The Great Divide: MDM and Data Quality Solution Selection

Michele Goetz

I just came back from a Product Information Management (PIM) event this week had had a lot of discussions about how to evaluate vendors and their solutions.  I also get a lot of inquiries on vendor selection and while a lot of the questions center around the functionality itself, how to evaluate is also a key point of discussion.  What peaked my interest on this subject is that IT and the Business have very different objectives in selecting a solution for MDM, PIM, and data quality.  In fact, it can often get contentious when IT and the Business don't agree on the best solution. 

General steps to purchase a solution seem pretty consistent: create a short list based on the Forrester Wave and research, conduct an RFI, narrow down to 2-3 vendors for an RFP, make a decision.  But, the devil seems to be in the details.  

  • Is a proof of concept required?
  • How do you make a decision when vendors solutions appear the same? Are they really the same?
  • How do you put pricing into context? Is lowest really better?
  • What is required to know before engaging with vendors to identify fit and differentiation? 
  • When does meeting business objectives win out over fit in IT skills and platform consistency?
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Forrester's Top 15 Emerging Technologies To Watch: Now To 2018

Brian  Hopkins

The pace of technology-fueled business innovation is accelerating, and enterprise architects can take a leading role by helping their firms identify opportunities for shrewd investment. In our 2012 global state of EA online survey, we asked again what the most disruptive technologies would be; here’s what we found:

The results shouldn’t surprise anybody; however, if you are only looking at these, you are likely to get smacked in the face when you blink -- things are changing that fast. In the near future, new platforms built on today’s hot technologies will create more disruption. For example, by 2016 there will be 760 million tablets in use and almost one-third will be sold to business. Forrester currently has a rich body of research on mobility and other hot technologies, such as Forrester’s mobile eBusiness playbook and the CIO’s mobile engagement playbook. But by 2018, mobile will be the norm, so then what?

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Is there a need for a next gen EA Framework?

Henry Peyret

 

There are interesting debates all around the globe about whether there is the need for a next gen EA framework.  James Lapalme recently published an excellent article: Three Schools of Thought on Enterprise Architecture explaining the reasons of such debates.   

In this article James identifies three schools of thoughts for EA, each with their own scope and purpose:

  • "Enterprise IT architecting" which addresses enterprise-wide IT, and the alignment of IT with business.
  • "Enterprise integrating" which addresses the coherency of the enterprise as a system with IT is only one component of the enterprise.
  • "Enterprise Ecological Adaptation" which addresses the enterprise in its larger environment
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5-Years Journey Of TOGAF In China Is Just A Beginning For EA

Charlie Dai

As businesses get larger, and the need for effective alignment of the business with technology capabilities grows, enterprise architecture becomes an essential competency. But in China, many CIOs are struggling with setting up a high-performance enterprise architecture program to support their business strategies in a disruptive market landscape. This seems equally true for state-owned enterprises (SOEs) and multinational companies (MNCs).

To gain a better understanding of the problem, I had an interesting conversation with Le Yao, general secretary of Center for Informatization and Information Management (CIIM) and director of the CIO program at Peking University. Le Yao is one of the first pioneers introducing The Open Group Architecture Framework (TOGAF) into China to help address the above challenges. I believe that the five-year journey of TOGAF in China is just an early beginning for EA, and companies in the China market need relevant EA insights to help them support their business:

  • Taking an EA course is one thing; practicing EA is something else. Companies taking TOGAF courses in China seem to be aiming more at sales enablement than practicing EA internally. MNCs like IBM, Accenture, and HP are more likely to try to infuse the essence of the methodology into their PowerPoint slides for marketing and/or bidding purposes; IBM has also invited channel partners such as Neusoft, Digital China, CS&S, and Asiainfo to take the training.
  • TOGAF is too high-level to be relevant. End user trainees learning the enterprise architecture framework that Yao’s team introduced in China in 2007 found it to be too high-level and conceptual. Also, the trainers only went through what was written in the textbook without using industry-specific cases or practice-related information — making the training less relevant and difficult to apply.
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Judgement Day for Data Quality

Michele Goetz

Joining in on the spirit of all the 2013 predictions, it seems that we shouldn't leave data quality out of the mix.  Data quality may not be as sexy as big data has been this past year.  The technology is mature and reliable.  The concept easy to understand.  It is also one of the few areas in data management that has a recognized and adopted framework to measure success.  (Read Malcolm Chisholm's blog on data quality dimensions) However, maturity shouldn't create complancency. Data quality still matters, a lot.

Yet, judgement day is here and data quality is at a cross roads.  It's maturity in both technology and practice is steeped in an old way of thinking about and managing data.  Data quality technology is firmly seated in the world of data warehousing and ETL.  While still a significant portion of an enterprise data managment landscape, the adoption and use in business critical applications and processes of in-memory, Hadoop, data virtualization, streams, etc means that more and more data is bypassing the traditional platform.

The options to manage data quality are expanding, but not necessarily in a way that ensures that data can be trusted or complies with data policies.  Where data quality tools have provided value is in the ability to have a workbench to centrally monitor, create and manage data quality processes and rules.  They created sanity where ETL spaghetti created chaos and uncertainty.  Today, this value proposition has diminished as data virtualization, Hadoop processes, and data appliances create and persist new data quality silos.  To this, these data quality silos often do not have the monitoring and measurement to govern data.  In the end, do we have data quality?  Or, are we back where we started from?

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Ethical Use: Do You Have A Data Policy for That?

Michele Goetz

Security and privacy have always been at the core of data governance.  Typically, company policies, processes, and procedures have been designed to comply with these regulations to avoid fines and in some cases jail time.  Very internally focused.  However, companies now operate in a more external and connected fashion then ever before.

