September 2021 - TVS Next

A Leap into the Cloud

Alex Thompson Data and AI September 8, 2021

A Guide to Persuade Your Entire Organization to Embrace the Cloud

We don’t need to educate people about cloud anymore. The technological aspects of cloud migration, such as choosing a hybrid cloud or omni cloud model, and running serverless applications that are cloud-native, are oft-talked about.

And yet, Gartner predicts that lack of cloud skills will delay organizations’ cloud adoption process by two or more years.

When it comes to convincing apprehensive members of your organization that cloud adoption is a necessary step for digital transformation, you have to deal with two different groups:

Skeptical board members &
Reluctant employees

Here’s a guide on how you can do it:

1) Audit Existing Applications

Before you embark on the cloud migration journey, the first step is to audit your existing IT infrastructure. Find out the bottlenecks of your existing system, and causes for operational issues and delays. Assessing your applications will help you identify what needs to be changed immediately, and what can be continued to be put to good use. A complete re-engineering of the entire organization’s technology infrastructure might not always be required. Sometimes, retaining some applications as-is might save a lot of time and resource.

2) Present Business Needs

When discovery and assessment of your existing infrastructure is complete, it will give you a better understanding of technological gaps and issues that require addressing. This will help you formulate a business case that specifically meets your organization’s needs. There are multiple business benefits to migration such as decreased IT spending for infrastructure, software and maintenance, and improved security, accessibility and process streamlining.

3) Explain Risks

The necessity for future proofing businesses has never been more realised than since *you-know-what* happened. Explain to your stakeholders about how failing to innovate could potentially bring your business to a standstill during unforeseen circumstances. Also explain the risks of being the business that’s left behind without modernizing while all your competitors advance with the aid of technology.

4) Identify Pain Points

When people are reluctant to trust new technology, there’s often a valid reason behind it. Members of the older generation may feel that they do not have the skills and abilities to quickly embrace the technology change. It’s important to deliver a solution that is not too complex for use, and when the new tools or applications directly meet their needs, many members of your organizations will readily embrace the change.

Not providing adequate training to all your members could also be another issue that might slow down the process. Include orientation and training programs as a part of your migration strategy, and also provide simple guides for people to refer to until they get used to the new system.

5) Throw Light on Individual Benefits

For the business stakeholders, decrease in spending, increase in profits, better security, higher productivity & operational efficiency and enterprise mobility are very appealing benefits.

For other users, the ability for collaborations anywhere, anytime and from any device, empowering them to truly work from anywhere might be a solid benefit that draws them in.

6) Build a Shared Vision

Cloud adoption might mean different things to people in varying levels across the organization. While helping your team members understand what the benefits of cloud adoption for them may be, it’s also important to build a big-picture of how the modernization project will impact the entire organization as a whole.

Building a shared vision not only means creating a roadmap with your success outlined, it also means creating a project where every team and individual is included. That can be achieved by assigning ownerships to everyone, and including every user from inception till the end. When each person bears a little bit of the weight of the huge initiative of cloud migration, the entire process will seem easy and effortless.

How to leverage automation for business success

Alex Thompson Data and AI September 7, 2021

Organizations very well know the importance of taking the right action at the right time. Be it recruiting a right candidate, or converting a lead into a customer, multiple right actions performed by multiple people combine together to drive the organization’s success. So, what drives these actions? A number of factors such as the available data, experiences and skills of the people involved, their cognitive bias, and also the time required versus the time available to perform the action.

What if the negatives of individual decision making could be removed altogether, and only the positive aspects are harnessed to perform the right actions at the right time? That’s what automation is all about.

For different parts of your organizational engine

Everything happening in an organization can be automated to a certain level. How do you know if something can be automated? Any function that requires a certain process to be followed can be automated. Here are some automation examples:

Human Resources

The HR department is a very valuable asset to every company, for they bring in every employee and make sure everyone is paid on time. Some of the automation possibilities in the HR department include:

Sourcing the right talent meeting the company’s needs
Onboarding and offboarding automation
Automating time logging, leave requests and payroll processing
Defining the KPIs and letting bots find out the top performing employees

Finance

Accounts payable, accounts receivable, cash-flow management, maintaining balance sheets, invoice generation are some of the many automation possibilities within the finance department. Automating finance operations has the added benefit of ensuring accuracy and preventing human errors.

