10 Steps To Digital Transformation While Simultaneously Cutting Costs

Written by mzweben | Published 2020/05/10
Tech Story Tags: digital-transformation | scalability | databases | cloud-computing | hybrid-cloud | cloud | distributed-systems | distributed-architecture

TLDR Business leaders know they had to digitize processes that were previously hampered by real-world constraints. Disney and Carnival Cruises, for example, offer digitized wristbands that enhance their customer experiences. Uber and Lyft have digitized taxi services to great success. Digital customer engagement comes with operational risks, since most supporting systems were not designed to handle the speed and scale of digital interactions. Migrating to the cloud and modernizing your legacy databases is now easy and risky and risky to do this now to scale-out.via the TL;DR App

Companies Must Transform Or Else (Photo by eelnosiva on Adobe)
Digital Transformation was the hot topic before the new era of remote work and social distancing hit us. Business leaders know they had to digitize processes that were previously hampered by real-world constraints. Disney and Carnival Cruises, for example, offer digitized wristbands that enhance their customer experiences, while Domino’s Pizza offers its customers the convenience of ordering exactly what they want on their mobile app, and getting it delivered to their location within 30 minutes. Capital One’s customers can create a fully functioning digitized account in 5 minutes. Uber and Lyft have digitized taxi services to great success and Netflix and Spotify have digitized the consumption of media.
Sometimes digital transformation improves existing business processes. For example, one payment company we work with transformed its customer service process for disputes by removing the costly and error-prone back and forth communications amongst consumers, banks, and merchants with an online self-service process. This vastly streamlined dispute resolution and yielded dramatically increased customer satisfaction and lower chargeback benefits.
In other examples, digital transformation completely changes processes. For example, a healthcare company we partner with transformed neurology by networking clinics together to use digitized medical tests and digitized patient reported outcomes to predict the trajectory of neurological diseases while in the doctor’s office. This uses objective real-world population data that could never have been possible without digitization and AI to help advise clinicians of their clinical options.

Digital Imperative: The New Normal

(Photo by phloxii on Adobe)
Before, companies that didn’t digitize could still survive, even if they weren’t leaders in their industry. Now we are officially in the era of a digital imperative where businesses must be singularly focused on engaging and serving customers at a distance. This is the new normal. This is no longer elective surgery. This is survival.
Conversations about survival in the corporate boardroom are all about minimizing the financial and operational risks caused by the crisis. The financial risk is due to the extreme uncertainty in revenue forecasting. Forecasting demand is now nearly impossible, and therefore cost takeout is the only controllable variable to reduce financial risk. But this is a conundrum. How can the company simultaneously engage digitally and reduce costs? The Digital Transformation journey is not straightforward. Unfortunately, digital customer engagement comes with operational risks, since most supporting systems were not designed to handle the speed and scale of digital interactions. This can make it hard to cut costs while simultaneously taking action on Digital Transformation initiatives and thriving during the new normal.
Consider the banking and insurance industries. They rely on antiquated special purpose analytical databases, legacy databases, and even old school mainframes to execute the most basic of functions. These systems have served them well for decades. But at the same time, the demands on these systems are increasing because of the spike in digital interactions. More people are checking websites, applying for loans or policies online, processing claims from home, and engaging with contact centers. The contact centers themselves have likely moved from a centralized location to a spare bedroom or closet in the employee’s home. Slow or frozen websites, long call queues and dramatically longer shipping times are unfortunate — but fixable — results of applications that are run on antiquated legacy systems. As a result, a much larger number of customers and employees will become frustrated with these resource-constrained interactions with companies.
The knee-jerk reaction to this crisis is to buy more expensive hardware to scale. But this may not be the best answer. In many cases, you have already maxed out the architecture, and throwing more money at buying hardware will be ineffective and potentially a luxury that no longer exists as boards demand budget slashing.
Fortunately, there is a better way. What if you could modernize systems on the cloud in weeks to simultaneously reduce costs and be able to scale to new unexpected loads?
Scale-Out in The Cloud: More Power — Less Costly (Photo by Spectral-Design on Adobe)
Now you can migrate to the cloud and modernize your legacy database or data warehouse onto a scale-out architecture without throwing away any application or reporting code. Even better, you can do this while avoiding the eye-watering costs of buying more expensive specialized hardware. There are at least 5 benefits to this approach. They are listed below.

5 Benefits of Modernizing on Cloud Scale-Out:

  1. Reduce specialized hardware costs without giving up business continuity
  2. Reduce database or data warehouse licensing costs
  3. Only pay for infrastructure in use
  4. Add more infrastructure as loads increase without downtime
  5. Preserve all your existing code and reports without rewriting them. Rewriting is expensive and risky.
    It is easy to migrate from legacy databases now to scale-out in the cloud (Photo by Michail Petrov on Adobe)
If this seems too good to be true, it isn’t. In fact, the largest companies in banking, insurance, payments, consumer goods and healthcare have already successfully executed the above strategy. And they did so in weeks or months, not quarters or years.

Below is a 10 step blueprint of how to do it:

  1. Choose a cloud scale-out RDBMS. I recommend using a multi-cloud RDBMS to avoid vendor lock-in, but I am biased because my company (Splice Machine) offers a translytical RDBMS supported on any public cloud. For those of you who are unfamiliar with the term “translytical”, it means that the database can simultaneously execute transactional and analytical workloads.
  2. Select a workload to test. Perhaps an application, a batch analysis job, or a report.
  3. Grab an activity/audit log from your existing RDBMS or Data Warehouse for a specified period of time representative of the workload.
  4. Migrate the DDL or schema that defines your data to the new database. Sometimes the vendor will have tools to automate this process.
  5. Migrate a snapshot of your data over to the new database. The vendor may have out-of-the-box data migration scripts for this as well.
  6. Run the statements in the activity log on the new database to assess functional and performance parity.
  7. Identify the gaps where syntax may need to be modified, where queries need to be hinted and then re-test. This step will identify the statements where workarounds will be necessary or new functions need to be defined. Sometimes there are no changes necessary. See this blog on DB2 application migration in which a comprehensive financial services application migrated from Db2 without any changes on a cloud scale-out architecture.
  8. Implement the above changes, if any, throughout the application.
  9. Shadow the application, batch process, or report by running on both the old RDBMS and the new cloud by sending statements to both. This is similar to running replication for disaster recovery and business continuity. Compare the corresponding behaviors for correctness and performance.
  10. Turn off the old system, saving money while simultaneously gaining scalability,
In order to maximize control over costs, this new architecture fully supports elastic scale-out. If you are migrating an online application, when data surges, you can increase and decrease resources without ever taking the application down. If this is a batch process or report, you can pause the RDBMS when it is not in use, saving cloud costs.
This is even possible for legacy mainframe applications. In this blog on mainframe application modernization, we talk about automatically converting applications written in COBOL using tools to compile the COBOL to Java.
Walking the Tight-Rope of Digital Transformation and Slashing Costs (Photo by eelnosiva on Adobe)
In summary, we are in a new era of a digital imperative, and as you cross the tightrope, you will need to balance improved outcomes for the way your company now has to execute with a likely cost take out strategy. Your new systems and your old supporting applications will need to scale in ways you did not expect. At the same, you have been asked to remove as many costs as you can from your operations. Modernizing your applications on the cloud with a scale-out architecture is likely an answer to this seemingly unsolvable problem.
To try these steps on one multi-cloud, scale-out RDBMS click here



Written by mzweben | CEO @Splice Machine, Advisor @ CMU CS, Former NASA, CEO@Rocket Fuel, CEO@Blue Martini
Published by HackerNoon on 2020/05/10