Ensuring Vendor Diversity - Why Enterprises should work with small IT vendors

Posted by Gaurav Mishra on Sep 19, 2018 11:22:00 AM

Large IT vendors are great. They have huge teams they’re able to put at your disposal, they’ve been around and will be around for a long time, and more often than not they have the experience of working on a project like yours. In short, they are safe, reliable, and they will get the work done. 

Smaller technology companies, on the other hand, are never the first choice for enterprises because of several concerns:

  • Do they have a team big enough to serve my project?
  • Haven’t really heard about them. Are they any good?
  • They make a good point but what if they can’t deliver? Is that a risk worth taking?

 

These are all valid questions that an enterprise procurement team has to consider. But amidst these doubts, there might be a few key advantages that you might be missing out on.

Here are four unique benefits that smaller IT firms bring to the table:

Niche Expertise

While large vendors may have teams offering a lot of different technologies, each is a small part of their overall skill set. So you get a team that has a range of skills but often not enough depth of skills. On the other hand, small IT companies typically build deep expertise in niche technologies, which makes them capable of delivering more customized and sophisticated solutions with those technologies. 

For example, we work with a global consulting giant because they wanted a team that has deep expertise and experience of working with Drupal. They were already working with a large IT vendor, but not really convinced of their Drupal skills. We, however, had a team of Drupal developers experienced with deploying large-scale Drupal implementations. And that fit in perfectly with what the client was looking for. We have been working with them for six years now, and till date are the only high-skilled Drupal team they trust.

Interestingly, our engagement with them has also led to them expanding their previously limited Drupal project. Currently, they run a vast array of internal systems on Drupal including internal as well as customer facing websites that leverage Decoupled Drupal.

De-Risk Project Delivery

Not putting all your eggs in the same basket are widely accepted words of wisdom that should apply to hiring an IT vendor as well. And then why you need vendor diversity - a mix of different vendors working on your project Entrusting the entire project, or all simultaneous independent or interdependent projects to a single vendor is taking a huge risk on the delivery. In a scenario where the initial engagement is plagued by project management or delivery challenges, that impacts other downstream projects as well, severely delaying project timelines. The high initial investment and time spent in on-boarding a large vendor also makes it difficult to quickly change vendors mid-project.

Introducing small IT vendors into the project, especially for parts of it that demand niche technology expertise, is a good way to de-risk delivery. This could have two key advantages:

  • Segments of the project get delivered even if there are challenges with the large vendor. So you are just left with a huge bill with nothing to show for it.
  • Since you already have a different vendor in the mix, with understanding of the project (even if just a part of it), they can be easily brought in to either assist or replace the teams from the large vendor, if necessary. You save on critical expenditures in the middle of the project, while being able to bring it back on track.

Agile and Transparent Project Management

Small companies have tighter teams, shorter hierarchies, and less red tape which allows them to move faster on projects.

While Agile is an accepted projected delivery method across most IT teams, it is easier to follow rigorously with smaller, tightly integrated teams. And that ensures a more streamlined, flexible, and faster product development and delivery process.

For example, one of our clients, a global financial services firm, had stalled their product development owing to the US$ 1 million budget, and six month delivery timeline quoted by a large IT firm.

We came on board and offered to do a PoC delivering the most complex piece of their product. We did it at an investment of US$ 50,000 and in just four weeks. The lower investment and shorter delivery time gave the client confidence to move ahead with the project. We successfully delivered the complete product and have been maintaining it for a few years now.

In addition to the speed, teams brought in by smaller vendors are more amenable to working in close collaboration with your internal teams, and aligning to your delivery processes. This gives your stakeholders better visibility into the project, and hence greater control. Given the shorter hierarchies, you also have easier access to vendor-side decision makers in case you need to escalate certain challenges and concerns.

Superior Service and Delivery

Smaller IT vendors specializing in a specific set of technologies are small by design. They choose to work on a limited number of projects at a time, and that creates a huge advantage for their clients.

Teams from smaller vendor firms are highly focussed on their respective projects, and not spread out too thin across different projects. This means greater attention to your particular project, with teams making the effort to identify and develop the right technology solutions, and taking the time to truly innovate to meet your requirements. With a fully dedicated team, you can also be assured of timely delivery and a more transparent project management process.

Yes, a small IT vendor may not be an immediately logical choice for enterprise procurement teams. But these advantages definitely make them a viable contender, especially when it comes to developing highly customized solutions leveraging specific technologies. What they might lack in numbers, they more that make up for in skill levels, flexibility, and accessibility.

Srijan’s 250+ strong technology team is currently working with global enterprises across seven countries. Our extensive expertise with Drupal, as well as skilled teams for complementary technologies, enable us to successfully deliver a range of transformative digital solutions to our enterprise clients.

Working across media, travel, retail, telecom, and pharmaceutical industries, we typically kickstart our engagements with small PoCs. That helps our clients assess if our technology expertise fits their requirements, and how our teams work and deliver.

Got a digital transformation project in the works? How about we do a quick PoC to demonstrate the benefits of working a smaller vendor?

Tell us a bit about your project, and our solution experts will be in touch.

Topics: Project Management, Enterprises

xAPI: Toward ROI of Enterprise learning & development

Posted by Shashank Merothiya on Aug 29, 2018 3:24:00 PM

Enterprises spend on training in many ways. Offline, online, through learning management systems (LMSs), coaching, mentoring and so on. But often there’s no real way to track how the training has impacted the business. And if someone doesn’t seem to have learned what they were trained for, they are slotted into more training sessions. And it just continues.

But that’s now changing because enterprises now are measuring many activities and have a lot of data at hand. That can be put to use for training. 

Unleashing Data to Enable Learning

Take the example of cleaning a washroom by a janitor. The company can track when he came in, and when he signed out. And if there are sensors attached to the various soap dispensers and cleaning machines, there’s data on whether the right levels of soap were maintained, or if the machine was operated at the right settings. To gather customer feedback, you can have simple button presses to capture a Happy or Sad rating.

What has that to do with training?

Let’s say the time taken to clean a particular washroom is 10 minutes on an average. By looking at the time each janitor spends, you know who is likely to rushing through the job, and who is taking too much time. Map that to customer feedback received, and you have more realistic data to go with. And you also have information on soap levels and machine settings.

You have all this data that can tell you which janitor is doing a great job, and which one’s not. And so, who needs to be trained? And in what area, and for what purpose.

Let’s say Paul, a janitor, doesn’t ensure soap dispensers are kept at the levels prescribed. Instead of putting him through a training module that teaches him “How to Clean Washrooms”, you just create a micro-learning module for him: maybe a video that shows him exactly how to check for soap dispenser levels, and do the refills. And it’s made available on his phone. So he doesn’t have to be called in for an-person training, or log into a straight-jacketed LMS.

