The global IT industry seems to have entered a new phase in its youthful evolution. No longer do we have customers banging on our doors to get our latest offerings; instead, we have to do a hard sell, demonstrating exactly what benefits will accrue to buyers if they make use of our solutions.
Perhaps it is time to look at enterprise IT from another angle, building the supporting structures on a firm foundation of data quality processes.
Julian Field, MD, CenterField Software
And that`s how it should be: IT is not a driver or an entrepreneurial leader, but a backroom function that acts in support of the business. As the back-office driver keeping the engines of business running, there is a fundamental aspect that will make IT an indispensable addition to business if technical departments pay close enough attention to it and business executives place the appropriate focus on it. If ignored, it leads to failure, no matter what solutions organisations attempt or even how well they implement them.
This fundamental issue is data quality. In every conversation about IT I have had over the last few months, the issue we always end up talking about is data quality. When organisations need to implement some type of integration exercise, for example, there`s no point in deciding on what product can meet the company`s needs or what applications or data formats to standardise on if the corporate data is not clean.
In other words, can you populate whatever solution you want to implement with data taken from all corporate databases sure that there are no redundancies, no errors in spelling or format that could create two records for the same account, and no bits of data that should gave been deleted but for some reason are still in use? And let`s be serious, in any enterprise, even SME-sized entities, data quality issues such as these and many others exist and cause problems on a daily basis.
Even in the pharmaceutical sector, many companies saw a future of integrated databases and applications that would enable "point-and-click" drug development. Back in the post-dot-com-boom reality, many of these organisations have learned the ugly truth of just how bad much of their data is and how hard it is to get value from it. This is a key reason that point-and-click drug development is not a common occurrence.
Knee-jerk reactions
Once the quality problem is recognised, often the knee-jerk reaction is to look for an application that will magically fix the data quickly and allow the company to continue its implementation - almost as if data quality is a side issue.
Of course, this only solves the immediate problem, allowing the enterprise application integration or process redesign and unification to go ahead as planned without too many delays. However, the next time a large project needs to be undertaken, the company is left with the old Dinner for One situation of: "Same procedure as every year, James." The whole data quality exercise - and it can be expensive and time-consuming - needs to be repeated.
Unfortunately, the way most corporate IT architectures are structured, heterogeneous applications and databases are the norm and data quality projects are not an option if IT is to deliver meaningful information to applications and users. Perhaps it is time to look at enterprise IT from another angle, building the supporting structures on a firm foundation of data quality processes.
This type of infrastructure will permit IT departments to do whatever they need to do in support of the business without any costly mid-project delays. From the boardroom perspective, IT will be there to provide all the services expected of it without any excuses of not having accurate data to work from or putting requests on a waiting list while extracting, cleansing and loading data into a data warehouse.
In other words, IT can serve the business as was originally intended and not the other way around as has happened in recent years. Constructing a solid foundation is par for the course for any building project: with a strong support structure, you can create almost anything.
The same should apply to IT. An effective data quality foundation does not solve all IT problems, but is a business enabler; an IT architecture without data quality is a disabler, demanding more time, effort and money to provide the support business should expect from IT.
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