There is hardly any business today that does not utilize IT to run some or all of its processes. From customer-facing channels to internal processes such as finance, human resources, engineering, administration, marketing, sales, and many more, IT is deeply integrated into every aspect of an organization. Since technology impacts every facet of the business, modern CIOs are facing many challenges to keep pace with the organization’s demand for technology transformation and enablement. This has led to the demand for quick turnaround time and agility while implementing technology projects to help accelerate operations, pace of innovation, and response to changes in the market dynamics.

A McKinsey research shows that about 50 percent of tasks are automatable with the technology available today. That leaves another 50 percent tasks that are non-automatable including the decision-making steps, interactions, and handoffs that analytics and other technologies can improve but not entirely put on autopilot. 50 percent is a good number to start with.

“57 percent of businesses have already started on an automation journey, with another 18 percent planning to kick-off something within the next couple of years.”

• McKinsey Automation Survey

In this article, I will discuss various dimensions for the CIOs to consider to achieve this 50% automation target by adopting the “Automation First” approach.

The “Automation First” Mindset

Adoption of automation is becoming more critical for quick response to the competitive marketplace, but the success depends on how you go about bringing the transformation within your organization’s mindset. Given the fact that automation has been related to job cuts and redundant workforce over the past years, it’s a difficult and uphill task; automation is the only mindset through which you can thrive in the ever-changing world of technology. You need to create a balance and foster an atmosphere of re-skilling your workforce to bring better value without sacrificing the bottom-line. The atmosphere where all your departments and teams come together and adapt to the idea of “Automation First” is the initial step towards achieving this mindset. As a CIO you can help by creating a strategy that revolves around some basic pillars:

• Lead from the front: To achieve this goal at an organization, the leaders would have to adopt it first and create stories about the adoption of automation in technologies within the teams.
• Empowering people: Traditionally, the workforce had accepted manual processes as part of their BAU jobs; we need to empower them to break that mindset and invest and innovate in ideas to bring in automation into all the mundane tasks.
• Re-skilling / upskilling and creating new opportunities: Re-shaping and bringing in the tools for automation and collaboration among the workers together with re-skilling them on these tools would motivate and spread the culture around. At the same time, CIOs are responsible for identifying and exploring new opportunities that make it possible for them to fulfill their future aspirations.
• Organization strategy: Automation must be built into the goals of the organization as well as the goals of the workforce.

The “Automation First” Approach For IT Activities

Making IT processes more efficient and effective should always be prioritized. When implemented correctly, automation can increase the speed and accuracy, and thus eliminate mundane operational tasks from the shoulders of IT personnel.

As a CIO, it’s important to transform the organizational workforce to focus on higher-value work, eliminating the need for them to do routine work which can be fully or partially automated. There are various ways of doing it by leveraging new evolving technologies and tools. CIOs should encourage the teams to adopt automation first approach during the Software Development Life Cycle to accelerate application development, testing, release and deployment process, security testing, monitoring, IT infrastructure management, and application delivery. Each team needs to think about automation first while doing their day-to-day work and deliver faster to their business owners.

Let’s talk more about the IT automation first strategy, which is needed to bring about change and transformation in their standard SDLC processes:

