During my February 22, 2017 webinar The Gartner Enterprise Information Management Maturity Model (replay available), attendees asked a number of excellent questions. Not able to answer them all during the session, I promised to address them in my blog.
We’re just starting on the EIM journey with a new CIO and Data & Analytics Leader. How does the accountability and ownership best split between the roles given the opportunity to establish from a blank page?
In my upcoming Infonomics book (due out in September), I include a set of “Generally Accepted Information Principles” (using the GAAP framework). One of those is the “Optimization Principle” which states: The business is responsible for optimizing the usage and understanding of information; the information management organization is responsible for optimizing information’s availability and utility; and IT is responsible for optimizing information’s accessibility and protection. I think establishing this triumvirate is an ideal starting point for defining the delineation of responsibilities. Of course you’ll want to discuss, negotiate and further refine each of these at a lower level of detail.
Do you recommend or have an opinion on the DAMA DMBOK as far as applying it to an EIM program?
The DMBOK is an excellent resource (as is DAMA). I find it very functionally-rich, but lacking some alignment across functions, and missing things like vision and metrics and overall EIM strategy. Ultimately the DMBOK is a fine EIM process checklist with detail on each of the functions. But it falls short in defining and how to coordinate an overall EIM program. Others like the CMM DMMM, the EDM Council MM, and MIKE 2.0 (based on my Meta Group work over a decade ago) also lack program/coordination and components for vision, life cycle, organization and roles, or even key activities like MDM. Some also lack incremental improvement recommendations or a self-assessment tool. But more than anything, these other models are not backed by 1000s of related research publications, as is Gartner’s model. Of course I’m biased.
Who should lead the EIM program: – CDO? – IT? – Business/Finance?
Ideally yes, a CDO or someone with executive level authority and resources. And an effective EIM program must coordinate across IT and business units effectively, so placing the CDO within one of those two can be suboptimal.
What would be the reason not to consider information as a true asset? There seems to be money to be made if they do.
Interesting question. One argument I’ve heard for the accounting profession not to consider information as a balance sheet asset is that it’s too difficult to measure the value of, and because it can be too easily copied, its ownership and control (key asset criteria) are difficult to ascertain. From an organizational perspective, not accounting for information allows information-centric companies to compile, generate and deploy information without disclosing it publicly. It also drives higher market-to-book valuations for info-centric companies.
What scope / deliverables should an EIM Phase 1 project have? (3 month delivery horizon?)
First, as I mentioned during the webinar, EIM is not a “project” per se. Rather it is an overall program approach for coordinating various information-related capabilities. That said, you have to start somewhere, right? So I’d suggest adopting the framework and laying out the components would be a great start. Use our Enterprise Information Management Program Template to flesh out your approach. Next, I’d suggest sorting out key roles and responsibilities, and an overarching set of principles for EIM that everyone, including the business and IT, can agree upon. In my upcoming Infonomics book (Sept), I lay out a set of “Generally Accepted Information Principles” gleaned from reviewing 100s of clients’ data strategy documents, and drawing upon key asset management principles from other disciplines. I’m happy to discuss and share these individually with clients any time.
Hello, do you view regulation (such as the EU GDPR) as a barrier to achieving maturity in this area or perhaps as a factor that we need to work smarter to deliver better controls and thereby achieve better information management?
On one hand, achieving regulatory compliance can detract from achieving direct economic benefits from information. On the other hand, many organizations use regulatory compliance as an impetus or imperative for overall information management improvements, including the hiring of a CDO, formalizing data governance, minimizing data extracts, improving data security, etc.
How do you recommend to implement the EIM program — with fully dedicated resources or can it be implemented with sort of virtual team across the organization?
The most successful EIM programs we see involve a core team of individuals…sometimes just a handful within the office of the CDO, and other times an entire 1000-person information management organization…plus coordination across business units and IT. Rarely, for example, do we see full-time dedicated data stewards. They are usually part of a virtual team.
Wondering where can we find the papers on how to quantify the value of data?
An overview of our information valuation models can be found in the blog: Why and How to Value Your Information as an Asset. The models themselves including guidance on how to do the calculations and adapt them is in the Gartner research publication: Why and How to Measure the Value of Your Information Assets. My upcoming Infonomics book (September) will also include details on the models.
I find making the leap from legacy data products to modern products challenging because the organization is entrenched in perceived value of legacy products. Is there a good test to measuring the actual utility of a data product?
