Need somewhere to start? How about the most wanted pages; or the pages we know need more work; or even the stub that somebody else has started, but hasn't been able to finish. Or create a ticket for any issues you have found.
MIKE’s Integrated Content Repository brings together the open assets from the MIKE2.0 Methodology, shared assets available on the internet and internally held assets. The Integrated Content Repository is a virtual hub of assets that can be used by an Information Management community, some of which are publicly available and some of which are held internally.
Any organisation can follow the same approach and integrate their internally held assets to the open standard provided by MIKE2.0 in order to:
Build community
Create a common standard for Information Development
Share leading intellectual property
Promote a comprehensive and compelling set of offerings
Collaborate with the business units to integrate messaging and coordinate sales activities
Reduce costs through reuse and improve quality through known assets
The Integrated Content Repository is a true Enterprise 2.0 solution: it makes use of the collaborative, user-driven content built using Web 2.0 techniques and technologies on the MIKE2.0 site and incorporates it internally into the enterprise. The approach followed to build this repository is referred to as a mashup.
Feel free to try it out when you have a moment- we’re always open to new content ideas.
Did You Know? All content on MIKE2.0 and any contributions you make are published under the Creative Commons license. This allows you free re-use of our content as long as you add a brief reference back to us.
Few companies manage information better than Google. If there were an annual award for corporate information management (IM), I’m sure that Google would have won it–or had been in the top three–over the past decade.
Why take IM so seriously? Because, quite frankly, without it, Google becomes much, much less valuable. Sans information, how does Google really help us? It helps us find what we want; Google doesn’t directly give us what we want. In other words, we don’t spend much time on google.com. We use it to go to the sites that let us buy things.
Information is a key asset for every organization, yet due to the rise of technology, web 2.0 and a general over abundance of raw data, many businesses are not equipped to make sense of it all.
How can managers overcome an age of “information overload” and begin to concentrate on the data that is most meaningful for the business? Based on your experience, do you have any tips to share?
A new McKinsey Quarterly report,The rise of the networked enterprise: Web 2.0 finds its payday, released just this week is proving to be a treasure chest of information on the value of collaborative technologies. This new release of a series of similar studies from McKinsey over the years comes out of a survey of over 3000 executives across a range of regions, industries and functional areas. It provides detailed information on business value and measurable benefits in multiple venues of collaboration: between employees, with customers, and with business partners. It also examines the link—and finds great correlations—between implementing collaborative technologies and corporate performance.
Few companies manage information better than Google. If there were an annual award for corporate information management (IM), I’m sure that Google would have won it–or had been in the top three–over the past decade.
Why take IM so seriously? Because, quite frankly, without it, Google becomes much, much less valuable. Sans information, how does Google really help us? It helps us find what we want; Google doesn’t directly give us what we want. In other words, we don’t spend much time on google.com. We use it to go to the sites that let us buy things.
It turns out that we ain’t seen nothing yet. Google has been fine-tuning Google Now (Google Alerts on steroids.) From a recent TechCrunch article:
Google Now is a standard feature of Android Jelly Bean and up. It’s an easily accessible screen that shows you information about your daily commute (because it learns where you go every day and makes an educated guess as to where ‘home’ and ‘work’ are for you), appointments, local weather, upcoming flight and hotel reservations (assuming you give it access to scan your Gmail account) and how your favorite team did last night (it learns that from your search behavior). It also notices when you are not at home and shows you how long it’ll take you to get back to your house, or, if you are travelling, presents you with a list of nearby attractions you may be interested in, the value of the local currency, the time back home and easy access to Google Translate.
In a post-PC world, it’s not hard to understand the vast potential value of a personalized technological companion who can help you navigate an increasingly busy and complex world. With what Google knows about you via email, Web-surfing habits, social connections via Plus, and the like, Google Now may in fact be a game-changer.
Implications for Big Data
But you can only do so much on your Android device. What if you could see things? What if wearable technology and augmented reality could make your life even easier (or creepy, depending on your point of view)? Enter Google’s Project Glass, a pet project of Sergey Brin.