• Software Designing: It’s not about the tools but the mindset that is important while designing applications. The team must think of modern technologies that can be utilized to provide better automation opportunities when implemented. The design should also be considered based on less human engagement and deploy more automation techniques to accomplish most of the standard business activities. For example, technologies like AI Chatbots replacing FAQs or Live Agents, Augmented Reality or RPA for showcasing products, Artificial Intelligence & RPA to replace standard business processes. Therefore, while designing, keeping such technologies in mind would pave the way for the mundane processes to achieve automation.
• Software Development: Gone are the days where there was a single platform with one programming language used to code the entire software. Think more in terms of multiple platforms and multiple languages suited for each process required in the software. For instance, keeping the cloud platform, micro-service based application in mind and thinking about auto-scaling and auto-healing software that is deployed on cutting-edge containerized platforms like Kubernetes would go a long way in providing the level of automation for build, unit test, security vulnerability test, containerization, and deployment activities, etc. This will give your organization a major advantage to develop and deploy your application faster.
• Software Testing: Automation should be the core of your testing strategy. Think about the automation of all the regression tests, performance tests, or manual tests that take a huge amount of manhours every time you change something or develop a new version of your software. At Maveric, we use our integrated Quality Engineering platform, which provides us tools and expertise for deploying a fully-automated and performance-tuned platform to enable continuous automation in the entire testing life-cycle; addressing all different layers of the application such as UI, back-end APIs, and surrounding system integrations.
• Software Deployment: If you are still taking days getting stuck with manual tasks or need downtime for your business application to deploy fixes, bugs, or new features, then you’re behind the curve. In today’s age, the deployment pipeline should be continuous without interrupting your operations or causing downtimes. Think about how to introduce new features almost every few days. Your software deployment strategy should lean towards DevOps and CI/CD (Continuous Integration and Continues Delivery) model.
• IT Infrastructure Platforms: IT infrastructure management is a broad term, however, to enable better automation from provisioning to production, each stage of the infrastructure management process can leverage relevant tools and techniques to automate most of the activities. For example, if you are using cloud services, you can choose from IaaS, PaaS, or SaaS service models. As you move from IaaS to SaaS, the manual work in your IT infrastructure management process reduces substantially. You need to strike a balance between automation and regulatory compliance requirements as per your industry standards, but there are still a lot of tools and technologies available to make that automation work. Automating the provisioning, configuration, and management of your IT infrastructure will provide you a better competitive advantage and your business can respond to market dynamics faster. Your IT infrastructure management strategy should also lean towards cloud, containerized platforms, DevOps, and CI/CD model.

Conclusion

Setting “automation first” as a goal for a team or a department would never work in the long run. You have to work continuously with all the stakeholders and embed this in the DNA of your organization. You can be assured that with automation at the realm of your organization, much more work would get done. You’ll realize that your company is able to release more software products or features in less time. Your business teams can compete in the market as they have much faster access to data and newer technologies. The leadership and management teams can make smarter, more informed decisions faster. In the end, building the automation mindset across the organization, will reduce your dependencies and risks and help you operate your business in a better, more transparent way.

The word “Transformation” means different things to different people depending on the context you ask that question, and the same goes to the term “Digital”. Therefore, when we talk about Digital Transformation, it is definitely not going to be an easy answer. However, in the context of this topic, I use the definition as “Digital Transformation is the Transformation of Technology which can be leveraged to fundamentally change how you operate and deliver value to your customers”. This article aims to cover some of the common areas around application of DevOps practices and principles and provide certain clarity on how to integrate in your digital transformation journey.

I will take enterprise context such as Banks or Telecom providers. Banks or Telecom providers are associated with large number of end-users / consumers and these consumers are engaged with their service providers through various channels whether it is website, mobile apps, e-commerce apps or social media platforms. Hence it becomes essential to develop and continuously enhance software to support these various channels and platforms with best customer experience. Therefore, to facilitate organizations to innovate fast and give their consumers the best possible experience, the technology and the technology teams need to undergo a huge transformation to deliver this demand.

Since technology and the technology team are going to play a critical role in enhancing organization’s ability to deliver services and increase value to customer, the adoption of DevOps plays an important role here.

Fig : Integrated SDLC flow for DevOps

DevOps will make sure that software meets the desired quality standard, ensures smooth development and deployment process, ensures right balance of security and operational needs and therefore enhance customer’s overall experience.

What role does DevOps play in this digital transformation journey? To answer this question, let’s look at various elements of digital transformation and their relation with DevOps.

Key elements of Digital Transformation where DevOps plays an important role are:

• Customer experience: Customer experiences can make or break your business. So, it is essential to provide a delightful customer experience to them. In my view, DevOps can act as a healer in these circumstances as it allows you to develop, test and deploy software faster and respond to customer feedback better and manages customer expectations.
• New Technology Integration: This one is my favorites because the pace at which new-age technologies like containerization, server-less computing, Artificial Intelligence (AI), and Machine learning (ML) are making their presence in businesses and changing the game altogether. The application of these emerging technologies are forcing organizations to look towards DevOps methodology as they are compatible enough in dealing, managing and testing these models faster and bring their ideas to the reality to serve their customers better.
• Workforce enablement: No one can deny the fact that digital and mobility are changing not just the customer expectations but also the way organizations interact with their customers. So, the organization needs to ensure that its technology team have the right tools and technologies in place to explore, experiment and develop software faster and better. This can easily be achieved with the help of DevOps adoption as it will facilitate automate and optimize their processes and workflow without wasting their valuable time and efforts.
• Operational agility: The speed at which businesses are hitting hard by digital transformation, it becomes essential for them to understand and align these new and changing priorities. By adopting DevOps, the organizations are breaking silos, embracing collaboration and infusing the elixir of agility so that they can deliver better customer experience and at the same time ensure a high level of customer satisfaction.
• Culture and Leadership: Every successful digital transformation and DevOps implementation requires a leader that has an ability to create an environment and culture where collaboration and sharing are encouraged. And this can only be achieved by giving all stakeholders a transparent visibility into every aspect of the process and workflow across development, testing, release and customer feedbacks. DevOps can help to provide relevant data inputs to setup the required telemetry for a transparent visibility.

