You want me to modernize my legacy technology and data systems during a global pandemic? Yes, and here’s how.
The world we’re living in today — where COVID-19 dominates the news outlets, conversations among friends, and our private thoughts — has made us all think about things differently. We’ve all seen the implications of COVID-19 come to life in our local communities and more broadly in the global marketplace.
Just a mile from my apartment, the woman-owned distillery where I got married shifted production from vodka and bourbon to hand sanitizer. While innovation has surged amidst COVID-19, we’ve also seen catastrophic effects on businesses. The hospitality industry has been hit especially hard, as major hotel chains have made excruciating decisions to furlough and lay-off employees.
The stakes for senior leaders are higher than ever as they try to make responsible decisions for customers, employees, and communities, all while keeping an eye on the bottom line. Add to that the need to do so faster than ever before and the risk of not acting quickly enough is no longer simply missing an earnings projection, it’s a bankruptcy filing or ceasing to exist altogether.
An organization’s data can and should be a crucial component in decision-making processes, whether those decisions be related to prioritizing initiatives, defining strategies, creating and releasing new products, marketing to customers, allocating budgets, or aligning on human capital needs. While this was true before the global pandemic, it is especially pertinent today. In a perfect world, each organization would leverage a finely tuned analytics machine to support these activities. But, with murder hornets becoming a serious reality in the United States, it’s safe to say our world is less than perfect.
So, in this post we’ll explore the options an organization has to overcome the constraints imposed by legacy technology and cumbersome data infrastructure. What can an organization do in the short-term to amplify innovation, when the ability to quickly adapt is constrained by burdensome processes, cost, and/or time, whether before COVID-19 or as part of the ‘new normal’ we’re marching towards? And, how can organizations do this in a way that promotes iterative, incremental value creation, rather than waiting for a full transformation lifecycle at the expense of competitive advantage lost to fast-moving, nimble digital entrants?
The answer is creating a Modern Culture of Data that promotes Access and Transparency and cultivates appropriate Ways of Working. The former focuses on creating integrated data and flexible, scalable systems, while a central component of the latter is to ensure that the right tools to conduct analyses are available to end-users. The overarching goal is to ensure employees have the information and tools they need to ensure data-driven decision making is possible.
In many scenarios, that might first involve reimagining legacy technology systems that comprise the backbone of an organization and then creating a cloud-based data platform. The amount of time required for this conventional approach is simply too long for today’s world. So, I’d like to explore three scenarios to achieve near-term objectives without undertaking a holistic transformation effort when time is of the essence.
Scenario One: Leverage best-of-breed, purpose-built tools to innovatively use available data
As a result of COVID-19, many hospitals around the United States were forced to cancel elective and more serious procedures in early 2020. Upon the expiration of stay-at-home orders, states began to lift restrictions, and hospitals must now determine how and when to reschedule weeks of canceled medical treatments.
Many drivers influence when to reschedule a patient’s procedure including procedure urgency, medical team availability, patient availability, and revenue implications. While the underlying data for each business driver may exist, it may not be available in one central place to facilitate holistic analysis, rendering the effort both time-consuming and costly.
Instead of investing the time and money to create a new process to centralize all the data and serve it in one place, a purpose-built tool like Anaplan can connect to disparate data sources and enable a user to make sense of the information. While this is just one example of improving Ways of Working, other purpose-built tools can minimize data silos and provide data to users when and how they need it. For the hospitals in this scenario, that means confidence in successfully prioritizing and rescheduling surgeries.
Scenario Two: Develop lean infrastructure while working within legacy system constraints to minimize costs
One of Slalom’s media & entertainment clients needed new ways to learn about consumer use of their product to facilitate better communications with their customers. The client relied on a legacy on-premise Subscriber Management system, running on Oracle, which had reached its scalability limits, and was no longer financially viable.
Rather than revamping their entire technology and data ecosystem, the organization acknowledged its constraints and exploited them by ‘building a bridge’. Slalom worked with the client to build a technical process to intercept requests and push them into a new, modern AWS data solution. All queries were run through the new, real-time data streaming platform. This approach allowed the current system to focus on what it was designed to do and created a new capability to support the immediate needs of data workload volume, access, and responsiveness, while also setting the organization up for future success with a flexible, scalable, event-driven architecture.
This approach to improving Access & Transparency ensured that the client was able to access the data they needed in a way that balanced both their need for expediency and respected their budget. In our current and post-COVID climate, this approach is likely to be particularly relevant as purse strings for major transformational efforts could be tightened, but the urgent need to become more data-driven is central to the success, and perhaps the survival, of an organization.
Scenario 3: Iteratively create a modern data platform without modifying transactional systems
This scenario focuses on creating a ‘net new’ data platform. Many organizations think that a new data analytics solution requires significant upfront planning and data modelling, but Slalom regularly works with clients to create data platforms that deliver value quickly and can then be iteratively grown and enhanced to support additional use cases.
At the height of the COVID-19 pandemic in April 2020, Slalom was engaged by a non-profit healthcare client, whose role is to aggregate and provide data to several states, to create a lean data platform that delivered value quickly.
To do this, the team first aligned with the client on the immediate needs and longer-term vision of the platform, and then leveraged our internally built Azure data lake accelerator to rapidly and effectively deliver results. By the third week of the project, the data lake infrastructure was stood up, and by the fifth week, the team had onboarded data sources to automate what was previously the work of a small team. Our work improved Access & Transparency and impacted the organization’s Ways of Working without disturbing or updating any transactional systems, and the client has not spent millions of dollars or months’ worth of time to see tangible results. The client team has quickly adapted to the new system and processes and is now able to focus on higher-value tasks.
How can we help?
While each scenario discussed above is particularly relevant today, we have been discussing these needs with clients before COVID-19, and we will continue to do so once the pandemic is behind us.
Has COVID-19 forced you to identify an urgent need to work within the existing technology and data infrastructure within your organization today? Are you anticipating a need to be better prepared for the ‘new normal’? Drop me a line and I’d be happy to chat.
Amanda Lintelman is a Solution Architect out of Slalom’s DC office, where she leads the Modern Culture of Data offering. Amanda is passionate about helping clients solve data-related problems by aligning business and data strategies. She has experience supporting clients across industries including Hospitality, Financial Services, Healthcare, Utilities, and Airline.
This is the second post in our Modern Culture of Data COVID-19 series. If you missed the first post by Oliver Asmus, check it out here. There will be four posts in this series; be sure to check them all out and reach out to learn more.