If you think that data is big now, get ready for Really Big Data. What if you could just think about recording a walk in Paris and publish it to YouTube in the process? What if you could review a product on Yelp by talking to yourself at the store? Perhaps speech-to-text technology would then publish that review automatically? Maybe your car will drive you to your next appointment on your Google calendar.
Does this sound Kurzweilian? It should. Google just hired the legendary futurist.
The implications are nearly limitless. As technology continues to evolve into heretofore “protected” areas, more and more data will be generated. Companies like Amazon, Apple, Facebook, Twitter, and Google have the compute power and storage capacity to actually do something with this data. Machine learning, text analytics, natural language processing, and other
Simon Says
The enabling technologies behind Big Data are getting better every day. We’re just getting started. Your organization ought to be preparing for a data-driven world right now. If not, it may very well fall and not get up.
A little over two years ago, I began what was once the unthinkable: I became a Mac guy again. After more than a decade of exclusive PC use, I became fed up with Microsoft’s products and terms of service. I made the jump.
However, buying a Mac and completely weaning myself from my PC are not one and the same. In fact, as expected, it has been a transition more than a clean break. That is, I didn’t follow Jerry Seinfeld’s Band-Aid advice.
A few legacy apps like Microsoft Access and my admittedly long-in-the-tooth accounting system forced me to straddle the fence for a few years. However, as Windows XP nears its decommission date, I am going into 2013 with the intent of being Microsoft-free.
To do this, I needed to purchase a new accounting program. By way of background, for the last ten years a “mature” accounting system called MYOB. It wasn’t the sexiest application, but it got the job done.
As I exported the data from MYOB to Quickbooks (for the Mac), I noticed that my data management habits weren’t exactly perfect over the past decade. (Nothing major, but a few things annoyed me in my quest for data perfection.) In a few cases, I had duplicate vendor records. Some of my customer master information was incomplete.
What to do? I spent some time in Excel doing some “winter data cleaning.” I considered the following questions:
What better time to cleanse this data than now? (I’ve said many times that new system implementations represent opportune times to clean things up.)
Why not purge records vendors and customers with which I have had no contact in the last five years? (For instance, I no longer pay the same electric and cable companies that I did while living in New York and New Jersey.)
Why not start life with Quickbooks as cleanly as possible?
I had no one else to blame. “Simon, Inc.” is a very small shop and I do all of my own bookkeeping. Still, the way that I do my books has slightly changed over the last decade.
Simon Says: Be Your Own Chief Data Officer
I’ve written before on this site about the role of the chief data officer (CDO). It was high time that I took my own advice. While this small business example might lack the nuance of a large organization, I’d argue that the same principle applies. It’s my data and I alone take responsibility for it. Why not make it as clean as possible before migrating to a new system?
In fact, I’m going to make this an annual occurrence. Cleanse what I need, purge what I don’t, and review it all.
As many of us prepare to go on leave over the Christmas/New Year period we’re cleaning-up our email and perhaps grumbling about the avalanche of electronic messages! I was reminded of a post I wrote in 2010 when I defended email as a business tool. Two years later, and I think that email is as much a part of our lives as it was then. That doesn’t mean we can’t do it better and I figured that it is timely to re-post my earlier comments.
Any serious business discussion about information must include email. Like it, or loathe it, email is a major part of every knowledge worker’s life. Unfortunately many staff have grown to hate its intrusion into their personal time, the fragmentation of their work and the expectation of a rapid reply to important messages.
The result has been that many people argue that email should be phased out and replaced by the next generation of social networking and collaboration tools within the enterprise. To some extent, this is true with collaboration and business messaging tools continuing to gain in popularity. However, email still remains the most popular way for most people within business to share information.
There are some things that we can do and in this post I suggest two quick actions that can change the email culture.
First, create the concept of “email bankruptcy”. The term has been around for a while, but it is time to give it some formality. Many staff report that exiting the company they work for, and the resultant clearing of their email, is a tremendous relief. In effect we’ve created a reward for resignation, which is usually the exact opposite of the behaviour we want to encourage.
