The CIO Playbook: 3 Steps to Bridge the Data Divide
Many businesses today are scrutinizing their operations to figure out how to join the digital transformation revolution. They understand that to become more competitive and customer centric, they need processes that are flexible, integrated, insightful and scalable. They understand harnessing data and infusing business processes with it is the key to success.
Unfortunately, poor data management practices, which cost businesses $3 trillion a year, according to a Harvard Business Review article written by Thomas C. Redman, are often overlooked as a key blocker. When it comes to the impact caused by poor data quality, the figures speak for themselves.
To turn that enormous loss into opportunities, CIOs need to better operationalize data at enterprise scale — putting qualified, clean, reliable data into the hands of more employees for them to then analyze and make informed decisions quickly. With the new emphasis on agility through digital transformation, CIOs now have the power to enable rapid change within their businesses by developing digital strategies with data at the core. These leaders have to change the departmental view that data is solely an asset used primarily by data scientists and to expand it to encompass data use by the entire enterprise.
Before CIOs can enable greater insight through self-service, they need to rethink their roles within the broader organization — shifting from simply being a caretaker of utility-type technologies that run the business to being a facilitator that helps users leverage data to gain insights.
CIOs and IT leaders need to create a foundational roadmap that:
Digital transformation doesn’t just involve the technology a company implements or says it’s going to deploy to be more customer centric; it also means making sure enterprise data is clean and accurate. It means ensuring that enterprise data is easy to find, analyze and share.
Corporations have spent years and billions of dollars trying to create better internal data systems by building centralized data warehouses using integration appliances to eliminate data silos. But these efforts focused solely on integrating internal systems and often neglected to include the multitude of cloud, social, internet of things (IoT), smartphone and other external applications or unstructured data sources that generate massive volumes of information.
As these new external datasets and applications are incorporated into enterprise data lakes, CIOs need to determine the best way to ensure the accuracy and integrity of this data, while also providing broader access to it. Without solid data integrity practices, bad data will continue to thwart a company’s digital transformation and hinder its competitiveness.
Bad data practices often lead to hours of lost productivity. For example, according to Redman’s article, “Salespeople waste time dealing with erred prospect data; service delivery people waste time correcting flawed customer orders received from sales. Data scientists spend an inordinate amount of time cleaning data; IT expends enormous effort lining up systems that ‘don’t talk.’ Senior executives hedge their plans because they don’t trust the numbers from finance.”
It’s time to include those who handle customer data on a daily basis to help maintain its quality. It can no longer be just an IT department function. New self-service solutions are equipped with intuitive interfaces such as Excel that make them familiar to non-data experts. Most of these solutions can automatically recognize common errors in datasets, such as errors found in email addresses, phone numbers or postal addresses, and guide users through the necessary actions to correct them.
CIOs are ultimately responsible for making sure enterprise information is available, accurate and secure.