Did he check the module sent to him? How many times? Did he see the video? Did he see it on mute? You have data on all this, which enables your learning system to tell him what he is learning/missing.

All this can be automated, except for the micro-learning module creation, of course. So for a company that has tens of thousands of janitors across the world, training now becomes more personalized, and far more impactful.

xAPI, the Enabler

That’s the power of xAPI, or Experience API. It’s a standard that defines how you can interface any application with a system that stores learning data. So in the example above, you are interfacing the application that captures soap dispenser sensor data to pick up instances that pertain to learning, store it in a learning record store (LRS) which is then pulled in by the company’s LMS.

Any activity that can be observed or recorded can be mapped into your LMS through xAPI. So potentially anything that an enterprises has deployed by way of IT setup can be used to extract data that can be used as inputs for further learning needed. This can be the ERP, collaboration platforms, helpdesk systems, performance management systems, and so on.

That changes how the way you look at learning & development, doesn’t it? No doubt, it is a great idea to have all learning modules up on the LMS complete with quizzes and assignments, and scores to ensure people spend time on what they need to know to do their job well. But with xAPI coming into play, you don’t have to force-fit everyone into the same training module. Someone with some prior experience in the job can take an assessment test, and if she clears that, can be put on to the job right away. And then the data being captured on her work, can be reviewed to see what areas she needs to work on so she can deliver the business impact the enterprise is aiming for.

Yes, that’s right. The entire learning focus now can be zeroed in on business impact. So it could be about increasing sales or improving the bottomline. It could be ensuring safety at all times. The enterprise moves from, a broad based training scope to laser-focused micro learning moments that can reflect in the business results.

With xAPI, enterprises now have a way to measure how their learning and development efforts are tangibly impacting the topline or bottomline.

Srijan is now helping enterprises with delivering these systems that will put them squarely on the road to L&D ROI. Our teams are also working with enterprises to revamp their existing learning systems and make them more effective. 

Wish to drive greater ROI from your enterprise learning systems? Let's start the conversation and explore how Srijan can help. 

Topics: Drupal, Enterprises

Enterprise Learning Management System - The possibilities

Posted by Shashank Merothiya on Aug 22, 2018 4:09:00 PM

Enterprises have spent tremendous efforts into building learning management systems, evaluation applications, performance management and employee management systems over the past decades. These have brought in significant improvements in learning, productivity and streamlining processes.

 It is now time to unleash the power inherent in these various systems and applications, often disparate and silo-ed. It’s now time to make sense of what happens in one system, to power the information residing in another, so that the right learning can happen for the right person in the right way. It’s now time to make this happen and be firmly on the road to mapping all this to business impact: increase in sales, improvement in margins, adherence to safety, and so on.

Here's a closer look at why an integrated enterprise learning solution is important

 

Srijan is enabling one of the world's leading manufacturers and marketers of quality cosmetics to do this by helping them take baby steps into the world of xAPI and microlearning. Srijan started off with handling performance issues and integrations to enable better productivity, and then embarked on developing proofs of concept related to xAPI. Here’s how the journey is shaping up.

Improving the LMS performance

The Company has a number of brands and each brand has its own set of products. A few years ago, the Company had decided to build its own learning management system (LMS), as it had very specific requirements and were looking for an open source system that would be flexible, customizable and scalable enough to meet the learning requirements across the enterprise. So Drupal was chosen as the backend. The frontend was built in ReactJS. Srijan was brought in to first deliver support on the LMSs. Srijan handled performance issues and is currently enabling the migration from Drupal 7 to Drupal 8.

Integrations to the LMS

The Company was moving from an H5P content authoring platform to Articulate facing challenges with authoring content and then uploading it to the Drupal LMS. Srijan helped them with the transition by building modules for Drupal to consume and render Articulate content. Srijan worked on integrating Articulate, a content authoring tool, to the Drupal backend and then having it appropriately render on ReactJS. Now the authors can work in Articulate and not have to worry about uploading to the LMS and have intense testing to see if the content is getting rendered correctly or now.

Integrating a Learning Record Store with Drupal

The Learning Record Store is at the heart of an xAPI setup. It stores the data about learning and achievement for each employee. When a user interacts on the LMS, the interactions can be captured via the xAPI protocol and stored in the LRS. Srijan completed a POC for this as well for the Company.

Some of the interactions being captured include:

  1. User interacted with the content
  2. User experience content
  3. User passed
  4. User failed

Some of the more complex interactions that can be captured involve the following:

  1. User mutes a video
  2. User skips a video
  3. User read part of the content etc

Integration of Articulate Content in Drupal with LRS

Articulate already supports xAPI, so once the content authored in Articulate is exported into Drupal, the content is rendered with the xAPI-driven data capturing in place. This is then pulled into the LRS. Srijan developed this POC to demonstrate how the LRS would get populated with interactions on Articulate content.

Creating a Microlearning Platform

The Company has data about an employee of two different systems. One is the LMS, and the other is the evaluation system. Both have Drupal as the backend and the frontend built in ReactJS. There is a middleware Java layer. The Company operates in various countries of the world, and has several Regions managing these countries. Each brand in a region has its own LMS, and each region has its own evaluation system.

So far, an employee gets evaluated by her supervisor and that information is stored in the Evaluation system. And it may or may not get translated into training specific to the employee’s performance. For example, if her evaluation report says she needs to improve her Communication skills, she could be asked to go through the Communication module again. Or be put into another Communication offline training.

However, in such a system, there is little attention on what her real learning needs are. It could be that she is very good with some parts of Communication, and not so much with other parts. Figuring out which parts, and then designing the right learning module for her becomes key in these ways:

  • The employee doesn’t have to waste time learning things she already is well versed with
  • The employee can be asked to simply get her learning for the specific areas, through snackable content like short videos, interactive quizzes, animations, etc.

 

How do we get to this?

Create a quiz to identify the proficiency level of the employee on the learning platform. This can be done by pulling out questions from various proficiency levels. People who do well with the questions, can be given questions from higher proficiency. This identifies the specific area the employee needs training on.  

The e-learning authoring team can then look at the existing content and create snackable pieces of content that will work well for this employee. It could be a short video, a small example, an animation, a flash card, and so on. This content is made available on the learning platform which serves content in micro formats. Hence it is called a micro learning platform

The platform can then have the algorithms in place to see how this content is being consumed. For example:

  • Did the employee complete the module?
  • Did she view the video fully? If she viewed it in mute, then an alert can go to her to remind her to view it with speakers on.  
  • Did she view the graphic?

And so on.

Once the module has been completed, the trainer can evaluate her again and see if the proficiency level has improved.

All this information is being captured and stored in the LRS. This can be used to get insights to what she has learnt, how well has she learnt it.