Sales & Operations

Salespersons can leverage automation to schedule appointments, send emails, resources and reminders. AI based chatbots on websites are available 24/7, expanding a company’s horizons across countries and beyond time-zones.

Tech Support

Anybody in IT would know that most of the support tickets are pretty repetitive: Access request, license request, password reset request, or asset request. By automating such service desk tickets, the workforce engaged to provide tech support on shift-basis could be deployed into more valuable projects.

Marketing

Marketing automation entails automated campaigns, dynamic content that changes based customer persona, contact segmentation for better targeting, and research and development. In all, marketing automation saves money by knowing where to spend it, without the hassle of hundreds of hours of research into targeting.

When every business function is automated, not only does it save time and money for the organization, it also frees up skilled workforce to engage in more valuable work that requires human intelligence. Automating repetitive tasks also ensures process compliance. Futuristic businesses have begun delegating work to bots and automation.

Interested in how automation will fit into your business case ?

Empowering Quality Assurance With Artificial Intelligence

Alex Thompson Digital Engineering September 3, 2021

Artificial Intelligence has crossed its nascent stage and is gaining rapid momentum. Organizations are looking into investing in AI for immediate intelligent insights that will result in long-term cost savings. Gartner predicts that augmenting artificial intelligence will create $2.9 trillion of business value in 2021 alone.

There has never been a better need for Quality Assurance than now. All kinds of applications are constantly being released and are continuously updated to provide more functionalities and better experiences to the end user. QA teams are expected to be agile, multi-skilled, be involved from the beginning of the development, and deliver high quality.

Leveraging artificial intelligence in quality assurance is a new wave to help QA engagements become predictive and analytics-based.

When it comes to combining quality assurance with artificial intelligence, it can be done in two ways: using QA while building AI & using AI to build QA.

Using Quality Assurance while building Artificial Intelligence

84% of CEOs think that AI-based decisions can be trusted only if they are explainable. More often than not, AI systems are not trusted easily.

For an artificial intelligence system to be deployed, it has to be proven accurate, secure and reliable. Building such an AI model is no easy task. It involves lots of data training, and rigorous testing and tuning. This process requires highly skilled domain-aligned QA to make the training success.

Using AI-empowered Quality Systems

Quality assurance automation has already been a key tool for many software building enterprises. QA automation software is used to make the product market ready at lesser costs in shorter intervals.

Bringing an AI-empowered quality system with superior predictive capabilities into the automated testing arena elevates the testing approaches and takes quality assurance to the next level.

Some QA use cases where AI can empower QA teams

High accuracy

Even the best QA teams could possibly overlook some defects during the most proactive quality control processes. This issue can be resolved when using artificial intelligence in inspection to help the QA teams. QA teams can leverage the test cases generated by AI based on pre-conditions and past coverage and reduce software bugs.

Predictive Analytics Based on Pattern Recognition

Rather than testing after the code has been written, artificial intelligence can predict potential defects that could occur in a particular module. Based on previous defect history, it can predict which team or person is likely to produce more bugs in the code. Thus, making a huge impact on achieving proactive quality.

Root Cause Analysis

When large or multiple teams are involved in building a software, although ownership may be assigned to each team/individual, it is difficult to point to the origin point of a defect. AI can be used in this case for software quality assurance to find the root cause of the issue, and point to the team or member who can fix the issue, thereby saving time for everyone involved.

Faster Release Cycles

Artificial intelligence testing can generate results very quickly, even for large codebases, thereby reducing the product release times. The bot can run unsupervised during nights, and developers can begin work the next day based on the results of the AI testing.

Test Data Generation

Test data generation takes up a lot of time during software development cycles. This test data is used to test the software and ensure that all the components are working as expected. AI can be used to generate test data that is very close to actual production data that will be fed when the software goes live.

Conclusion

In a highly competitive digital landscape, it’s important to stay relevant and deliver unmatched user experiences, regardless of whether you’re a B2C or a B2B business. Augmenting quality management through AI-driven Quality assurance is an integral part of running businesses of the future that can help mature your QA teams from being a reactive QA organization to a proactive & cognitive QA organization.

With TVS Next as your AI-based QA partner, you can deliver products and services that stand out among the rest and with business clarity through scalable quality management systems. To know more: