by Jason Bissell and Calvin Hoon, Talend
Today’s enterprise IT organizations are once again experiencing a massive upheaval due to pressure from employee forces.
It’s a familiar story. Just think of the turmoil caused by the dawning of the bring-your-own-device (BYOD) era, with employees demanding to use their beloved, personal mobile phones or tablets for work. If IT balked at their requests for mobile, some resourceful users would resort to workarounds – creating ‘shadow IT’ – to get access to corporate systems on their personal devices. Of course, in the process, those employees also unknowingly put sensitive company information at risk.
Now even more IT agitations are on the way, once again being generated by employee demand. This time, users demand access to the growing pools of big data companies have amassed, and the insights they likely contain. If IT can’t deliver the tools to access the information residing in corporate data lakes, employees will — just as they did in the BYOD era — find a workaround, which will likely put enterprise information at risk. Thus, there is no other option for IT than to deliver data via self-service access across all lines of business. However, IT must find the proper way to do so in order to prevent exposing company assets to unnecessary risk. They must adopt a model of collaborative governance.
The transition from authoritative to collaborative governance of company data might be hard, but there’s an opportunity for corporate IT departments to create a system of trust around enterprise data stores, wherein employees collaborate with IT to maintain and/or increase the quality, governance and security of data. The good news is that IT professionals have a blueprint from the companies that pioneered the use of the World Wide Web for collaborative data governance. Just as Web 2.0 evolved around trends that focused on the idea of user collaboration, sharing of user-generated content, and social networking, so too does the concept of collaborative governance. Collaborative governance breaks down the technological and psychological barriers between enterprise data keepers and information consumers, allowing everyone within an organization to share the responsibility of securing enterprise data. This concept has the power to transform entire industries.
Wikipedia is a good example of user collaboration in action. Launched in 2001, it is the world’s sixth most popular website regarding overall visitor traffic. Everyone can contribute or edit entries – a mixed blessing when it comes to reliability and trust.
Or take TripAdvisor, an American travel website company that provides reviews of travel-related content and interactive travel forums. It was an early adopter of user-generated content.
Airbnb is another excellent example of collaborative governance in action. Founded in 2008 as a “trusted community marketplace for people to list, discover, and book unique accommodations around the world,” including, as the website states, “an apartment for a night, a castle for a week, or a villa for a month,” it is the users themselves that provide the venues, and the company that provides a platform which owners and travelers can leverage to share and book venues.
The greatest challenge – and enabler – for this model has always been trust. Users place their trust in others to accurately update content and information (ratings), meaning consumers are putting their trust solely in the information presented to them. The system works because the data in the system is bountiful and the platform it resides within is designed specifically to enhance user experience.
Now let’s consider the typical IT landscape in an enterprise. Information used to be designed and published by a very small number of data professionals targeting their efforts to “end-users”, or consumers, who were ingesting the information. Today, the proliferation of information within companies is uncontrollable, just like it was on the Web. We’re all experiencing the rise of a growing number of cloud applications coming through sales, marketing, HR, operations or finance to complement centrally designed, legacy IT apps, such as ERP, data warehousing or CRM. Digital and mobile applications connect IT systems to the external world. To manage these new data streams, we are watching new data-focused roles emerging within corporations, such as data analysts, data scientists or data stewards, which are blurring the lines between enterprise data consumers and providers. Just like the adoption of BYOD, these new roles are presenting challenges of corporate data quality, reliability, and trust that must be addressed by IT organizations.
As the Web 2.0 model evolved, trust between consumers and their service providers was established by crowdsourced mechanisms for rating, ranking and establishing a digital reputation (think Yelp). One lesson learned in the consumer world is that the rewards of trust are huge. These same positive returns can be realized by enterprise IT departments that adopt selected strategies embraced by their more freewheeling consumer counterparts.
Delivering a system of trust through collaborative data governance and self-service is just one of the opportunities available to evolving IT organizations. Through self-service, line of business users become more involved with the actual collection, cleansing, and qualification of data from a variety of sources, so that they can then analyze that data and use it for more informed decision-making. Currently, many companies—in their mad rush to become data-driven—are increasingly making decisions based on incomplete and inaccurate data. In fact, according to The Data Warehousing Institute, ‘dirty data’ is costing businesses $600B a year. Companies will continue to experience extreme loss and possible failure if they don’t have a sound data governance system in place.
Collaborative data governance is an easy way for IT to help ensure that the quality, security, and accuracy of enterprise information is preserved in a self-service environment. Collaborative governance allows employees in an organization to correct, qualify and cleanse enterprise information. This helps IT because the master data records are being updated by those most familiar with or closest to the data itself (i.e. the marketing analyst who cleanses tradeshow leads, or the financial analyst who rectifies a budget spreadsheet).
Additionally, fostering the crucial shift to more business user involvement with an organization’s critical data leads to numerous other benefits. For example, users save time and increase productivity when they work with trusted data. Marketing departments improve their campaigns. Call centers work with more reliable, accurate customer information, much to everyone’s satisfaction. And the enterprise gets better control over its most valuable asset: data.
So my simple message to companies looking to become more data driven: digital transformation can be achieved — it’s all just a matter of trust.