Srijan has built a microlearning platform as a POC for the Company to see how all this works. It is also built using the Drupal-ReactJS stack. Once this is approved, it can be scaled up, and eventually integrated with the LMS. 

The Road Ahead

The next POCs that Srijan will do involve creating the reports in and out of the LRS. Once there is enough data in the LRS, Srijan will also be working on creating advanced reports about the learning performance.

The analytics can give insights for each user, brand, region and group. So there’s information about who consumed what kind of learning, and this can be scaled up across the enterprise. Map this to data around business impact, for example, sales. And you would be able to showcase this on a dashboard using xAPI pulling data from LRSs and the ERP system tracking sales numbers for each region/brand.

The Company can also get analytics about the learning content being produced. For example, if there’s a module that people are dropping off from mid-way, what could be the reason? If a video is being watched on mute by nearly all viewers, is there a problem with its audio? The content authoring team can thus identify which pieces need modification, so better consumption can take place among learners.

We've been working closely with global enterprises to modernize their learning ecosystems, whether it's by upgrading existing systems or intertwining them with emerging technologies like xAPI, chatbots, VR and more.

Wish to drive greater ROI from your enterprise learning systems? Let's start the conversation and explore how Srijan can help. 

Topics: Enterprises

Owning Amazon Alexa skills: Is your Enterprise keeping up?

Posted by Gaurav Mishra on Aug 20, 2018 2:23:00 PM

By 2020, Amazon’s Alexa is expected to become a $10 billion industry. A current leader among the voice assistant platforms, Alexa, allows third party developers to build new Amazon Alexa skills using its extended API. Many media enterprises  like the BBC, ESPN, and the Daily Show have already introduced their own ‘skills’ for the Alexa platform, aimed at providing unique content to their customers.

What are Alexa Skills?

Alexa Skills are like voice-powered equivalents of applications that are used in mobile phones or PCs. Once installed on devices, they can be used by Alexa to provide immediate and intimated response to customers, by understanding and building upon their intent and needs.

While branded skills like, “Alexa, what’s the Forbes quote of the day?” are specific only to a brand, it is the generic skills that are more challenging to capture. For example, if someone says, “Alexa, give me the latest news headlines”, there are millions of websites that provide the information but Alexa will read out only from the first search result, or curate it from a select bunch of sites.

However, if you are a media company that captures this generic skill, you become the sole owner of it. This means that next time someone asks “Alexa, give me the latest news headlines”, Alexa finds your skill to be the most suitable to answer this query. So your brand is the one that’s providing the answer, increasing your engagement with the audience. And even when people who are not currently your reader/audience, use this generic command for Alexa, they are exposed to your branded content, allowing you to rapidly expand your reach.

This single-owner model has created a rush among enterprises to capture the skills before they are gone. The race, as they say, is on.

Why Alexa Skills

Andrew Ng of Baidu estimates that 50% of all searches will be completed either via speech or image search by 2020. Besides, the Alexa Skills marketplace has also surpassed 30,000 in the US in just two years.

If enterprises do not see these figures as an opportunity now, they will face it as a threat in the near future as competitors gain the first-mover advantage, and capture critical generic skills. With enterprises like Uber, CNN, Starbucks and Techcrunch already in the picture, it only makes sense for your business to tap into the market before it is too late.

Besides, Alexa skills can help your enterprise achieve the following:

Increased engagement with customers

The use of Alexa skills will help in creating a unique content experience for the customers where they will be able to gain all the required information at one place, and complete everyday tasks like add things to their shopping list, or book a ride. For example, the Uber Skill can help them order an Uber by simply downloading the skill on their device and saying, “Alexa, ask Uber to request a ride".

Similarly, they can use other travel skills for their commute, Domino’s skill to order food and Audible’s skill to read books. These types of easy-to-use skills, makes your brand very accessible to the customers, lead to significant increase in engagement, as well as attract new customers.

Catering to new content consumption needs

With the help of new innovations in voice tech, brands can help users by providing them a skill that could organize their lives better.

For example, a fashion brand can come up with a skill that can take customer requests about the kind of clothes they require for an occasion, and suggest relevant outfit options from the brand’s collection. And these services can be generic skills, activated with simple commands like, “Alexa, find me the right outfit.”

How to approach Alexa Skills

There are currently over 25,000 skills on Amazon Alexa in the US and with companies in the race to launch their skills, it can be quite difficult to stand out. Enterprises can think about their Alexa Skills strategy in a few different ways:

Use the skills that already exist

You leverage existing generic Alexa Skills that syndicate content to answer specific queries. For example, the Alexa Flash Briefing skill curates headlines from various publications. If you are a media company, you can get your content to list for this particular skill.

While this strategy is a good starting point, in terms of getting your brand before the right audience, it has a drawback. Getting listed on a skill like this does not allow you to access any data on user interaction with your particular content.

Create a branded skill

Branded Alexa Skills are one of the best ways to engage your audience, especially for brands that offer a particular service, like ordering food, or booking a cab, opening a bank account.

For example,

  • BFSI enterprises already have their apps to ensure easy access for customers. These can also be transformed into branded skills that can allow customers to achieve tasks and receive information with single commands.
  • Branded skills could also be explored by B2B enterprises, to streamline internal operations, and save time and money. Like a retail company’s branded skill which can help them track inventory and receive crucial updates, all through a voice activated feature.

Branded skills allow you to extract and analyze a range of user data as well, which can be funnelled into creating more personalized responses and improved experiences. The only hiccup is skill discoverability - the fact that your users have to first know that your brand has an Alexa skill, and then download it on their devices.

Capture a generic skill

Generic skills are where the race heats up. “Alexa, give me the top financial news”, or “Alexa, suggest a good mystery novel” are simple commands, not demanding the user to add any brand name to the query. These name-free interactions are easily discoverable, and naturally integrated into users daily lives, which is what makes them prime property.

Amazon’s current single-owner model means capturing a generic skill give your brand sole access to answer a particular query. And once you own a generic skill, you can access complete usage data and leverage that to improve customer experience.

As enterprises realise the potential of generic skills, they are rapidly capturing these skills. So if you spot an opportunity here, you need to move fast or someone else will.

As of now, industry specific news feeds are one of the high-value generic skills that are still open. And your brand can capitalize on this irrespective of whether you are a media enterprise or not. Being the sole provider of top news feed for your specific industry can bring your brand in contact with a significant section of your target audience. And that is too valuable an opportunity to miss out on.

How to build an Amazon Alexa Skill

Now that we’ve established the value of Alexa Skills, the next question is how you can build these for your enterprise, or rather who would do that for you?

While Amazon has built a toolkit to help you develop Alexa skills, you can also get them built through third party solutions. One benefit of using a third party developer is that it saves time and helps you build your skill once and submit it to multiple devices. Using a third party solution can definitely accelerate your launch process, especially if you are just venturing into the voice arena.

