I’ve been doing a great deal of research on Apple lately for my new book. In so doing, I’ve stumbled upon some amazing tales with lessons for information management professionals.
Andy Hertzfeld (Apple employee number 435) writes about the company struggled to release the 1983 version of the Macintosh. Engineers struggled to fix bugs as its deadline neared. Unable to triage every issue, Hertzfeld was placed in the unenviable task of having to recommend to Steve Jobs the company postpone the release by a few weeks. In his words:
“No way, there’s no way we’re slipping!”, Steve responded. The room let out a collective gasp. “You guys have been working on this stuff for months now, another couple weeks isn’t going to make that much of a difference. You may as well get it over with. Just make it as good as you can. You better get back to work!”
The entire story can be read here. In a word, it’s fascinating.
Jobs was ahead of his time. He understood then–as many do now–that there’s no such thing as perfect. Yet, many folks in organizations resist change and new data management initiatives because perfection cannot be achieved. From a consultant’s perspective, this is very frustrating.
A Little Yarn
For instance, I worked on a very contentious project about four years ago migrating systems for a large hospital system. The hospital was retiring its legacy mainframe finance and payroll system. In its place would be a modern ERP application with all sorts of bells and whistles. Web-based reporting, e-mail notification, and fancy dashboards would replace paper reports.
Except that it wouldn’t.
The data from the hospital’s legacy system was a complete mess–and was in no position to be loaded into the new ERP system. Those visually appealing reports and dashboards would be useless.
Of course, this wasn’t surprising, as it had never been cleansed over the past 25 years. Some fancy data manipulation and the creation of several ETL tools improved the data by orders of magnitude.
But it wasn’t perfect.
Conversion and load programs would correctly kick out errant records. Lamentably, key internal players on the project focused only on those legitimate errors, not the tens of thousands of (now much cleaner) records that successfully loaded by virtue of meeting a complex array of business rules. A finance director in particular would seemingly always ask, “How can I be sure that something else isn’t wrong?”
This was precisely the wrong question to ask, but his doubts resonated with other key players. The project was a mess and exceeded its budget and deadline by ghastly amounts.
Simon Says
Expecting perfection is the acme of foolishness. Yes, diligent data management professionals and functional end-users should care about information loaded into new systems. What’s more, it’s vastly easier to correct and edit records in Excel, Access, or any number of tools versus a CRM, ERP, or other application.
At the same time, though, the majority of these applications provide industrial strength tools to fix errors. Database refreshes, purge programs, and batch error handling mechanisms collectively allow for mistakes to be fixed. Don’t wait for perfection. In the words of Voltaire, “The perfect is the enemy of the good.”
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What say you?