Let's consider this.  Two stories in the news have recently exposed an aspect of data governance that muddies the water on our definition of data ownership and responsibility.  After the tragedy at Sandy Hook Elementary School, the Journal News combined gun owner data with a map and released it to the public causing speculation and outcry that it provided criminals information to get the guns and put owners at risk.  A more recent posting of a similar nature, an MIT graduate student creates an interactive map that lets you find individuals across the US and Canada to help people feel a part of something bigger.  My first reaction was to think this was a better stalker tool than social media.

Why is this game changing for data governance and why should you care?  It begs us to ask, even if a regulation is not hanging over our head, what is the ethical use of data and what is the responsibility of businesses to use this data?

Technology is moving faster than policy and laws can be created to keep up with this change.  The owners of data more often than not will sit outside your corporate walls.  Data governance has to take into account not only the interests of the company, but also the interests of the data owners.  Data stewards have to be the trusted custodians of the data.  Companies have to consider policies that not only benefit the corporate welfare but also the interests of customer and partners or face reputational risk and potential loss of business.

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Input To The Questions In Forrester’s 2013 Information Strategy And Architecture Survey

Gene Leganza
In a month or so I’ll be launching a survey to research issues around information strategy, information architecture and information management in general. I thought it might be useful to do a bit of crowdsourcing to get the best ideas for what questions to ask and make sure I’m covering your top-of-mind issues. We ask you all fairly often to provide answers to survey questions – maybe you’d like to provide input into the questions this time out?
 
Surveys are interesting – one is tempted to ask about everything imaginable to get good research data. But long onerous surveys produce very low percentages of completes vs. starts -- it’s classic case of less is more. Twenty completes for a very comprehensive survey is nowhere near as valuable as a couple hundred completes of a more limited survey. For example, I really wanted to provide an exhaustive list of tasks related to information management or information architecture practices and then provide an equally exhaustive list of organizational roles to get data on who does what in the typical organization and what are the patterns regarding roles and grouping of responsibilities. But the resulting question would have been torture for a respondent to go through, so I edited it down to the 15-ish responsibilities and roles you’ll see below, and I’ll probably have to reduce the number of roles further to make the question viable. 
 
So, below are the questions I’m thinking of asking. Please use the comment area to suggest questions. I can’t promise to use them all but I can promise to consider them all and publish some of the more interesting results in this blog when they come in. 
 
Here’s what I’m asking so far:
 
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How Bad Are Firms In China At Data Management?

Charlie Dai

Data management is becoming critical as organizations seek to better understand and target their customers, drive out inefficiency, and satisfy government regulations. Despite this, the maturity of data management practices at companies in China is generally poor.

I had an enlightening conversation with my colleague, senior analyst Michele Goetz, who covers all aspects of data management. She told me that in North America and Europe, data management maturity varies widely from company to company; only about 5% have mature practices and a robust data management infrastructure. Most organizations are still struggling to be agile and lack measurement, even if they already have data management platforms in place. Very few of them align adequately with their specific business or information strategy and organizational structure.

If we look at data management maturity in China, I suspect the results are even worse: that fewer than 1% of the companies are mature in terms of integrated strategy, agile execution and continuous performance measurement. Specifically:

  • The practice of data management is still in the early stages. Data management is not only about simply deploying technology like data warehousing or related middleware, but also means putting in place the strategy and architectural practice, including contextual services and metadata pattern modeling, to align with business focus. The current focus of Chinese enterprises for data management is mostly around data warehousing, master data management, and basic support for both end-to-end business processes and composite applications for top management decision-making. It’s still far from leveraging the valuable data in business processes and business analytics.
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The Kiss of Death for Data Strategy

Michele Goetz

The number one question I get from clients regarding their data strategy and data governance is, “How do I create a business case?” 

This question is the kiss of death and here is why.

You created an IT strategy that has placed emphasis on helping to optimize IT data management efforts, lower total cost of ownership and reduce cost, and focused on technical requirements to develop the platform.  There may be a nod toward helping the business by highlighting the improvement in data quality, consistency, and management of access and security in broad vague terms.  The data strategy ended up looking more like an IT plan to execute data management. 

This leaves the business asking, “So what? What is in it for me?”

Rethink your approach and think like the business:

·      Change your data strategy to a business strategy.  Recognize the strategy, objectives, and capabilities the business is looking for related to key initiatives.  Your strategy should create a vision for how data will make these business needs a reality.

·      Stop searching for the business case.  The business case should already exist based on project requests at a line of business and executive level. Use the input to identify a strategy and solution that supports these requests.

·      Avoid “shiny object syndrome”.  As you keep up with emerging technology and trends, keep these new solutions and tools in context.  There are more data integration, database, data governance, and storage options than ever before and one size does not fit all.  Leverage your research to identify the right technology for business capabilities.

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Design Thinking Blurs The Line Between Process And Experience Design

Clay Richardson

Lately, I have become a bit obsessed with evaluating the linkage between good process design and good experience design. This obsession was initially sparked by primary research I led earlier this year around reinventing and redesigning business processes for mobile. The mobile imperative is driving a laser focus for companies to create exceptional user experiences for their customers, employees, and partners. But this laser focus on exceptional design is not only reshaping the application development world. This drive for exceptional user experience is also radically changing the way companies approach business process design.

Over the past six months, I have run across more and more BPM teams where user experience is playing a much larger role in driving business process change.   Some of these teams highlighted that they see experience design playing a greater role in driving process change than the actual process modeling and analysis aspects of process improvement.

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