The market, as they say, is ripe. Developing even a basic skill now can give you a first-mover advantage, and make your skill a habit for your customers.

Srijan teams are already building Amazon Alexa Skills for diverse use cases. As a Standard Consulting Partner in the Amazon Web Services Partner Network, Srijan has certified AWS professionals who can help you build Alexa skills specific to your business area. Let’s get the discussion started on building your very own Alexa Skills.

Topics: Machine Learning & AI, Enterprises

Enterprise Chatbots: The possibilities beyond customer service

Posted by Gaurav Mishra on May 2, 2018 3:11:00 PM

Over the last few years, the mobile application was a must-have piece in the market strategy for both start-ups and incumbents. And while it’s still essential, there’s a definite paradigm shift happening from applications to chatbots. 

By 2020:

 

A large part of the discussion around chatbots is focussed on how these automated conversational interfaces can enhance the customer experience for brands. They can ensure a 24x7 responsive customer service that solve customer issues, guide customers to conversion, up-sell products and services based on the context.

enterprise chatbot

However, the impact of chatbots extends well beyond customer interactions. There are a host of enterprise processes and operations that can be streamlined with the introduction of bots. A few key use-cases for enterprise chatbot across industries would be:

Business Intelligence

About 70-80% of enterprise BI projects fail, and a key reason for that is low adoption rates. BI software today, while extremely powerful, are not really easy to master. While there is a lot of in-depth analysis that can be done on your dashboard, does every stakeholder know how to extract the data they want? Probably not. And hence the low usage rates.

Moreover, attention spans are short and executive do not have a lot of time on their hands to manipulate report dashboards to get the insights they want. They are seeking answers to very specific questions, and want the answers in real time.

enterprise chatbot for BI

With bots as an interface between the BI software and stakeholders, access to information can be simplified. You can simply ask the bot “What were the sales numbers in New York last quarter?”, and you will have an answer. No more filters to apply, no date-ranges to select, no login to the dashboard. Such access to data is extremely valuable for busy executives and allow them to focus on their core work. 

These enterprise chatbots can be designed and trained to answer increasingly complex questions. And generate relevant insights and action items for the user, based on the question they ask. They can fit into a variety of business applications that channel data, like IoT systems, marketing automation dashboards, sales reports, operational portals and more. This kind of asked-and-answered approach makes it easy for everyone on the team to leverage these BI software or other data sources to their full potential, and actually practice data-driven decision making.

Bots for the Developer

This one might be specific to technology or product companies, and is one of the most pertinent uses cases for adopting bots within your enterprise. 

Collaboration and communication is a cornerstone of DevOps, and chat platforms like Slack are the place where this collaboration is happening. However, this collaboration can be further improved when chat platforms become the new command center of sorts. This means your teams no longer just receive an alert or issue on the chat platform, but can actually perform fixes without leaving the platform. They can command a bot, by simply typing into the chat platform, and the necessary action/fix will be performed by the bot. Bots can also independently identify issues, handle escalations, and prompt necessary action items to the right team members.

This is ChatOps, where bots like Hubot, Lita, or Errbot help monitor and orchestrate the delivery pipeline with intelligent coordination and execution capabilities.These bots can be designed and tweaked to suit your particular scenarios and workflows, and can take over a  significant amount of mundane monitoring, alerts, issue prioritization, and even simple fixes like start/stop environments, and rollbacks and roll-forwards.

Human Resource Management

Enterprise HR teams have a bunch of repeated tasks and processes that can be automated with bots. 

Access to Information

One of the most prominent areas would be easy access to all company policy documentation. Instead of having to personally ask HR executives, employees simply put their questions to a bot built specifically for this. The bot can direct people to the right documents that would sufficiently answer their question. This means quick access to information, with time saved all around.

enterprise chatbot for HR

Employee Onboarding

Instead of the HR team being personally involved in onboarding employees or freelance staff, bots can guide them through the process. The complete process is built into the logic of the bot and it can lead new hires through a series of questions, task completions, and other helpful videos and documents to complete onboarding.

Micro-learning

Similar to onboarding, employee training and professional education courses are also a great application for chatbots. Instead of a set of dry course material and videos, the bots can make the process more interactive. Increasing the complexity of these bots, to incorporate AI, would give them the ability to run micro-learning courses at a pace that is customized to the capabilities of each employee.

Employee Data-Gathering

Currently, HR rolls out surveys that ask a number of questions, via email. And more often than not, these go unfilled. A well-designed bot can make the process more immediate and interactive, giving better chances of collecting meaningful data. Also, given the existing interactions between bots and employees, there’ll also be a lot of immediate employee data points available by analyzing these interactions. 

Other HR operations like travel and ticketing, time-logs, tracking leaves, and reporting can all be simplified with specialized enterprise chatbots. Field teams dispersed across geographies can also resolve common operational queries, easily access data on the go, and complete and update tasks remotely; via interactions with chatbots.

Intra-organization Communications

Working in teams means a huge amount of time being spent in coordinating with the team members. And this coordination can now be automated, with chatbots working as virtual assistants for each employee. You simply have to ask a chatbot to set up a meeting for you. Accessing someone’s calendar, looking for a free time-slot, scheduling the meeting, adding reminders etc. is then completed by chatbots talking to each other.

Similarly, company-wide updates, access to current news and events, and a host of other essential but repetitive communications required between teams can be handled efficiently by chatbots.

The core benefits of introducing chatbots into enterprise operations, are the same as customer-facing bots:

  • Anytime, anywhere access to required information 
  • Free up valuable resources from mundane tasks
  • Simplify and accelerate the execution of a number of tasks
  • Save time and money

 

Once the diverse use cases and possibilities are understood, the next step for enterprises is to identify exactly which of their processes can be supplemented by chatbots. Enterprise teams will also have to decide between using available platforms for building their bots or building one from scratch, the natural language processing (NLP) engines to be used, designing the bot logic and decision trees, and training bots to perform at scale. There’s also the aspect of measuring the efficacy of these bots, and zero in on the exact metrics to be monitored to track bot performance.

While this might look like a lot to go through before getting started with chatbots, let’s take it one step at a time. 

What is the one business process at your enterprise that can be handled by chatbots? 

Srijan's enterprise chatbot development services can help take your chatbots from concept to implementation. Book a meeting with our Chatbot experts to explore exactly how we can make that happen.

Topics: Machine Learning & AI, Enterprises

The first steps to adopting Robotic Process Automation for your Enterprise

Posted by Poonam Lata on Apr 23, 2018 12:20:00 PM

With a projected market size of 2.9 billion USD in 2021, Robotic Process Automation(RPA) is a term that’s on the digital transformation radar of most enterprises. Put simply, RPA is a type of software application or bot that can imitate repetitive human tasks, and perform them continuously, faster, and without errors.