A potential solution is to allow staff to declare themselves “email bankrupts”. The act of doing so will result in a declaration, through a message to all who have sent an email outstanding in their inbox, that nothing prior to the given date will be read or actioned. The bankrupt then has a clean inbox and a fresh start.
Declaring bankruptcy should have some consequences, but they must not be too serious (name and shame would normally suffice). In addition, like a financial bankrupt, they should be given some assistance to help them avoid the situation in the future.
Second, encourage staff (starting with yourself) to batch email sends. Email was created based on the analogy of paper memos. Those memos went through an internal or external mail system (“snail mail”) that caused a natural lag in the communication. People typically looked at their incoming mail in the morning when they came to work. If there was a backlog of mail they took it home in their briefcase to read and reply – but the sending was done the next day.
There is nothing wrong with doing work out-of-hours. What is a problem is that the resulting messages appear in our colleague’s inboxes within moments of us sending them, creating a reminder that they should perhaps be working as well. Worse, the near instant nature of email encourages responses that are rapid rather than considered – leading to many people working through something that in the past required just one person to do it properly.
The solution is to batch email in the same way that paper memos were in the past. Email clients typically allow you to select a “delay” option. For instance, in Outlook, go to the options tab and select “delay delivery”. Set the delay to the next business day when working after hours and to a time several hours hence when responding to an email during business hours.
The result of this batching is that you still get the sense of being in control of your inbox without the depressing reality of a flood of replies coming in as fast as you deal with them. As people get used to you working this way they will consider their reply carefully so as to maximise the value in the information that you return, knowing that they can’t create a dynamic conversation.
Email is a powerful tool and to reject it outright because of its shortcomings would be a mistake. We must, however, all work to make it much more effective.
It’s a question that I’ve heard more than a few times in my consulting career, especially as organizations have moved from legacy systems to more contemporary equivalents. Most of these improvements mean that organizations can consolidate data sources and, at least in theory, store all of their data in one place.
Now, generally speaking, hoarding is not a healthy thing–and I don’t need reality shows to tell me as much. With respect to data management, though, is it really detrimental to an organization?
Amber Simonsen seems to think so. Simonsen is the PMP Executive Project Manager of Pierce Transit and talks about the perils of data hoards. ”What begins as an innocent desire to keep relevant information close at hand can turn into an unhealthy obsession that plagues IT departments and Records Managers in organizations everywhere,” Simonsen warns.
It’s a fair point, but think for a minute about data storage costs. To say that they’ve dropped in cost over the last three decades is the acme of understatement. Consider the following chart:
For more on the methodology used to derive these numbers, click here.
Considerations
So, the cost of data hoarding has dropped exponentially, even as the amount of data available has also risen exponentially. If you do the math, you’ll discover that organizations can store much more information these days than even five years ago for significantly lower costs. As a result, it’s hard to buy the “it’s too expensive to store this data” argument.
Of course, just because an organization can store a great deal of data doesn’t mean that it should. Data storage is a continuum, not a binary. What’s more, CIOs can actively decide not to store certain types of information for all sorts of reasons. Perhaps the most important consideration for an organization is what it uses to access and analyze new forms of data. If you’re trying to cram Big Data into Small Data solutions, then data gathering and storage (never mind) hoarding is going to pose a significant problem. As I write in my new book, you can’t write SQL statements against petabytes of unstructured data and expect to see meaningful results. New tools are needed to make sense of Big Data.
Simon Says
Data hoarding only makes sense if two conditions are met:
Your organization has deployed the right tools–i.e., Hadoop, NoSQL and columnar databases, etc.
Your organization actually does something with that data.
Many of us walk around with the knowledge that we generally understand how the world works. When people ask us for our professional opinions, we’re often more than happy to oblige. Some of us are even flattered when someone wants to know what we should do when faced with uncertainty.
