’s how most people — clinicians included — interact with the world in their daily lives. Why should healthcare be any different?

Learning complexities: Best practices of work in the future

Posted on 04/03/202015/06/2021 by Tushar

Today’s high performing organizations know that the world of learning has undergone tremendous change, and they need to put employees at the center. Employees require a lifetime of continuous learning to keep pace with change.
An innovative approach to learning can help tackle the workforce skills gap, retain talent, increase performance and improve productivity.

Organizations need to create a learning culture and environment that welcomes knowledge seeking and employee self-improvement. The next generation of learning technology expands access, personalizes experiences, offers actionable insight and helps track how learning affects business outcomes.

Learning leaders must work together and share the same vision to successfully engage and prepare their employees for the future of work. Here are five best practices we view as critical for successfully overcoming the challenges and complexity within learning today:

Take advantage of new learning platforms. Standardizing on a single LMS is not the only option to address learning complexity. Having multiple systems is fine, even preferable, provided they can be accessed through a single platform. What’s important is to implement a multi-platform, agile methodology where the learner’s experience is the focus.

Meet learners where they are at. Employees do not have as much time as they would like for formal learning, informal “in-the-flow” work learning is necessary for training and development.

Embrace evolving workforce demographics. To address learning diversity, investing in next-generation learning technology and fresh approaches includes mobile learning tools and personalize learning paths needed to improve performance and retain talent.

Up-skill for the future of work. Closing the skills gap requires prioritizing learning development programs that empower employees to seek new skills that meet evolving business needs.

Ensure employees remain relevant in the digital workplace. Employees need to build comprehensive skill sets that are applicable to a variety of roles that will eventually be in high demand with the adoption of automation, robotics, and artificial intelligence.

In today’s changing world of work, employees need access to anytime, anywhere learning that’s relevant and meaningful to their development. An active learning community encourages employees to become insight experts and share actionable knowledge that enhances organizational intelligence.

It is time to pursue an innovative approach to learning and to take full advantage of next generation learning technology that prepares employees for change, aligns with business goals and connects a global workforce to deliver performance that accelerates growth.

Dimensions of change in the digital workplace

Posted on 26/02/202015/06/2021 by Tushar

Upgrade workplace technology: check. Modernize infrastructure: check. Adjust to new workforce: check. Overcome resistance to new ways of working: check. Adjusting to digital transformation’s impact on the workplace and workers is, well, a lot of work. A lot of change. And it’s essential to understand that workplace transformation will only deliver expected business benefits when organizations develop effective ways to cope with change along many dimensions. These include:

Workforce. For the last few years, we have focused on the generational shift taking place as millennials become the bulk of the workforce. However, there is a second shift that will impact how we operate. Organizations are adopting more gig workers for specific tasks or projects, which puts pressure on IT to streamline gig workers’ experience and optimize processes to maximize gig workers’ productivity. Capitalizing on automation, intelligence, and integration to optimize business flows and processes will become fundamental to IT operations.

Human resources. This blended workforce, and the recognition that organizations are already adopting a task or gig-like approach internally, impacts the way we run our Human Resources processes. The line manager might continue as a custodian, but the management chain becomes flatter, tied to activities and projects. The old reporting model breaks by having so many stakeholders and managers. We need to automate and collate information for the relevant project and stakeholder, distill it succinctly, and publish it to those who are invested, as well as archive it as input to the performance review process.

Project management. That information will enable project managers and stakeholders to better manage the individual and the team, optimizing for performance and cost. As they see near-real-time information about productivity and performance (on their specific project), they can flex, coach, and change the team as needed. It is a much more hands-on world, although some of the tasks can be automated. Project resource managers can learn from just-in-time manufacturing techniques, bringing in the right folks at the time they are needed.

Relevant information. In this environment, relevant information — not more information — is the key. Luckily, the platforms citizen developers are experimenting with also provide some of the components needed. They can capture tasks done, documents touched and discussions held, giving us a raw feed of activity. Post-process this information, in the context of each stakeholder, can be used to produce concise, relevant reports grounded in system data, not flawed memories.

Embrace employee-driven innovation. Organizations must become better at matching the pace of change, using techniques like employee-driven innovation to quickly identify new workplace trends and opportunities. Formalizing informal support networks can help manage change more effectively and capture the benefits of disruption. And when companies understand how productivity and morale are boosted by ongoing workplace investments, the cost of change is less daunting and easier to justify.

Connection and collaboration. Companies must continue to develop policies that give workers flexibility in the devices they chose to use. How people connect and collaborate is changing as well; companies will need to foster collaboration on, and set policies for, social media in the enterprise.

Automation. Software agents, bots and intelligent machines will make tasks easier. Companies will need to consider how these new devices and applications can learn and apply user preferences, and how they can use real-time information in context to automate more tasks and decisions.

Enterprises can truly change the way employees work by providing a flexible, expansive workplace with the right technologies and policies. Those who come to grips with the new definition of the workplace and its enabling technologies will be the digital leaders of tomorrow.