This delivers certain key benefits to enterprises:

  • Cost Savings: One of the most upfront benefits of RPA is the reduction in expenditure on back office processes. This is a result of the lower number of resources required for these tasks, and also because of the economies of scale achieved by automation. By most estimates, RPA adoption can lead to anywhere between 40-75% cost saving, when adopted at scale.
  • Zero-error Processes: Security and compliance are critical for enterprises, especially in regulated industries like banking and insurance. Lapses here can be disastrous, and also very expensive for organizations. But bots, when designed well, do not make mistakes that human are prone to, and hence automated processes can guarantee security and compliance.
  • Re-deploy workforce to high-value tasks: Automating mundane tasks gives enterprises the freedom to re-skill the existing workforce and deploy them to more value-added tasks. Besides being less expensive than hiring new resources, this re-deployment also gives employees the opportunity to engage in more productive and innovative projects.

 

Despite the benefits, getting started with Robotic Process Automation is easier said than done. The resistance here is two-fold:

  • There is resistance from the top of the organization who view RPA as an expensive exercise that will be displacing a system that has worked reasonably well for decades. While the cost saving aspect would be understood, they would want to see actual ROI before they are completely on board.
  • The second challenge is the workforce assuming that RPA will lead to loss of jobs. And while this is true to the extent that certain jobs would become redundant, RPA does not immediately lead to a slew of layoffs in the organization. 

 

Here, we will deal with the first challenge, and lay out the best course of action to demonstrate ROI from Robotic Process Automation.

Step 1: Find the Right Process to Automate

Selecting the right process for automation is critical to the success of your RPA project. The process you choose has to be balanced between simple enough to automate for a pilot project, while having enough business value or high volume, to showcase discernible ROI.

While identifying the suitable process to automate, here’s what you should be looking out for:

  • Structured and Repetitive processes: The process should be a well structured one: a set of tasks that can be completed in a fixed series of steps, and then repeated over time. 
  • Rule-based processes: The process, when broken down to the basics, should present a series of if-when decisions, taken according to a set of rules, that can be automated. 
  • Stable and Optimized processes: The worst thing to do for an enterprise would be to invest good money in automating a broken process. So ensure that the process you choose is the most optimized version possible. However, there have been instances where organizations pick a sub-optimal process and attempt to fix it simultaneously with automating it. And that can be a recipe for disaster, as it increases the complexity of the process.

 

A key thing to remember at this stage is that not everything needs to be automated. Even within the process you choose for RPA, there might be parts that will need manual intervention, that is par for the course. Automating even sections of a process at the pilot can brings in significant time and cost savings.

Step 2: Do a Pilot Run

Once the process is chosen, the next step is to set up the automation and see how it performs. This stage is about building the base automation system, and testing and iterating till it achieves process efficiency. 

You will also have to give some thought into evaluating the team and the tools to be used.

TEAMS

For this, you can have an:

  • Internal team that evaluates your process, takes it apart, builds the automation application. 
  • Outsourced team that has expertise in building Robotic Process Automation solutions

 

While choosing between the two options, you should weigh in the fact that while internal teams might have better understanding of your processes, they would be new to the tools and technologies involved in RPA. An outsourced team would bring in a certain level of knowledge, experience, and speed into the project. So enabling them with a thorough understanding of the processes would be needed.

Tools

If you are bringing in an outsourced team for your RPA project, they will have their own set of tools and technologies that work best for your requirements. However, if you have an internal team working on this, then you have to choose between commercial or freely available RPA tools. These help you build your process map and based on that, the automation software or bot.

A few common mistakes that organizations make at this stage:

  • Missed coordination with IT: Because RPA involves the adoption of new technology, enterprises often assume that the IT will lead the charge. However, enterprises teams have to realize that RPA solves for business problems, and hence should be business-led. At the other end of the spectrum, we also have teams that do not loop in IT at the right stage. While IT does not take the lead on RPA projects, they should be in sync with the team that’s building automation systems, so they can build the necessary environments at the right pace.
  • Traditional Delivery Models: Delivery models like the waterfall would not be effective in an RPA project. Since the entire pilot is focussed on “build-test-iterate”, traditional delivery models would only be a roadblock in the process, and increase the time taken to get to the implementation stage.

Step 3: Change Management

RPA adoption will provoke a series of changes in job roles, processes, and policies and enterprises should be prepared to deal with that. A few aspects that need to be planned for:

  • Re-assigning Workforce: As RPA automates back office processes, segments of the workforce are now free from some of the tedious time consuming tasks. Enterprise team have to plan ahead so these employees can smoothly transition to newer or value-added roles.
  • Integration: While RPA will definitely mean new systems to work with, it should not be responsible for completely upending established processes. Once implemented, RPA bots should be integrated with existing systems to ensure continuity and ease of use.

Step 4: Measure ROI

The final step for a pilot Robotic Process Automation project would be to evaluate the ROI. For this, enterprises should start with three basic metrics:

  • Speed: How much time does a process take, from start to finish, with the implementation of RPA?
  • Scale: What is the increase in number of task completions within a set timeframe, with RPA? 
  • Quality: What is the percentage of error in a set number of task completions? If the bot has been designed correctly, this percentage should be zero.

 

When done right, RPA implementation should show clear gains across all these metrics. That, combined with the reduction in resources required to run the process at peak efficiency, should ideally outweigh the initial investment in RPA.

While the exact ROI calculation will be different for each enterprise, basis the complexity of their processes, these metrics are a good starting point to think about gains from RPA.

Once your pilot RPA project is shown to deliver tangible ROI, it’s time to scale it up. This would be both in terms increasing the volume of tasks handled by your pilot project, as well as expanding RPA to more enterprise processes. Large enterprises could also start developing Automation Centers of Excellence(CoE), which would be capable of evaluating business processes suitable for RPA, creating RPA solutions for diverse business processes, and towards standardizing bot governance and control within the enterprise.

Looking to get started with RPA at your organization? Explore our webinar session that takes you through the basic steps to setting up robotic process automation.

Srijan enables enterprises set up near-zero-error RPA solutions that can simplify and accelerate business processes. Sit down with our automation experts to identify RPA opportunities at your enterprise.

Topics: Machine Learning & AI, Enterprises

How Edge Computing for IoT is set to impact Businesses

Posted by Sriram Sitaraman on Feb 14, 2018 4:29:00 PM

Connectivity has rapidly evolved from connected people to vast networks of connected things (IoT) including industrial machines, a variety of equipment, controllers, and sensors. With data scientists treading to harvest benefits, machine data are typically transmitted to a centralized computing location in the cloud.

