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The Lean Post / Articles / What Is Information Waste?

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Administration & Support

What Is Information Waste?

By Steve Bell and Mike Orzen

September 2, 2011

Excess information — in our inboxes, hard drives, shared drives, intranet sites, data warehouses, etc., — is waste. This unnecessary "inventory" causes congestion, delays, inefficiency, errors, and rework, note Steve Bell and Mike Orzen in Lean IT. In this excerpt from their book, the authors offer examples of info waste and advice on identifying and eliminating it.

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The many benefits of electronic information systems are often offset by the waste they generate. Too many times we have witnessed lean teams attempt to improve a process, but the moment they return to their keyboards, theyíre forced to act out the same old familiar and wasteful practices in their daily work. Information waste produces many harmful consequences, including lost productivity, costly delays and errors, and unnecessary complexity. Often manifesting as confusion and frustration, information waste is felt by everyone who interacts with the organization.

Data is of course important, but I put greater emphasis on facts.

-Taiichi Ohno, Toyota

Excess Information Inventory Waste

In an office or manufacturing context, excess inventory is a highly visible symptom, a beacon to illuminate the search for root causes of wasteful activity. From a Lean IT perspective, what is excess information inventory? It is too much virtual stuff — in your inbox, your local hard drive, shared drives, intranet sites, and data warehouses. Excess information inventory is work backlog waiting to be done, unnecessary e-mails in your inbox, unused features in software applications, local spreadsheets impeding the flow of work as a process skips across departmental boundaries, and so on. Excess information inventory causes congestion, delays,inefficiency, errors, and rework. Everyone in the enterprise struggles against info-glut.

Most people naturally hoard inventory; itís a primal instinct that goes back to our hunting-and-gathering days. Having too much stuff buffers you from variability, since you always have enough even when your supply runs out for a while. For this reason, excess information inventory is important to seek out because it indicates that the process itself, the flow of work that the information supports, is unreliable. More information (e.g.,additional data, better software, and more automation) alone is unlikely to fix the problem.

Just like excess physical inventory is stored in warehouses, excess data and documents are stored in data warehouses and repositories throughout the organization. The effort required to capture, store, search, and manage these data just in case they might be needed is wasteful, even if storage space is abundant and inexpensive. This waste is compounded by data fragmentation, version control challenges, excessive security controls, and other flow inhibitors caused by excess information inventory.

Information Overprocessing Waste

Another form of information waste is overprocessing, of doing more work than necessary. A common form of overprocessing is the overdesign of a software application, creating unnecessary navigation, keystrokes, and other forms of complexity. Less than half of software features are typically used, but once implemented, they must all be maintained and supported. This non-value-added effort creates a burden for users and IT staff alike. Unnecessary transactions are another common form of information overprocessing, including unnecessary approval steps, and excessive data capture to feed calculations and reports that donít support efficient workflow or effective decision making.

Multitasking is a pandemic form of overprocessing waste in the business world. At one time we all considered multitasking a virtue to be cultivated, but now we realize that constant interruptions and task switching are unproductive. In the Harvard Business Review article “Manage Your Energy, Not Your Time,” Tony Schwartz and Catherine McCarthy suggest that, Distractions are costly: a temporary shift in attention from one task to anotheróstopping to answer an e-mail or take a phone call, for instanceó increases the amount of time necessary to finish the primary task by as much as 25 percent, a phenomenon known as ìswitching time.î Itís far more efficient to fully focus for 90 to 120 minutes, take a true break, and then fully focus on the next activity.

Most people require about 15 minutes to productively resume a challenging task when they are interrupted even by something as innocuous as an e-mail alert, scientists at Microsoft Research and the University of Illinois found in a 2007 study. While 15 minutes may not seem like much time, if interruptions occur several times a day, this can add up to serious performance degradation — or worse.

Interruptions seem to be a fact of life, but they are costly in terms of time, concentration, and quality. Awareness of this fact can, over time, lead to changing work patterns and communication practices, and setting aside uninterrupted time and space to tackle difficult tasks. In our experience, especially in the office environment, many interruptions are for simple status inquiries such as “Where is this?” “When will that be done?” and “What do you need from me now?” The effective use of simple visuals to communicate status and priority of work can significantly reduce interruptions, improving the quality and efficiency of work while creating a more enjoyable workplace.

Poor Data Quality Waste

Yet another type of information waste is poor data quality. Often a sleeping giant within the databases and spreadsheets spanning the enterprise, poor data quality is both a cause and a consequence of poor process design and operational execution.

The lean principle of quality at the source means that data quality is everyoneís responsibility. Ideally, data should be captured once at the source, with the appropriate time and effort invested in getting them right the first time. Ultimately, the process owners (not the IT organization) should take responsibility for data quality, establishing standard work and error-proofing methods, accompanied by supportive measurements. High-volume transactional processes with data quality problems are often well suited for the rigorous analytical techniques emphasized by Six Sigma.

Links with useful information about lean information technology:

  • Slides from the Lean IT workshop show why a lean IT effort is important to a successful lean transformation.
  • Article: Lean IT as a Factory?

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Written by:

Steve Bell
|
Mike Orzen

About Mike Orzen

With a consulting and coaching career spanning more than 20 years, Mike has gathered a unique blend of lean, IT, healthcare, and operations experience that he uses to coach organizations pursuing enterprise excellence.

Read more about Mike Orzen

About Steve Bell

Steve launched LeanAgileNGO.org in 2010 to improve operational excellence and innovation among non-governmental aid organizations (NGOs). The organization’s mission is to help them learn, scale, and spread continuous innovation, improvement, and learning across their locations, programs, projects, and partners. LeanAgileNGO (and its partners) provide a platform for large global NGOS,…

Read more about Steve Bell

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