With plethora of articles on this subject you can easily see confusion around the topic. The main reason for this confusion is attributed to divergent interest of siloed organization, mindset with resistance to change and lack of skills. Therefore, it is important to keep in mind that we need to fundamentally change how we operate and deliver value to our customers. To make it possible, let’s have a look at the other essential technical factors that can help you in building an effective DevOps strategy.

• Automation: Automation is certainly not a curse; it is a blessing. As I have already mentioned above that DevOps is all about breaking down the traditional barriers and streamlining processes. And all this is possible because of automation can pass through all silos to make an end-to-end process and experience better. It will also make repeatable processes error-free and can deliver result quicker with more efficiency.
• Adoption of Open Source Technology: Open source has always been the first choice for DevOps teams as it allows them to innovate faster and at a lower cost. You usually don’t have to pay money to acquire open-source software. That’s why it has become the first pick against proprietary alternatives where vendor locking is one of the basic criteria. Not only this, open-source software is built with the enhanced collaboration which can lead to more innovation and flexibility.
• DevOps Orchestration Framework: To rightly implement DevOps strategy you can get countless benefits that one can think of. Therefore, look at all areas of strong collaboration between the teams, continuous release and deployment, testing, monitoring, and easy detection and resolution of issues. The diagram below indicates various areas of software development and operational aspects that needs to be considered as an integrated and converged orchestration model to implement DevOps.

Let us look into some of the best practices for implementing DevOps in this digital era:

Some of the Best Practices for Implementing DevOps

• A Perfect blend of DevOps strategy with the business – Just like the right stepping stone is required for the strong foundation. Similarly, the right blend of IT and business strategy is need of the hour. If they are not aligned together then DevOps will not be successful.
• Handpick the right project– Choosing the right project at right time for implementing DevOps is one of the difficult and essential tasks. Make sure to choose such projects that differentiate your business.
• Invest on result-oriented platforms – While selecting the platform and tools for DevOps to improve your current processes, you should always keep in mind to pick those ones that have known for its flexibility and ease of implementation. Because sometimes testing new tools can lead to a huge time consuming in terms of resolving existing bugs and incompatible issues to your platform of choice. Thus, it should be wisely picked.
• Make Automation a priority: DevOps is a focal point around which organizations can shape their digital transformation strategies. Therefore, the way technology is automating every aspect of process and workflows irrespective of its size, complexities and one should not forget to automate to enjoy the benefits of DevOps.

The next step is to integrate AI/ML models to your DevOps implementation to learn patterns, anticipate problems and suggest solutions in the following areas

• App Performance
• Data access bottlenecks
• Common alerts (Infra, Networking, and Application layer)
• Common failures during application testing
• Telemetry from business channels

Outlook
According to Forrester Research “50% of organizations surveyed said they are implementing DevOps and are increasingly focused on how their organizations can successfully accelerate the delivery of applications and services — without additional headcount.”

“Those organizations that are enjoying its benefits have reported 60% higher revenue and profit growth than others. Moreover, the companies were 2.4 times more likely than the rest of the organizations surveyed to grow their businesses at a rate of over 20%”.

However, still, there are a majority of organizations that are missing out on the extensive benefits of DevOps e.g. faster delivery time to market and higher customer satisfaction, etc. So, the question still arises that why organizations are still struggling to embrace these practices?

It has been found that the organizations that are reluctant in adopting this growing field are plagued by barriers like cultural, skills leadership, investment, skill gaps, etc. To make it into a successful investment it is important to first understand how to implement it correctly and the benefits that one can derive from it.