The volume of data produced in IoT networks is massive. For example - a Boeing 787 generates 40 TB per hour of flight whereas a large retail store with IoT infrastructure gathers 10 GB per hour. Sending massive volumes of data to the cloud, even if technically doable, is both cost-prohibitive as well as impractical due to computational capacity requirements, relevancy, and network latency for critical actions.

This is where edge computing for IoT comes into play. The concept of edge computing refers to creating computing capacities nearer to the source/ consumer. The most familiar use of edge computing is- locally processing data that’s relevant near source or consumer to reduce the traffic to the central data-center, and mitigate latency where real-time response is required.

egde-computing-workflow

How Edge Computing will impact businesses

The speed and agility benefits of edge computing are so great that in coming years IoT-created data will be stored and acted upon close to the edge of the network rather than in their centralized data centers. It would not bring surprises if equipment manufacturers started building edge-computing capabilities into devices and sensors themselves over the next few years.

A research firm IDC estimates that “by 2019, 40% of IoT data will be stored, processed, analyzed, and acted upon close to or at the edge of the network.” Here are some ways edge computing will impact businesses: ·

  • Real-time response times: Faster or real-time response is a necessity in most applications of machine learning that involve time-critical action points such as artificial intelligence, robotic process automation, connected cars, M2M communications, etc. The inability to respond in real time could mean loss of business, functional and safety issues. With the ability to process data at the source or nearer to the source, edge computing enables to act immediately. For example – a driverless car with the ability to process sensor data within the car to apply brakes, accelerate or maintain a certain speed, a production line machine turning itself off due to parts failure. ·

  • Dependable operations: Most of the data is processed at the source or nearer to the source, that does not need internet connectivity at all times. Edge computing enables equipment and other smart devices to operate normally without disruption even when they’re offline or Internet connectivity is intermittent. This makes it an ideal computing model for businesses that count on the ability to quickly analyze data in remote locations such as ships, airplanes, and rural areas—for instance, detecting equipment failures even when it’s not connected to the cloud.

  • Cost savings: Data that has local relevance is processed at the edge of the network, reducing the amount of data that is sent to the cloud. Reduction of traffic to the data center in the cloud saves data transaction costs (back and forth between sources and cloud) as well as the need for higher computing capacities at a centralized cloud.

  • Secure and compliant: Edge computing helps to address the security and compliance requirements that have prevented some industries from using the cloud. With edge computing, companies can filter out sensitive personally identifiable information and process it locally, sending the non-sensitive information to the cloud for further processing.

  • Interoperability between new and legacy devices: Edge computing converts the communication protocols used by legacy devices into a language that modern smart devices and the cloud can understand, making it easier to connect legacy equipment with modern IoT platforms. As a result, businesses can get started with IoT without investing in expensive new equipment—and immediately capture advanced insights across their operations.

cloud-vs-edge-mainenance-cost

Cloud Computing and Edge Computing

It’s expected that by 2020, up to 65% enterprises will use IoT. This means more complex networks of connected things including multitudes of machines, equipment, and devices that will produce a mindboggling amount of data. Most of the elements in these networks will require a faster processing and real-time response that centralized processing in the cloud simply can’t fulfill.

Edge computing will be able to deliver quick processing requirements and mitigate latency, intermittent connectivity and computational challenges in processing a vast amount of data. Cloud computing is going to stay but it will act more like an off-site location to draw patterns, forecasts, and reporting while handing over immediate processing to edge computing.

In the current landscape of industrial IoT and the pace it’s growing – it’s imminent that edge computing is going to take a lead pushing cloud computing to the second place, in near future.

Edge Computing - A complement to the cloud

Most industry experts are calling edge computing a successor of cloud computing that will have a symbiotic relationship with each other. We foresee the emergence of a strong relationship between cloud and edge computing, in which each will handle data for different computing tasks and data types while complementing each other. While edge computing will serve time-sensitive data for immediate intelligence within or closer to the device itself, the cloud will handle data intended for historical analysis. The next wave of the business transformation will be the Edge computing. The time to prepare for the future starts now, to avoid the risk of getting left behind.

Take a closer look at how Edge computing is being implemented, and specific use cases across industries.

Looking to evaluate your IoT and edge computing requirements? Write to us and let's explore how our expert teams can help.

Topics: Data Engineering & Analytics, Enterprises

How Travel Enterprises can drive higher conversions with enhanced Digital Customer Experience

Posted by Gaurav Mishra on Jan 22, 2018 11:32:00 AM

Travel has always been about the ‘experience’. In recent years, this ‘experience’ has become a tangible, marketable thing, and the primary factor driving customer choices. And it starts much before the actual physical travel. 

This can be solely attributed to the rise and dominance of digital channels in how we plan, book, and execute our travels. Digital travel sales are expected to touch USD 817.54 billion by 2020. 

How Travel Enterprises Can Drive Higher Conversions with Enhanced Digital Customer Experience

Travel enterprises, be it hotels, airlines, booking websites, or travel agencies, are all cognizant of this fact. That’s why we see the rise of Digital Experience Leaders or Strategists, who are tasked with two key responsibilities:

  • Increase leads and conversions via digital channels

  • Steadily increase the share of revenue from these channels

 

The key to achieving both these goals lies in creating a compelling digital customer experience across all channels. And while the core principles of ensuring smooth user journeys and offering a customized experience remain intact, the manner in which they are being delivered has evolved greatly. 

Download our Travel, Tech, & Transformation ebook to stay on top of industry trends, and leverage emerging tech to ride the travel industry growth wave.

 

We take a look at the technology and business interventions that travel enterprises should focus on, to offer digital customer experiences that stand out.

Frictionless Customer Journeys

The first requirement for a satisfying customer experience is to offer a smooth user journey, where they intuitively know what to do next. Your digital channels should anticipate everything they need to make their decision, and have it readily available. 
Some of the aspects that digital experience leaders should be paying attention to are:

Third-party integrations

From researching a destination, to booking flights and hotels, to planning itineraries, your digital channels should be prepared to offer a host of functionalities. So whether it’s payment gateways, or financier applications, or social media channels: third-party integrations are crucial to offering a complete customer experience.

Microsites

Customers research destinations online across various sites to arrive at a final choice. Rich images, videos, cultural and historical information about the place, heavily influence traveler decisions. 

Hosting all this content on dedicated microsites is a great way to engage and interact with the audience. These sites can also host user-generated content like reviews, stories, and amateur videos. The idea is to make sure that a huge chunk of the destination research happens on your site itself, increasing time spent on site and chances of conversion. 

Leveraging Mobile

In 2017, 40% of digital travel sales were through mobile devices, and that number is only going to rise in the coming years. Travel enterprises have to ensure that their digital properties are mobile-ready. However, having just that is not going to be enough. 

