[As is the case with our 8 things series, the opinions expressed in the 5 myths guest columns are those of the guest contributor and not necessarily mine or AIIM's. This guest post is by Robert Hillard from Deloitte Touche Tohmatsu. As usual, contra perspectives welcome.]
Myth #1 –We'll all work less hours in the 21st century.
Reality -- In the 1970s and 1980s, many writers -- such as Alvin Toffler in “Future Shock” -- mused that the increasing computing capability available to business and government was going to greatly reduce the work required to run our economy and society. We were told that in the twenty first century, our biggest challenge would be to decide what to do with all our leisure time!
For example Mechanix Illustrated published an article in 1968 titled "40 Years in the Future" (by James R. Berry) which confidently stated: “People (will) have more time for leisure activities in the year 2008. The average work day is about four hours."
The reality has turned out to be very different and it’s time to start asking, how did they get it so wrong? (Or when can I start taking mid-week holidays?) Affordable computing power has increased as predicted, yet something else must have happened as well?
This is not an academic argument. Technology projects cost too much and are getting much more expensive despite the continual reduction in the cost of the computing capacity itself. Despite the elimination of many, if not most, clerical roles from organizations, we are seeing a shortage of available staff to run our businesses. The status quo is not sustainable.
In the 1980s most businesses had just one form or entry process to complete each major process such as bringing on new staff, registering new customers and creating products. By the 1990s, businesses introduced call centers and online channels with many different processes – each of which were mirrors of their original process but, ungoverned, created their own unique records, documents and other content – each adding exponentially to the complexity of business computing. Is the problem that we are creating more data?
Myth #2 – We're creating more data than ever before.
Reality -- I often hear people talking about the amount of data that is being created as being unprecedented. It isn’t. What is unprecedented is the disparity of content (such as with all the different business processes) and, even more importantly, its retention. We are all conditioned to the "growth of data." This is really lazy language and should be changed to the "growth of the retention of data." A business process which creates data has probably been always creating it, but until recently it was probably just transient.
When someone proposes a new approach or product, the best way to determine if it is actually new is to measure its use of information. But what does this mean?
Consider Amazon who recommend books for your future purchase. The data that they use isn't new, you have always had an identity and you always made individual book purchases, it is just that it wasn't previously kept beyond the time of the transaction. The approach to handling the data is new, but the data isn’t.
While Amazon isn’t really creating new data, a small number of business innovations are actually creating something that didn’t exist before. Consider the creation of a loyalty scheme by an airline where a new interaction is generated, which is the redemption, which provides new information.
In other words, a small number of people are writing something new. However, the rest of us may have just stopped throwing-out the rubbish and may even be able to extract some value from it.
Myth #3 – An infinite crowd is infinitely wise.
Reality -- All that data needs someone to bring it together. It’s very fashionable at the moment to deal with quantity and complexity of information by turning to a crowd. After all, an answer from the crowd (such as with Wikipedia) is always better than something you could produce from your own small team, right?
The wisdom of the crowd is great, but it isn’t going to differentiate your business in the longer term– after all, that great idea is probably available to everyone else. True “ah ha” moments come from unique insight, the lone inventor (or small team) who look at a problem in a completely different way.
The crowd can find an idea that already exists in the mountains of information rubbish (through six degrees of separation), refine the answer or test the insight. Ultimately though, the crowd is best at ensuring that we maintain the status quo. We are herd animals and the crowd is the ultimate herd!
We have to stop assuming that the analysis of massive amounts information by massive numbers of people will always give us a better answer. The next “big idea” to solve world hunger, fix the economy or improve the environment isn’t likely to be a small increment to existing approaches sourced by the crowd. The next “big idea” takes a genius who is prepared to turn their back on the herd and take the risk of being wrong.
Myth #4 – Email was a 20th century tool.
Reality -- Because people assume that we are now always going to be working as part of a crowd, there is a movement to get rid of email. What role does one-on-one communication have anyway? Plus, most of us are being buried under a mountain email and desperately want a way out!
Rather than give up on the modern version of the business “memo," there are two quick things that we can do:
First, allow staff to declare themselves “email bankrupts." The act of doing so will result in 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 metaphor 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.
Modern email clients allow us to set the priority of email and to delay their sending for a few hours or until the next day in business hours. IT leaders should encourage the use of this feature.
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 maximize the value in the information that you return, knowing that they can’t create a dynamic conversation.
Myth #5: All documents and unstructured content are equivalent.
Reality -- A part of responsible rather than quick communication is putting the information in context. We assume that all content is equal and don’t put it in the context of where it sits in the organization. All material can be identified as sitting at one of four layers in the information landscape:
Layer 1: Metrics -- For information to be used for management decision making, it ultimately needs to be summarized into a score or metrics against which “good” or “bad” can be defined.
Layer 2: Dimensional or Navigational -- At this layer we are talking about structuring the content in way that we can find in a systematic way (via a taxonomy). It is from here that metrics, such as a count or score, can be derived. It is also from here that we go to find content in its general form.
Layer 3: Normalized or Atomic -- In the unstructured sense it is better to use the term “atomic” for this layer which contains the content in its original form referenced by the event that created it rather than a business taxonomy.
Layer 4: Operational -- The fourth layer is the front line and refers to the situation and technology context in which the content is created or updated.
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