Why Every Enterprise Needs a Hybrid Cloud Governance Strategy

Over the past five years, I’ve had the opportunity to work with more than half a dozen Fortune 500 clients as well as several government agencies in various contexts. There is one thing that every one of these organizations had in common – all of them needed a Hybrid Cloud Governance Strategy and none of them had one. I’m sure that there are a few organizations out there that have tackled this already, but if there are, they’ve certainly jumped well ahead of the curve. Adoption of a Hybrid mix of Cloud and non-cloud capabilities has quite literally exploded in the past few years. There are few if any enterprises that haven’t already begun moving down that path. However, this is definitely a case where the technology trend is outpacing our ability to integrate it into business operations and processes (at least in a fairly well-defined or unified manner).

The time has definitely come where this is no longer a nice to have or something for trailblazers only. Today, every enterprise needs to tackle the challenge of immediate or near-term Hybrid capability management. And it might be better referred to that way because if we were only concerned about the Cloud portions of what the enterprise were managing, then we’d still only be dealing with a partial landscape. Here are a few reasons why you need it…

1 – Because piecemeal governance is ineffective. In order to meet service level expectations or objectives with clients, there has to be a comprehensive ability to manage all of the resources that support such a capability, regardless of how that capability may actually be distributed. Now, there may always be some dispute as to what exactly “management” represents given that some Cloud providers will give limited access or control rights to their infrastructure, which begs the question – can you manage something you don’t control? The answer to that is a yes, you can – but let’s specify what we’re referring to as management:

• You can manage access control from your user base to the capability
• You can manage capacity planning and execution
• You can manage upgrades, enhancements and expansion of the user base (in tandem with the provider/s)
• You can manage network security expectations (to and from your various capability elements)

You can manage integration between capability elements or between separate capabilities

2 – Because Holistic Governance has always been an area for improvement, now it is a necessity: Most organizations have had some challenges implementing or maintaining Governance processes (I discussed this recently in another post on Data Governance). What tends to happen more often than not is that an organization settles into one or two subsets of Governance, for example a focus on Data Governance or Portfolio Governance. But Governance can cut across everything, from SDLC to Security, to Architecture to ITIL – basically Governance could or should touch every core process in the enterprise. Dealing with new Hybrid Cloud capabilities presents an excellent opportunity to tackle an age old problem.

3 – Because where there is more complexity, there needs to be more cooperation to effectively coordinate: One major advantage of managing all of one’s own capability on premise is at least the potential that a single point contact or service provider may be available to help coordinate everything. With a Hybrid Enterprise, the number of diverse providers and teams may increase quite a bit. And while you won’t likely have a single POC anymore, you can mitigate that through implementation of a single process.

4 – Because this diversification of capability will likely continue for some time to come. The trend towards greater capability diversification is likely to accelerate quite a bit in the coming years. While there will be exceptions where some organizations will migrate all of their capability to one Cloud provider (like AWS), this will definitely not be the norm. We are going to retain some on premise capability for a long time, especially where mainframe technology is involved and there will be a wide variety of other SaaS players that will continue to pull the typical enterprise in multiple directions

So how can your organization get started with Hybrid Cloud Governance? Here are a couple of suggestions…

1 – Create a Capability Inventory (coordinate with provider inventory). This suggestion is generally a worthwhile exercise anyway, particularly as a planning or strategy aid. It is typically done up front and can be relatively quick. Capability can be viewed in multiple contexts, the two most common being; Business Capability and Technical Capability.

2 – Determine your metrics approach and standardize it across capabilities. This is sometimes tricky in that Cloud providers often have different types of SLAs and SLOs, but rather than trying to map to everyone else’s definitions, set up your own and map everyone’s to that.

3 – Dedicate a team to facilitate it. This doesn’t have to be big team, in some organizations it might even be one person. The important thing to keep in mind though is if you don’t have someone dedicated to cross the capability barriers, then things will likely remained stove-piped.

Copyright 2016, Stephen Lahanas

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The Top 7 Reasons for Data Governance

In the Age of Big Data, many people might think that the practice of Data Governance is a thing of the past – nothing could be further from the truth. Data Governance has often been misunderstood or underappreciated and relatively few organizations have taken the time and made the investment to integrate it into their enterprise processes. So, there are actually several questions that need to be answered here:

1. Does the de-normalization of data through exploitation of Big Data technologies discount the need for Data Governance?
2. Why isn’t Data Governance more widespread if it indeed still has value and
3. What is the value proposition behind Data Governance? (what are the 7 reasons why you need it)

We’ll tackle these questions one at a time.

1 - Does Big Data Require Governance?