While there is no sure shot mantra for success, but there are many real examples that showcase the success. Though DevOps tend to be overused term but it is an ongoing journey that will set a standard for the next generation of enterprises. It will be here to stay because it brings practicality, profitability and valuable asset for today’s organizations and at the same time help open new business avenues faster to market.

The Indian FinTech market has scaled great heights in the past few years, both in terms of funding and adoption of emerging financial services solutions. India ranked 2nd globally in FinTech adoption with the percentage of users reaching 57.9%.

Deloitte has already pegged FinTech as one of the fastest-growing sectors due to increasing number of preferred digital channels for financial investments and wealth management[2]. In fact, the overall transaction value in the Indian FinTech sector is projected to reach $137.8 billion by 2023, as opposed to $66.1 billion in 2019[3]. The weather has also run favourably for the sector on several fronts.

First, customer experiences have undergone sweeping transformation by the non-financial tech firms, leading to the rise of increased digital expectations from financial firms/service providers. Second, the Indian regulators have now enabled a positive environment of knowledge sharing for FinTechs in addition to several initiatives aimed at enhancing the country’s digital infrastructure. Finally, the adoption of new technologies such as artificial intelligence (AI), machine learning (ML) and big data, fueled by the rising internet and mobile penetration has empowered financial organisations to tackle the pressing pain-points of the time.

Quite understandably, innovation in the FinTech sector has taken the world by storm. Moving forward, the open-API economy may even see surprising participation from the non-financial sectors such as telecom, retail, and power, who can leverage open-data as a means to boost their portfolio by foraying into financial services.

Before we get ahead of ourselves, let’s dive into the key technology advancements India needs to be ready for along with the need to propel indigenous R&D and IP creation.

How FinTech is leading the revolution

A large portion of India’s population are excluded from the formal financial system, due to a multitude of reasons. Lack of awareness about the benefits of financial services products, the inability of traditional financial players to serve this segment in a cost-effective manner and the lack of a national infrastructure to support future progress being the key.

However, since the launch of schemes such as Jan Dhan Yojana, and Direct Benefit Transfer, there has been a significant rise in the awareness of these products. The introduction of the Goods and Services Tax (GST) regime has also been a mindful step towards formalizing the unorganized sector of the Indian economy with several FinTechs leveraging its generated digital footprint (i.e. GSTN), standing at an impressive ~1.21 crore registered entities. Jan Dhan Yojana, the flagship initiative by the government has also seen a significant uptick in the number of people with bank accounts in India, currently standing at 320 million. Finally, access to platforms such as UPI through the ‘Digital India’ initiative has allowed banks, wealth, lending and insurance players to innovate freely around the pressing consumer problems.

These, in turn, have led to the rise in demand for financial services solutions, thereby creating viable market opportunities for FinTechs.

Driving excellence through collaboration

If we were to take part in the collaborate-vs-compete debate, the growing trust in the FinTech industry has brought challengers and incumbents together to explore more opportunities for new revenue streams, and rapid go-to-market solutions. In fact, FinTech challengers today have emerged as sophisticated competitors. The interactions between them, incumbent players and global experts are forming ecosystems that are replacing traditional bilateral partnerships designed to solve problems. It is interesting to see so many partnerships and the launch of new brands such as Kotak 811, iMobile and SBI’s YONO. ICICI powered Neobank initiative called ‘Open’ is also an example of a similar move.

To achieve the middle ground between innovation and regulation, RBI’s proposed first-of-a-kind regulatory sandbox for FinTech start-ups offers the right kind of boost needed to help this industry achieve its potential.

That said, the road to collaboration is not free from hurdles. While incumbents struggle with the pace of innovation and the obsolescence of their legacy systems, startups are feeling the brunt of bureaucratic, legal and cultural issues when working with these institutions. Nevertheless, the maturity of collaboration is all part of the ‘one-step-at-a-time’ revolution, sure to lead to a promising avenue for growth and financial inclusivity.

Each must welcome the wave of change with a humble heart, open mind and embark on the journey of unlearning the traditionally accepted models.

This article has been published in BUSINESSWORLD.

Read now: FinTech Will Lead India’s Financial Formalisation

At the heart of open banking strategies lie application programming interfaces (APIs). They form the backbone for information exchange between banks and third-party providers (TPPs) or non-financial service providers. By doing so, banks are able to build on value-added services to a set of consumer base directly or indirectly which they would have taken longer time to acquire & develop.