Optimizing Agile delivery when the development team isn’t co-located

Posted on 24/02/202015/06/2021 by Tushar

Co-locating Agile development teams with the customer or business unit is optimal for collaboration and customer intimacy. However, co-location is not always feasible. Development team members could be from multiple geographic locations, the customer could also be spread across multiple locations, and economic considerations might direct some of the development to regions with lower costs.

This requires an effective Distributed Agile/Remote Agile Delivery model. Here are the four key considerations that need to be taken into account for a Distributed Agile Delivery model to ensure successful delivery:

1. Culture. If the teams are spread across multiple countries, cultural differences are bound to arise due to diverse work practices, values, processes, styles of leadership, decision-making, and problem-solving approaches. Not being able to work side-by-side can lead to misunderstandings from unrecognized cultural differences.

To mitigate, it is essential to build trust and establish relationships between the teams early on. Initiation events, where teams meet and work together, and establish common standards and consistent practices, present a great opportunity to establish trust and foster team building. Sending “Ambassadors” from each site to the others on a periodic basis is also an effective way to bridge the cultural gap.

2. Common hours and communications. Cultural and language differences make effective communications hard. Even with web- and video-conferencing, it is challenging to overcome the lack of visual cues and face-to-face interactions. This is further compounded by insufficient time zone overlap.

Teams need to work out an approach to shift some work hours to improve their time zone overlap. Often teams agree on “core hours” during which members at all locations will be simultaneously available. Reliable communication tools, desktop sharing, phone, instant messaging, and virtual rooms can then play a big role in establishing strong communications. Agile coaches and Scrum masters need to step up as effective coordinators. Bi-directional travel by key customer stakeholders and vendor leaders also helps.

3. Collaboration. Distance makes collaboration and frequent communication challenging. Context of discussions is sometimes lost as well. Using a “Proxy Product Owner” at each site can help bridge any gaps in business and domain knowledge. Building a work culture around compulsively using Enterprise Agile Planning Tools (EAPT) and collaboration tools facilitates collaboration among remote teams. The Ambassador program mentioned earlier — rotating some or all of the team between locations — and bringing the teams together on a periodic basis helps.

4. Consistent Infrastructure and Configuration Management. Challenges with Distributed Agile multiply if you do not have standard shared infrastructure and continuous integration. You need to leverage virtualization and provide identical environments for teams at all sites. Other strategies include using a single configuration management system for all teams, deploying DevOps (at least Continuous Integration and Continuous Testing), and insisting on frequent builds.

Ensuring that these four areas are addressed at project onset sets the collaborative tone for your distributed agile delivery. Having a collaborative team mindset from kick-off through delivery is crucial to project success.

Techniques and Tactics concerning Hybrid IT

Posted on 23/02/202015/06/2021 by Tushar

As companies embrace hybrid IT, they must address both technology and the human side of change. There are several key actions to take:

Staff and train differently: As applications move from traditional platforms to the cloud, current IT staff needs to be trained and re-skilled. Companies should recruit developers adept in Agile methodologies. Siloes should be broken down, and the workforce should become more integrated, multifunctional, flexible and agile.

Overhaul change management: The existing governance processes, gates and approval procedures designed for traditional legacy IT environments are no longer appropriate in a cloud environment. Companies need to revamp their change management systems to allow changes to happen quickly and, using automated workflows, to reduce manual intervention.

Integrate cloud operations: As organizations move workloads to the cloud, the IT operations function should adapt to manage both on-premises and cloud-based applications. This new model, called CloudOps, can provide continuous integrated operations in a multi-cloud environment to enable rapid response to events, incidents and requests. Adding DevOps to the mix then utilizes automation, integration and organizational change to enable more frequent enhancements that result in higher quality software.

Automate support: To the extent possible, automate IT support functions. For example, the traditional trouble ticket system can be manually intensive and inefficient. Automation can improve service and free up IT personnel for higher-level activities. Longer term, companies will be able to deploy machine learning and AI to take log data from cloud-based systems and automatically take actions to resolve and even prevent incidents.

Manage “shadow IT”: Business units are often acquiring the cloud services they need because IT moves too slowly. At some point, those services must be integrated back into the traditional IT environment for operational and security reasons through a services governance model that encompasses hybrid IT elements.

In addition, it’s important for CIOs to have a handle on what the enterprise is spending on IT services. The only way to accomplish this is to adopt hybrid IT and demonstrate to business units that IT can support the pace and scale that the business requires.

Most popular questions companies have regarding AI and ML

Posted on 22/02/202015/06/2021 by Tushar

Artificial Intelligence (AI) and Machine Learning (ML) are rapidly evolving to help companies with both digital transformation and innovation. There has been a lot of hype and discussion about these topics, and, in a very short time, we have moved the conversation from “AI is cool” to “AI can drive specific business outcomes.”

Experience has allowed companies to clarify the economics of AI and reduce time to value. In addition, the technology has continually improved, with advancements including:

extracting unstructured data for improved insights and processes
moving from simple chatbots to more sophisticated conversational assistants that are smart, use more natural language interaction (text and/or voice), and enable the initiation of transactions
integrating operational and knowledge management systems

As our clients start to understand more about AI/ML, there are 2 key questions typically asked:

Question 1: “How do AI and Machine Learning differ from traditional programmed systems?”