The immediate expectation in response to this question might be – well no - as Governance seems to represent the formal and complex approach used for both RDBMS and OLAP data structures. But does this make sense per se? Classifying a data model as normalized, star schema or a de-normalized Big Table doesn’t necessarily impact the nature of the data attributes themselves. In other words, we still need to understand that data regardless of where or how it housed – we still need to know where it comes from, who owns it, where it goes, how it is transformed and so on. If we want the data to be valid, accurate and managed across a lifecycle, Governance is still needed. The technology itself does nothing to prevent us from experiencing a ‘Garbage in / Garbage out’ situation. The adoption of new technology doesn’t imply the need to discard common sense.

2 – Why isn’t Data Governance More Accepted?

This is a tougher question and in fact can’t easily be broken down into a single reason. Some of the most common reasons include:

• To govern data you first have to understand it holistically, and that initial assessment / analysis is a generally the hardest part – and is often why things don’t progress beyond that point (as many of these assessments simply never get completed)
• Often times, all Governance within an organization may be lacking because of the perception that some processes can’t be Agile and just hold things back or slow them down too much. While there is some truth to that, there is also truth in the lesson learned innumerable times that bypassing that Governance causes tremendous impacts later (to cost, efficiency and the ability to deliver and maintain capability).
• Because sometimes the tools get confused with the practice and while there are a number of great data governance tools available – sometimes they become an obstacle in themselves (e.g. some may be considered too expensive, others too complicated or perhaps there might be too many in the mix). The reality is that a lot of Data Governance can occur before or even sometimes without making that investment. It is the practice and not the software used to facilitate the practice that really matters.

3 – Why do Most Enterprises Need Data Governance? Here are 7 good reasons that tend to represent the more or less universal value proposition:

• Data Governance reduces enterprise complexity. At first, as I alluded to earlier, the impression here might be the opposite. But one only needs consider a highly typical data Use Case to see how Governance cuts right through complexity. Perhaps the number one integration issue I’ve seen faced over the past twenty years pretty much everywhere is the proliferation of similar or even the same data across multiple systems (this can include both multiple databases and reporting platforms). This quickly leads to all sorts of confusion and ultimately costs more to manage as long as it stays, well, confused. Governance tackles this type of problem at its core, by first designating authoritative systems and then more strictly controlling the use or reuse of such data. This can translate into business rules across the stack and often results in the elimination of both redundant data elements as well as duplicate systems.
• Data Governance Enhances Security – How one might ask, does it do that? Well, precisely through some of what I’ve already mentioned; including an assessment and classification of what data assets your enterprise has as well as determination of rules and architectural requirements for safeguarding both Data at Rest and Data in Motion. All of this starts with and becomes part of Data Governance. And if we think a little deeper about it, this is only logical when we consider that Data Assets are in fact the number one target of every major Cyber-Attack ever launched. To protect your enterprise, you must first know what’s in it and secondly you must have the ability to control the flow of that information.
• Data Governance is the best 1st Step for Integration – Almost every integration challenge is at its heart a data challenge. How we transport data, transform data and keep everything aligned is to a large part dependent on how well we understand that data. Messaging / Middleware / API Frameworks / EDI / SOA /EAI – you name it - it’s all about the data. Once integration is place, it must be governed – data interfaces (through messaging or other similar mechanisms) – is actually one of the most pragmatic initial places where Data Governance can be instituted.
• Data Governance Enables more Sophisticated Capabilities – such as MDM – Master Data Management is an example of a valuable enterprise capability that simply couldn’t exist if some level of Governance weren’t in place. To deploy MDM, an organization has to understand its core business entities and how they relate to attributes and be able to control them in a consistent manner. Every MDM solution I’ve ever seen either has Data Governance built in or relies on some other existing Data Governance process. MDM is not the only capability dependent on Governance though.
• Data Governance is Critical to Achieving an Effective Analytics Solution – The last thing any organization wants to be getting different answers to the same or similar questions. Data Governance not only helps to de-conflict issues at the data level – it can be used to de-conflict entire solutions. In other words, data governance helps drive consolidation of reporting and reporting architectures as well as the source systems underneath them.
• Data Governance can Impact the Bottom Line – Having Data Governance can make your enterprise more effective, not just from an IT perspective, but also the Business perspective as well. I’ve seen many organizations reduce duplicate systems and eliminate conflicting data and experience immediate results. The amount of benefit is dependent on how many systems can be consolidated or turned off and how improving data accuracy will impact whatever the business mission of the organization may be – but in almost every case – these types of benefits will be realized to some degree.
• Data Governance is often the Keystone upon which more Effective Enterprise Governance is Built – It is a great place to start if no Governance is in place or an even better place to expand if perhaps there are already some pockets of Governance already deployed. Since Data tends to be a cross-cutter, both organizationally and architecturally – it can become the foundation for a wider Governance framework.

In my experience, even in the organizations that didn’t fully implement Data Governance, the elements which were deployed provided obvious and immediate value. The current technology trends tend to point to a heightened need for Governance rather than the other way around, especially with the massive levels of adoption of Hybrid Cloud capability. I’ll talk about that in an upcoming post.

Copyright 2016, Stephen Lahanas

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