Dennis D. McDonald (ddmcd@ddmcd.com) consults from Alexandria Virginia. His services include writing & research, proposal development, and project management.

Change Management, Digital Transformation, & the Cloud: No More Normal

Change Management, Digital Transformation, & the Cloud: No More Normal

By Dennis D. McDonald, Ph.D.

On behalf of Dimensional Concepts LLC of Reston, Virginia I recently attended two virtual sessions sponsored by ATARC:

The Cloud Migration session was a quick overview of how GSA and other agencies are moving key government data and applications to the cloud as well as the associated challenges given the workforce impacts of the COVID-19 pandemic.

The NASA digital transformation event was a deeper dive into how that agency is reorganizing itself to “digitally transform” its operations to streamline business processes and make data more accessible and useful.

I admit to having some skepticism about discussions of “transformation” given what I know about the very real barriers, intended and unintended, that can hobble tech-enabled changes such as collaboration and improvements in data governance.

Nevertheless, what I heard from these two sessions rings very true given how information technology has permeated all levels of society and raised expectations about system responsiveness, accessibility, and ease of use.

In no particular order, here are some of my own takeaways from these two events:

  1. Head start. Organizations that were already adopting virtualization technologies such as hosted email, collaboration and knowledge sharing, teleconferencing, and cloud based applications are better equipped to weather the transition to home based working driven by the pandemic.

  2. New normal. If and when the pandemic subsides, the remote working changes brought about may remain with us. More traditional and legacy bound organizations will find a much stronger need for effective change management procedures than ever before as older systems and business processes are forced to adapt to the new realities.

  3. New vs. legacy. Management will take notice of how rapidly specialized and mission-specific applications can be rapidly spun up and proliferated through cloud based environments with their built in tools and support features. Legacy dependent back office systems and functions, given that they are already paid for, will lag behind in the transition.

  4. Siloes. Traditional departmental divisions have created restrictive data ownership practices. This can hobble data access and taking advantage of modern AI and Natural Language Processing techniques.

  5. Authentication and security issues make single sign-on solutions complex to implement. This complexity is exacerbated by the need to support a wide range of mobile and personal devices.

  6. Management support. Support by top management is essential to the success of any digital transformation effort.

  7. Data governance. The ability to take advantage of advanced data analytics, key to many digital transformation efforts, may require dedicated data governance efforts that cross departmental boundaries and involve both technology and business involvement.

  8. On prem downside. The flexibility and scalability of cloud based applications “… crushes what you can do ‘on prem’ - except for the legacy applications you’ve already paid for.”

  9. Hidden data. Much potentially useful government data is still “hidden” and not widely accessible.

  10. Interoperability between agencies and between different cloud vendors is still a challenge.

  11. Remote offices. Given what they have seen in the pandemic-driven move to working from home, some agencies are beginning to question how many people they really need in remote offices and facilities.

  12. Transformation fatigue. Given that many large organizations are regularly undergoing change and reorganization, it’s essential when promoting “digital transformation” that people not experience “transformation fatigue.”

  13. Research vs. production. There is a big difference between (a) developing an experimental AI based application and then publishing an academic paper and (b) developing that model and putting it into production.

  14. Data prep realities. At the end of the day, making data “AI ready” involves a lot of gutwork — data cleaning, standardization, data transformation, etc.

Overall, we are much better positioned now than in the past to take advantage of technology abled tools, improved data access techniques, and intelligent data sharing methods. And, like it or not, pandemic-driven remote working is accelerating both system and process transformation.

Whether it’s appropriate to call this “digital transformation” is another question. Changes arise in both technology and business processes and these changes are driving the need to change management approaches as well.

I do suggest that in the future whenever these topics are discussed there is also a more open discussion of the costs and benefits of “digital transformation” changes. Moving applications and large volumes of data to the cloud, for example, can require significantly more than simple “copy and paste” function; the ripple effects involve more than just front end conversion costs and can extend throughout an organization and how it operates.

Copyright (c) 2020 by Dennis D. McDonald

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