How to migrate to SaaS applications

Moving from legacy applications to cloud-based software-as-a-service (SaaS) applications is no different. The process is demanding — but can be done skillfully and deliver positive business outcomes. Such a move gives us an opportunity to discard old items and old ways of doing things while managing emotional involvement, resistance to change and challenges to the status quo. Developing a sound approach with rules, and deploying proven tools, will help make the move easier and deliver numerous business benefits. (See “Benefits of technology-driven cloud migration.”)Enterprises can migrate successfully if they have the right tools, technologies and expertise at their disposal. This paper lays out actions to take before, during and after migration to the cloud.

A fresh start

To enable digital transformation, enterprises should have business systems that are operationally agile and efficient. Migrating to cloud-based SaaS applications provides flexibility to support new business models and improvements in key areas such as data portability, analytics and security. A successful move involves using technology in new ways and leaving behind bad habits and items you never use.

Traditionally, most enterprise resource planning (ERP) projects start with business process reengineering, whiteboard sessions, offsite process walk-throughs, process mapping and so on. Most, if not all, of these activities should be performed with the help of new technologies, which can provide data-driven, fact-based views of current processes and non-biased options. This removes the guesswork and opinion-based best-practices discussions that have become all too familiar.

A successful migration to SaaS applications requires a technology-driven approach that guides the enterprise before, during and after the migration, with a focus on delivering business value and maximizing return on investment. Using advanced technologies such as data mining, machine learning and predictive intelligence, enterprises can identify and proactively address opportunities to reduce costs, improve quality and spur innovation. The approach includes analyzing the data and various components involved in the migration, validating them and taking actions that will ultimately produce positive business outcomes. (See Figure 1.)

Before the move: Discover and design

Before implementing SaaS, enterprises should deploy data-discovery tools to identify the current state of their business processes. The goal is to build a comprehensive digital blueprint of all process activities. Enterprises should make the necessary up-front investment in time and resources to build foundational structures that will support system migrations. They should:

• Use tools such as Hadoop, Spark and Google TensorFlow to construct machine-generated process mapping, automated metrics calculations and intelligent “hot spot” analysis
• Generate metrics for every process step and every record or case that has been processed
• Uncover unknown facts of all possible paths or broken processes and the reasons behind each of those instances
• Identify pain points based on facts such as numbers of occurrences, process variations, repetitions, average durations and long duratio
• Pinpoint opportunities to consolidate, simplify and modernize business processes to eliminate redundanc
• Provide metrics to improve cycle time and co
• Deploy process improvement approaches to simulate and compare current-state processes versus SaaS processes to identify process-improvement opportunities, change-management approaches and training strategies

A key output of these actions is a machine-generated digital baseline. An important step in producing a digital baseline is to create a diagram of the processes that you think exist in the enterprise, what change-inducing factors have occurred over time, and therefore what processes likely exist now. (See Figure 2.) With a machine-generated digital baseline, enterprises will know what to fix (hot spots) and precisely where the fix must be applied, using the best processes offered by SaaS products supported by automation, simple procedural and policy adjustments, and process-performance dashboards.

Once the diagram is mapped out, enterprise process champions can analyze it, looking at the source system, customizations and SaaS cloud solution and performing an impact analysis. Then, instead of forcing a preconfigured solution onto the enterprise, solutions can be tailored based on modern best practices.

During the move: migrate and transform

With the digital blueprint in place, next comes the migration. Having a machine-generated digital baseline is crucial because it provides a complete digital blueprint to build from. Now, it’s time to deploy migration tools.

It is important to deploy a wide array of migration and testing tools to perform extracts, inject setups and master data, and engage in end-to-end automated functional testing of applications and other critical tasks. The migration path relies on process discovery, rapid deployments and automation to transform the enterprise. (See Figure 3.)

Follow these steps to complete a successful SaaS migration:

• Conduct online, questionnaire-based interviews to compile configurations for the SaaS functional setup manager
• Deploy automated and secure software to prepare all data, and install it directly into the target instance.
• Auto-inject all configurations to stand up SaaS instances with future-state business processes.
• Provide reports and dashboards to review configuration injections and ensure that all configurations are loaded, verifying that they are correct and supported
• Deploy tools that allow configuration simulations and comparisons to test different scenarios and migrate configurations between environments.
• Establish a test repository with assets such as scenario descriptions, test scripts and user-configurable workbooks.
• Provision a testing-as-a-service (TaaS) automated testing tool to significantly reduce testing time and costs for quarterly updates and to enable the delivery of high-quality solutions

After the move: Automate and optimize

Once the migration is complete and the newly transformed SaaS solution is in place, the focus turns to automation and optimization. The goal is to drive continuous improvement via lean methods to optimize workflows and team performance. This results in better quality and performance, as well as positive business outcome.

Enterprises should undertake several postmigration actions, including:

• Provide managed services, including continuous delivery, for perpetual support and governance of cloud applications, including functions such as quarterly updates and automated testing.
• Refresh the digital blueprint to validate the solution’s effectiveness and pinpoint hot spots statistically worthy of automation.
• Create proof of performance with pre- and post-improvement performance metrics snapshots.
• Leverage automation insights to identify automation candidates, based on comprehensive historical data, to ensure that the digital workforce (bots) is executing each automation step successfully as planned, even as processes and technologies change
• Engage in continuous innovation and optimization to expand and maximize the value of cloud and automation investments.

Enterprises can use a variety of tools and techniques to eliminate waste from existing business processes, adopting modern best practices to simplify and standardize process flows. Enterprises can deploy cognitive/artificial intelligence robots to serve as a virtual workforce that rapidly improves speed and quality and reduces costs. Even simple automations are immediately effective, if you know where to deploy them.

Take a measured, data-driven approach

Moving business systems to cloud-based SaaS applications delivers many business benefits, unlocking innovation and improving user experience. Enterprises have moved beyond asking preliminary questions about modern technologies such as data mining, machine learning and predictive intelligence. The more important questions are when and how to adopt these technologies to simplify and automate business processes, upgrade business capabilities and enhance user experience.

The primary goals are to successfully implement and optimize quality cloud solutions, reduce risk and improve business outcomes. A measured, data-driven approach that includes developing a machine-generated digital baseline and migration blueprint, and uses automated tools, can go a long way toward making the move to the cloud smooth and successful.

About the author

Manish Patel is digital transformation advisor at DXC Technology. He is responsible for building and driving adoption of Oracle digital cloud solutions — including robotic process automation, artificial intelligence, machine learning, internet of things and analytics — to help customers transform their business models to the next generation of digital.