But do we know as much as we think we do? I have my doubts, especially after finishing Everything Is Obvious: How Common Sense Fails Us by Duncan J. Watts. It’s a thought-provoking book because it challenges readers to ask themselves, “What do we really know?” The answer, unfortunately, is not as much as we think.
Simple vs. Complex Systems
As Watts points out, part of the problem stems from the distinction between simple and complex systems. Let’s take a simple situation: the game of blackjack. I’ve been known to play a few hands, and only a fool would hit on 18 with the dealer showing a six. It’s just bad strategy. In such a simple environment, the best decision is clear.
The problem with simple systems is that they aren’t terribly representative. In complex systems like, say, the economy, myriad forces are at play, the vast majority of which are not under the control of any one person, group, department, or organization. Even the US government could not completely solve the financial crisis with a $900 billion stimulus. Bottom line: there’s only so much that any of us can do in a complex system.
And, as I turned the final pages on what is easily the best book I’ve read this year, I started to think about that big question in the context of Big Data. If we truly embrace Big Data, then we will have to question many long-held assumptions about how many things work: our jobs, our departments, our industries, and our environments. Looking at data with open eyes means that we may not like what we see, nor what that data will tell us. And that makes many of us uncomfortable. How many of us want to constantly question what we think we know?
Simon Says
To me, Big Data is not all about technology. Far from it. I’d argue that there’s a human element in all new technologies, and Big Data is no exception to this rule. There’s an organizational readiness component to it, as well as a personal one. Will people and organizations unaccustomed to consulting the data suddenly change their behavior? Will they be open-minded? Or will they act as if they know how things have worked, work now, and will work in the future.
It’s a big question. Big Data may prove that you don’t know as much as we think you do. What will you do then?
Executive turnover has always fascinated me, especially as of late. HP’s CEO Leo Apotheker had a very short run and Yahoo! has been a veritable merry-go-round over the last five years. Beyond the CEO level, though, many executive tenures resemble those of Spinal Tap drummers. For instance, CMOs have notoriously short lifespans. While the average tenure of a CMO has increased from 23.6 to 43 months since 2004, it’s still not really a long-term position. And I wonder if Big Data can change that.
In a recent article for Chief Marketer, Wilson Raj the global customer intelligence director of SAS, writes about the potential impact of Big Data and CMOs. From the piece:
CMOs today are better poised than ever not only to retain their roles, but to deliver broad, sustainable business impact. CMOs who capitalize on big data will reap big rewards, both personally and professionally. Bottom line: Businesses that exploit big data outperform their competition.
Necessary vs. Sufficient Conditions
The potential of Big Data is massive. To realize it to an optimal level, however, organizations need to effectively integrate transactional and analytical data and systems. Lamentably, many organizations are nowhere close to being able to do this. That is, for every Quantcast, Amazon, Target, and Wal-Mart, I suspect that dozens or even hundreds of organizations continue to struggle with what should be fairly standard blocking and tackling. Data silos continue to plague many if not most mature organizations.
Utilizing Big Data in any meaningful way involves a great deal more than merely understanding its importance. Big Data requires deploying new solutions like NoSQL databases, Hadoop, Cassandra, and others. Only then will CMOs be able to determine the true ROI of their marketing efforts. That is, accessing and analyzing enterprise and external (read: social) information guarantees nothing. A CMO will not necessarily be able to move the needle just because s/he has superior data. (Microsoft may have all of the data in the world, but so what? Bing hasn’t made too many inroads in the search business and Surface isn’t displacing the iPad anytime soon.)
Think of access to information as a necessary but insufficient condition to ensure success. As I look five and ten years out, I see fewer and fewer CMOs being able to survive on hunches and standard campaigns. The world is just moving too fast and what worked six months ago may very well not work today.
Simon Says
Some believe that Big Data represents the future of marketing. I for one believe that Big Data and related analytics can equip organizations with extremely valuable and previously unavailable information. And, with that information, they will make better decisions. Finally marketers will be able to see what’s really actually going on with their campaigns. Perhaps problems like the one mentioned at the beginning of this post can finally be solved.