How Travel Enterprises Can Drive Higher Conversions with Enhanced Digital Customer Experience

Enterprises have to look at these devices as a separate channel altogether. Virgin Hotels’ Lucy, is a case in point. The tagline says Lucy “can make things happen”, and the brand delivers on that promise. From booking a meal or a spa to controlling your room temperature, the app is a perfect digital personal concierge. 

This is a digital channel that can be leveraged by airlines, cruises, hotels, and travel agencies. Applications that bring in a high degree of convenience, while furthering the brand experience, bring immediacy and interactivity that can attract, convert, and retain customers.

Personalization

Generic offers and rewards programs that were a mainstay of the travel industry are on their way out. What’s replacing them is a highly personalized digital experience that permeates everything from the website, to tour packages, itineraries, and in-travel interactions. 
Here are a couple of ways this is playing out:

Content Personalization

Enterprises are putting vast amounts of collected customer information to good use, Complex analytics algorithms are run to transform this data into complete customer profiles. 

This helps them offer a degree of personalization that can range from a simple “Hi Sarah” when she opens a website, to a complete microsite that has information on Sarah’s favorite destinations, tour offers at custom prices, and even booking options for pet-friendly hotels for her dog Max. 

Personalized content creates immense value for the customers, because it provides them exactly what they want. Once again, Virgin Hotels seem to be doing all the right things with their “The Know” program, that simply asks customers for their information, so they can custom-design travel experiences.

Chatbots

By 2020, 85% of enterprise interactions with consumers will happen via chatbots. Retail brands are already implementing chatbots that can help customers get to the right buying decisions via a series of questions.

For travel enterprises, these are the perfect balance between handling a huge site traffic while still being able to offer a degree of personalized interactivity. They will work pretty much on the same principles as choosing a destination, dates, and budget filters on a site. But the fact that customers will have the ease of typing things in, like a natural conversation, and then get a customized offer, is what makes chatbots a great investment.

IoT

The Internet of Things is being employed by enterprises to eliminate stress factors from the customers’ travel experience. Hotels are using a connected devices ecosystem to know where guests are on the property, anticipate needs, and offer personalized service. Airports are using RFID chips for luggage tracking, and motion sensors to estimate passenger wait times. 

Less time spent worrying translates into more money spent enjoying the services on offer. While this definitely boosts revenue, the experience also prompts return visits and referrals.

Yes, setting up a sensor ecosystem and implementing the required technology changes can be a significant investment. But the gains made due to the enhanced customer experience, increased efficiency, and improved turn-around times will make it worthwhile. 

Transforming to Platforms

Right now, digital interactions for travel are spread across multiple sites. Given this fragmented market, enterprises that transform into travel platforms will have a competitive advantage. 

Offering varied services on a single platform would make for a convenient digital customer experience. Brands will also be able to collect data around all aspects of the customers’ trips: from the destinations they like, to food and entertainment preferences, to on-tour activities and more. This means more data for the analytics applications, helping them create highly personalized digital experiences, leading to greater engagement and repeat conversions. 

How Travel Enterprises Can Drive Higher Conversions with Enhanced Digital Customer Experience

Adding new service verticals alongside your core business also opens up new revenue streams. Airbnb started offering bookings for local activities in addition to lodging options, and it was a perfect offering for their kind of customers. Often, brands just have to dig a little deeper to find complementary services that their customers will be eager to pay for.

So that’s how digital experience leaders at travel enterprises can meet their twin goals of driving conversions and revenue. 
They will a need a team with the technology expertise to pull off these enhancements. But more importantly, they will need a team that truly understands the nuances of the digital customer experience they are trying to create and the business value that rides on it.

Looking for a team that fits that description? Let’s start the conversation and explore how Srijan can help transform digital travel experiences

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Topics: User Experience and User Interface, Enterprises, Travel & Hospitality

The silver lining: GDPR as an opportunity for enterprises

Posted by Rajat Lal on Jan 8, 2018 4:56:00 PM

With the May 25th, 2018 deadline to get GDPR compliance into effect, enterprises are busy evaluating their data collection, usage, and storage. The penalties for non-compliance are severe, which is why enterprises do not want to be on the wrong side of the law. 

There’s also an expectation that the Information Commissioner's Office (ICO) is looking to make an example of companies that breach the law. Add to that, the fact that firms have to incur additional expenditure to realign their data security practices to GDPR guidelines. 

All this combined has made GDPR seem like a threat to enterprise operations and revenues. In fact, there have been several instances of companies deleting their entire email database, just so they do not have to bother with GDPR compliance.

But maybe there is a silver lining in all this. 

Here’s a look at the opportunities GDPR presents for different enterprise teams:

Data Security Teams

Large enterprises often collect personal data across several touchpoints: marketing, billing, legal, HR and more. Often there’s no single place where all this data is stored, or no standardized security measures around the data collected by different departments. 

With GDPR, enterprises now have to re-evaluate all this data. That’s the chance for the data security teams to tighten the ship. They can set up efficient systems that help legally collect and store data. They can also train departments on how to handle and use the data while ensuring compliance. 

As these systems are put in place, enterprises will also become more transparent with their customers. And that could become a huge differentiator for their brand, earning greater trust and consequently more business.

Marketing Teams

For global enterprises, marketing is the one area that’s really feeling the heat with GDPR. They are having to review entire contact lists, trying to figure out how each contact got into their database. And whether they have documentation to show that contacts opted in.

But the fact that GDPR is forcing marketing teams to closely adhere to people’s preferences for receiving communication, is what makes it an opportunity. Here’s how:

  • Without the option of mass mailing contacts from a haphazardly curated list, they now have to create valuable content that people actively want to receive

  • Their forms now have to reveal why they are collecting personal information

  • They have to document consent through opt-in emails, rather than just giving them an option to opt-out later

 

This puts a stop to bad marketing practices. And also makes sure you get greater returns on your marketing efforts, by communicating with people who have explicitly expressed interested in hearing from you.

Product Teams

For enterprises in industries like IT, AI, IoT, and business intelligence, GDPR presents a huge opportunity for innovation. They can launch new products and services that:

  • Help companies assess their security standards and GDPR readiness

  • Offer end-to-end change management while establishing systems of compliance

Collect and interpret customer behavior data without having to rely on personal information

The demand for these is huge, and enterprises that can launch fast will swiftly consolidate their share of the market. 

Viewing GDPR as an opportunity might not come easy for enterprises. But let’s put it this way: enterprises have to make changes if they are to ensure compliance. And that will be easier to do if they know there are actual benefits for them, rather than just avoiding fines.

Topics: Enterprises

How to chalk out your Enterprise DevOps adoption strategy

Posted by Pavan Keshavamurthy on Dec 15, 2017 5:45:00 PM

There are a lot of steps from product build to deployment, and also a lot of things that can, and do, go wrong. A few of these might sound familiar:

  • The Dev team adds a new feature right before release and the QA team does not have enough time to run the whole gamut of tests. The code is pushed to live and it’s too late before you realize that you missed a few bugs.

