Challenges to DevOps May Be Deep-seated But Not Unexpected
The challenges to DevOps based I.T. management practices described by Alex Henthorn-Iwane in DevOps Impact on IT Operations Management look similar to some of the challenges to “big data” adoption I’ve been finding in my big data project management research.
This should not come as a surprise and may reflect so-called “resistance to change” that other technologies have faced when being introduced to the enterprise.
The reasons are basic to how organizations operate. Few systems and processes within an enterprise are totally independent. They evolve at different rates along with their many interconnections. Some systems and processes face less “resistance” to technology-induced changes than others. This variation is due at least partly to how they interconnect and to the real costs associated with making changes.
I am not ignoring politics or the often-blamed “culture” as reasons for resistance to change. These factors obviously can play a role in delaying or even preventing technology-induced change. As always, failure to address how business processes can (or need to) change in response to technology change will be a recipe for disappointment; experienced project managers understand this.
After years in consulting and project management, though, I now view politics and culture as factors to be anticipated and managed rather than ignored. This is true whether one is planning an individual project or an enterprise wide portfolio management strategy.
Regarding “big data,” Henthorn-Iwane says this:
However, an interesting challenge for true conversion to cloud-based DevOps approaches is the need to address a Big Data problem. The amount of data generated by IT infrastructure and networking equipment is now so voluminous that traditional systems and approaches can’t keep pace. Legacy systems that have their architectural provenance in the 1990’s are based on scale-up models, and were never built for today’s data volumes. Even cloud-based solutions may not necessarily be scoped to address IT Big Data.
While Henthorn-Iwane approaches big data’s impact on DevOps as due to data volume, the ripple effects actually go beyond volume-induced issues of data capture, storage, and processing to also include fundamental challenges to how data are used and managed throughout the organization.
Business processes both within and outside I.T. may need to change. Organizations that are already data-centric will have a leg up on understanding how big data methods and technologies can be put to use. More traditional or older organizations, especially those at least partially dependent on integration of newer with legacy data management technologies, may face greater challenges involving the need to upgrade and/or introduce analysis resources and technologies with which they have little experience. They may also find it necessary to think of data management and governance more strategically and about how existing governance and management processes might need to change in response.
A good place to start will be to get a good handle on the costs and benefits of introducing new big data related initiatives into the organization. The more realistic these costs and benefits are, ideally based on actual experience, the better.
- The Changing Culture of Big Data Management
- Developing a Basic Model for Data Analytics Project Selection
- How Infrastructure and Cost Impact Technology Adoption Rates
- Is the Project Management Office Evolving or Devolving?
- Knowing An Organization’s Data Management Maturity Helps Promote Effective Open Data Program Planning
- Problems and Opportunities with Big Data: a Project Management Perspective
- The Tip of the Spear: Connecting Big Data Project Management with Enterprise Data Strategy
Copyright (c) 2016 by Dennis D. McDonald. Dennis (email email@example.com phone 703-402-7382) is based in Alexandria, Virginia. His experience includes consulting company ownership and management, PMO setup and management, database publishing and data transformation, managing the integration of large systems and databases, corporate technology strategy, social media adoption, statistical research, and IT cost analysis. His clients have included the U.S. Department of Veterans Affairs, the U.S. Environmental Protection Agency, the National Academy of Engineering, General Electric, AIG, the World Bank, Whirlpool, and the National Library of Medicine. He has worked as a project manager, analyst, and researcher throughout the U.S. and in Europe, Egypt, and Hong Kong. His professional web site is here: http://www.ddmcd.com.