There are three different capabilities that AI/ML typically extends and enhances into existing applications. One aspect is understanding – enabling systems to understand language, other unstructured data, including pictures, just like humans do. A second aspect is reasoning – enabling systems to grasp underlying concepts, form hypotheses, and infer and extract ideas, similar to humans. The third aspect is focused on learning – improving over time and avoiding repeated mistakes. These capabilities, often referred to as U-R-L (understand, reason, learn), are easily integrated into existing applications as consumable APIs, can reduce time to value.

Question 2: “Where is the value from Artificial Intelligence/Machine Learning?”

As we look across client environments, most clients are very comfortable with structured data that is within their firewall – things like transaction systems, customer records, and even predictive models. Many analysts estimate that 80% of data created today is unstructured, which requires clients to expand their current perspectives in 2 dimensions:

Structured to unstructured, such as documents, transcripts, social media, weather, images, IoT and sensor data, and news
Within the firewall to outside the firewall, including public data, licensed private data, and new types/sources being created every day

From a value perspective, the enticing aspect of AI and machine learning is connecting these structured and unstructured data types within and outside these walls. This enables richer, more, and unexpected insights, new business processes, and improved workflows at dramatically reduced cost levels.

As AI and machine learning mature, three use cases patterns have emerged around customer care, human capital management and the rethinking/reimagining of processes thanks to insights gained from unstructured data and natural language capabilities.

We’ll expand on these use cases and how we are applying AI/ML for our clients in our next blog post.

Techniques of making Cloud Application Migrations simpler

Posted on 19/02/202015/06/2021 by Tushar

Many system integrators and cloud hosting providers claim to have their own unique process for cloud migrations. The reality is everyone’s migration process is just about the same, but that doesn’t mean they’re all created equal. What really matters is in the details of how the work gets done. Application transformation and migration requires skilled people, an understanding of your business and applications, deep experience in performing migrations, automated processes and specialized tools. Each of these capabilities can directly impact costs, timelines and ultimately the success of the migrations. Here are four ways to help ensure a fast and uneventful move:

1: Create a solid readiness roadmap.

The cloud readiness stage is often referred to as the business case and/or involve a total cost of ownership assessment, rapid discovery, advisory services, and more. However, most of these approaches fall short of the up-front analysis really needed to decide which applications to move, refactor or replace. When you embark on a migration to cloud, job one is to ensure you are ready to go. Diving right into a migration without a roadmap is typically a recipe for failure. If you don’t know what the business case is to migrate, then stop right there. You should come out of the readiness phase with a high-level plan and an initial set of migration sprints and a detailed roadmap on how to address the subsequent sprints.

2: Design a detailed migration plan.

This phase, also referred to as deep discovery, will help keep migration activities on schedule. All too often, lack of proper analysis and design leads to surprises in the migration phase that can have a domino effect across multiple applications. This phase should include a detailed analysis of the scope of applications and workloads to be migrated, sprint by sprint. This agile process shortens migration time and ensures faster time to value in the cloud. All unknowns are uncovered, and changes are incorporated in the roadmap to ensure anticipated business objectives will be achieved.

3: Set a strict cadence — and stick to it.

Often, most of the planning effort focuses on getting past that first migration sprint. This phase requires a great deal of planning and preparation across multiple stakeholders to keep the project on time and within budget. Scheduling all of the resources and tracking the tasks that lead up to D-day is no simple job. These activities must follow a standard cadence of planning steps to ensure effective and efficient migrations.

4: Automate as much of the migration as possible.

The way your organization performs the migration can also impact the project. In most cases, tools that automate the application transformation process, as well as the migration to cloud, can mean a huge savings in time and money. Unfortunately, there’s no off-the-shelf automation tool to ensure success. The migration phase requires people experienced in a range of tools and how to orchestrate the work.

One could argue that a fifth way to ease migration headaches is optimizing applications during the process. However, there are different schools of thought on whether to optimize applications and workloads before, during or after migration. I can’t say there is a definitive right or wrong answer, but most organizations prefer to optimize after migration. This allows for continuous tuning and optimization of the application moving forward.

It is important to note that steps in the migration process are not one-and-done activities. The best migration and transformation services are iterative and continuous.

You can’t determine readiness only once. The readiness plan needs to be reviewed on an ongoing basis. Don’t analyze and design migrations just once. Do it sprint by sprint, and plan each migration activity. Make sure you continuously collect and refresh data, refine and prioritize the backlog, and look for key lessons learned to ensure continuous improvement through the lifecycle of entire migration. Experience and planning can go a long way toward easing your next application migration.

Tag: #guide

WHAT’S NEW IN SOLUTIONS?

In the marketplace abstraction of problem solving, there’s a supply side and a demand side.

So, how do solutions differ from products, from meta-software, service as a software and the gibberish?

Making Change Management Work for You

Remote workforces kept productive by IT support automation