  • You update your product and release a new version. It worked fine for the developers and testers, but not when deployed on the production servers. Because the Dev team missed informing the Ops team about updating a library or the database on the servers.

  • Your code is ready to go, but the Ops team says they will need a couple of days to configure all the environments to the given specifications. Or maybe a server goes down, and they take hours to get it back up, manually configuring it all over again.

 

Every product team has faced these challenges at some point in time. If your product development and delivery pipeline is largely manual, the only way to avoid these challenges is to work steady and double check to make sure you haven’t missed anything.

Meanwhile, that new disruptive start-up in your industry has already released the second version of a competing product. They are able to do this because of shorter and faster release cycles, ability to deploy quick fixes for bugs, and recover faster from system failures.

And this is probably why your enterprise has to start looking towards DevOps adoption. If you wish to stay ahead of the curve with your products and services, this is no longer a matter of choice. Besides resolving some of the current challenges your siloed teams face, DevOps is key to a faster product delivery pipeline.

However, enterprise-wide DevOps adoption is easier said than done. There is, of course, the initial resistance to changing established practices. Additionally, convincingly showcasing the value of DevOps to the entire organization is a challenge.

Micro Hering, Principal Director at Accenture, points out one of the key reasons why DevOps adoption is derailed: “Some group goes off and implements DevOps practices (for example the testing center of excellence or the operations team) and they have great successes. Their individual results improve so that the automated regression now runs in minutes not hours and giving developers a development environment from the cloud takes hours not weeks. Yet the organization as a whole fails to see the benefits because the different practices are not compatible or too many dependencies continue to hinder real results.”

Hence, what is needed is a well-planned and executed DevOps adoption strategy, that will produce measurable results. What we suggest is a two-phase roadmap:

Phase 1: Showcasing DevOps ROI
Phase 2: Identifying and Side-stepping the Trip Wires

Showcasing DevOps ROI

To accelerate time to market with DevOps, it has to be adopted by all teams across the organization. And that is easier to achieve when stakeholders get behind the idea of DevOps adoption. So the first step is to demonstrate to all stakeholders how DevOps can bring in significant benefits.

Here’s how to do that:

Evaluate Your Delivery Pipeline

Understanding the existing delivery pipeline is the first step. Get together all the process stakeholders. Map out your pipeline in complete detail, understanding each process, highlighting if it’s manual or automated, and how long it takes to complete it. Identify any inherent cause-effect relationships and dependencies in the pipeline.

Identify Process Bottlenecks

The next step is to identify all the existing process bottlenecks. 

This could be in terms of time taken by the Ops team to configure a production environment. Or the time taken by the QA team to thoroughly test every feature addition. Or mismatch in configurations between development and deployment servers. 

Identifying these bottlenecks helps you and other stakeholders realize that there is a need for adopting better practices. It also demonstrates where the distinct DevOps practices like infrastructure-as-code, automated test scripts, configuration management etc. will fit in.

This is also the right time to identify certain base performance metrics, which will help showcase the improvements made with DevOps.

Choose Your Experimental Set

A lot of times, applying DevOps principles to an isolated process is not enough to convince stakeholders of the benefits. It gets viewed as a one-off incident and not something that would be replicable across the organization.

Your experimental set, i.e. the specific set of processes on which you want to apply DevOps practices, has to be chosen carefully. 

Ideally, it should meet the following criteria:

  • The processes are integrated and need to change together in order to work

  • They are important for the enterprise and whose improvement will deliver significant benefits

  • Can be optimized within a short period of time

 

For example, let’s say you choose server configuration as your experimental set, which will involve:

  • How you configure a development, testing, or production server, and how long it takes

  • How do you update the servers when new product versions are released

  • How fast can you reconfigure a server that went down

 

This inter-related set of processes can be tackled with the DevOps practices of infrastructure-as-code and configuration management. And an improvement in your server configuration times means a huge acceleration in your delivery pipeline. 

Practise DevOps

With your experimental set of processes identified, start integrating DevOps practices from the ground up. The earlier on in the process you introduce it, the better. The key here is to be conscious of the process changes and making sure the team sticks with them. Tight feedback schedules and team’s complete alignment with the final goal would be crucial. 

As you work on optimizing these processes, the benefits of DevOps would start reflecting. In the time taken to delivery, the number of bugs reported, the automations introduced and their impact on performance. These benefits must get documented and mapped against the base metrics identified. 

Now your work is ready to be showcased to stakeholders as an example where DevOps created significant ROI for the enterprise. Once they see the measurable value additions, it’s easier for them to buy into the idea and make a strong push for DevOps adoption across the enterprise. 

Identifying and Side-stepping the Trip Wires

With key stakeholders on-board, the next phase is to make sure you foresee the challenges that can come up, and how to get over those. This involves taking a look at three key factors:

Organizational Practices

DevOps demands close collaboration between Dev and Ops teams and a work culture that is focussed on accepting and correcting mistakes rather than pointing fingers. This kind of cross-team cooperation could be difficult to get right at the first go. But recognizing the need for it, and enabling it across the organization is the first step here.

Enterprise teams should also consciously extend the development methodologies of agile, to the operations teams. This allows both teams to communicate in stand-ups and retros, building a greater understanding and collaboration.

Legacy Modernization

Here’s where most enterprises trip up because they feel:

  • DevOps practices would only be effective with modern applications and platforms

  • Legacy modernization would mean completely doing away with the old architecture, which will involve significant expenditure

 

However, DevOps practices can work as easily with legacy platforms as with modern ones. Continuous integration, one-touch deployments, agile release cycles are all possible on legacy platforms, with the right tools.

Moreover, legacy modernization does not always mean an expensive upheaval. In most cases, it can be achieved through adapting your heritage systems to modern methods. And DevOps practices can actually let you do this faster and in a more efficient manner.

System Reliability

The speed of delivery achieved through DevOps often raises concerns around system reliability.

As a concept, DevOps embraces failure as inevitable and concentrates on designing systems that can get back to work fast, after a breakdown. There are examples like Netflix’s Chaos Monkey, that are designed to trigger randomized system failures. This pushes their teams to build systems that are capable of healing fast in such conditions. 

So DevOps moves beyond reliability, towards achieving more resilient systems.

While this two-phase roadmap is a great starting point as enterprises start thinking about DevOps, you will have to tweak it suit your particular organization. 

There are, of course, a lot of decisions to be made once you start down the DevOps way. The most important of those is choosing the right DevOps toolchain for your teams. This is also where  DevOps consulting services like ours could lend a hand. 

Let's start the conversation about how we can power your competitive advantage with DevOps.

Topics: CI/CD & DevOps, Enterprises

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