I think “fit for purpose” is the operative expression here. What are your objectives in terms of functionality, performance, ease of use, flexibility, scalability, cost, etc.? And how would you quantify these? Having a well-defined vision and set of associated metrics can be useful in identifying if and when legacy technologies are reaching their end-of-life. As I mentioned during the webinar, “user satisfaction” is a poor proxy for value.
How are governments and for example police departments seeing information as assets?
Public sector, especially in the US is a bit of an exception. Rather than the information assets belonging to these kinds of organizations, it is part of the public trust (security and privacy notwithstanding). The Freedom of Information Act assures this, and recent open data mandates ensure the improved utility of information both within these organizations, and by others. FOIA prohibits government organizations in the US from selling or licensing information, but there are clever ways to monetize it internally and externally (e.g. via public-private partnerships). Government organizations in other countries are not so constrained. E.g., Gartner Consulting worked with another country’s national archives to determine the market value of digitizing certain artifacts.
Could you please provide some case examples on how some companies (preferably in Fin Services) have successfully used the EIM maturity model or a similar framework, wholly/ partially?
We have a library of dozens of examples of how organizations in every industry and geography have innovated with information. Many of them, however, focus on outcomes and economic benefits rather than the intricacies of how information is managed. For interested clients, you can submit an inquiry request to have me send you a selection of these real world stories.
A question on Governance, can you brief more on the “Eliminate notion of data ownership”. I was thinking ownership of data is in line with Governance principles and thus comes the accountability of data owners.
It’s mostly a matter of semantics. Using the term “ownership” perpetuates the notion of data siloes and hoarding. Language is important, as my colleague Valerie Logan has recently written about. (See Information as a Second Language: Enabling Data Literacy for Digital Society.) To maximize information’s value to the organization, it should be perceived, discussed and treated as an enterprise asset. However, of course you are right that governance is no-less important. Still, I personally prefer to see words like “trustee” used to designate an individual (or group) with authority over policies related to an information asset. Going a step further, the role of a fiduciary might fit as well. A fiduciary is someone with a contractual and ethical obligation for the well-being of an asset or portfolio of assets (typically financial assets, but just as applicable to information assets).
What size companies benefit from a formal EIM practice? We are 1,800 employees, $1B revenue, public utility.
Remember, EIM is a program or initiative. It does not specify the size or scope of information assets being managed or the requisite size of the organization. At its core, it’s a framework applicable to any size organization.
Information or data – interchangeable or important distinction?
Generally, I use the term “information” to refer to any and all forms of data or content, structured or unstructured, raw or processed. However, tacit information (a.k.a. “knowledge” or “wisdom”) is a different topic altogether as it does not meet the conditions of a true asset, and therefore cannot be monetized, managed or measured as one. Also, in most circumstances I consider the “data vs. information” argument to be pedantic, and “turning data into information” type phraseology to be trite marketing speak. Information’s potential value is more of a continuum. Ultimately, one person’s data is another person’s information. It’s contextual, and it’s a continuum. So making some artificial designation doesn’t really help much.
If you focus a lot on data does this focus cause a problem for organisation which are records/document-centric
Again, I think all information, whether structured or unstructured, electronic or printed, or raw or derived, can benefit from the same kind of asset management discipline and EIM program. I’d like to see the day in which all forms of data/information/content/records are managed under some unified approach.
I’ve noticed that a lot of EIM initiatives (and data governance, generally) tend to focus exclusively on data storage, ignoring data model standardization at the API / services layer. What are your thoughts on this?
Very good point. The Gartner perspective is that information architecture (including models and APIs and service layers) spans each of the EIM dimensions. I have been lobbying for information architecture to have its own EIM dimension, and would certainly support any organization that takes this approach. I agree with you that it is important enough to warrant a distinct high level capability.
How do you manage the tension between consistency across the dimensions and the need for data scientist to grab info prior to enterprise rationalization?
Ah, the age-old conundrum of expediency versus formality! Actually, your EIM strategy and data governance precepts should specify if/when/how data can be used before it is cataloged, cleansed, certified, integrated, and loaded into an enterprise data store (e.g. data warehouse, data lake, etc.). Or it should specify particular sandboxes for data R&D and experimentation. And governance policies should specify the degree to which that data can be used in any operational or strategic sense.
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