But banks have to be aware of the risk of overdeveloping APIs. Creating a multitude of APIs opens banking landscape to security risks and overloading the underlying IT infrastructure. Without proper security protocols, API weak points can be exposed to operational risks and data breaches. But how can we reduce the risk of API overload in open banking? We take a look at strategies to attenuate the risk of API overload.

• Development of API should be in line with digital banking strategy:

Most banks have rushed into API development without a defined API strategy. The development of APIs needs to be in line with the company’s business strategy, specifically its strategies for digital transformation. APIs can be used in different ways, but the core of digital transformation relies on creating value addition to the customer. Today, the banking ecosystem comprises an eclectic mix of financial institutions, FinTechs, vendors, and a diverse customer base. To be able to cater to this new ecosystem, banks have to digitally transform their legacy systems, address microservices.

Focusing on customers’ needs, banks are creating unique partnerships with technology companies to develop value add services. With newer technologies like artificial intelligence (AI), machine learning, blockchain, and predictive analytics, banks are developing new resources to lower costs and quicker turnaround. Some banks have collaborated with neo banks or acquiring them to align API development with their digital transformation journey.

Enriching the digital ecosystem, BBVA’s API market creates infrastructures that support the distribution and creation of third-party products in synergy with banks. Their aim is to make banking services “invisible” in order to minimize a customer’s effort to use digital products. For example, BBVA invisible payments allow employees/customers to make payments via facial recognition. In the bank’s cafes and restaurants, customers have to look into a camera to automatically bill and pay for purchases.

• Create synergy between the various teams within the organization:

Data silos have plagued the banking sector for decades. But in the age of digital advancements, banks can no longer operate by building walls around teams. Across banking functions, teams need to communicate and exchange information/data. Legacy siloed architectures are also a major barrier for breaking down silos.

For banks to implement APIs they have to first improve their data integrity capabilities, essentially rethinking their data collection processes. Application querying data sets with errors can bring the entire system down. In this scenario, tools like validation APIs can help banks integrate data. But these tools are limited by the flow of data from varied sources. Standardizing data collection and management processes across silos would streamline and centralize data sources. This eliminates duplication efforts and reduces siloed API development.

As data sources increase (Internet of things devices, smartphones), data siloes would continue to manifest itself. Banks have to focus on breaking these silos with innovative solutions. Most banks are adopting DevOps to remove barriers between development and testing and breaking down silos. Lloyds Banking group, for example, uses DevOps to drive community and collaboration among engineers/developers.

• Maintaining a balance between internal and external APIs:

The banking sector is highly regulated owing to the sensitivity of the data being handled. In this environment, it is a security risk for banks to allow TPPs to access information, who may leverage the data to extend their own offerings. A recent report

A good start for addressing security and trust issues would be for banks to develop APIs that support their internal development. These private APIs are by invitation only and are being used by banks in B2B experiments. For example, in 2016, Deutsche bank conducted an open house hackathon to test its dbAPI programming interface. The event drew over 750 applicants from 22 countries to develop digital solutions for banking clients. The interface provided an easy and convenient platform for developers to use. Eventually, the banks opened its data store to external software developers.

Partner and Open APIs are the latest trends to take over since open banking. These APIs allow automated information exchange with third parties. While the system allows for quick development of products and solutions, it opens security vulnerabilities if implemented incorrectly. Plug-and-play APIs allow banks to extend their service offerings and build API-led connectivity. This strategy is effective in monetizing the API economy and creating new revenue streams.

Successful APIs require internal and external developer communities that are healthy, collaborative, and future-thinking. While banks need to offer their services to TPPs, they should also think about leveraging TPPs for their own offerings; fostering external connections. Gartner calls it an “inside-out banking”, wherein banks interconnect with external FinTech companies.

Globally, open banking initiatives remain in very early stages of development and implementation. The four most powerful technology companies  Google, Amazon, Facebook, and Apple (GAFA) are enabling a broader cross-industry data sharing ecosystem. To compete with non-banking financial companies (NBFCs), banks have to develop strong relationships with their customers and vendors, while distributing the risks. Mitigating API overload will aid banks to increase revenues and focus on developing mutually beneficial business value offering than a technology marvel on their ability to integrate.