Even with the wealth of data at companies’ disposal, getting actionable insights from data has never been harder. Data collection has become quick, easy, ubiquitous—maybe too much so. Within the last five years, the volume of marketing technologies has hit an incredible 5,000 technologies, pushing data generation through the roof.
Not to mention the multiple mobile technologies and apps emerging and pushing further speed and volume of content updates, campaigns and new releases.
As a result of the rapidly expanding technology landscape, it can be difficult to say which data is useful and which is useless. Digital analytics technologies can’t keep up with quickly changing digital ecosystems—the technology is still unable to match the cadence of the digital-lifecycle and compensating for the shortcomings of heavy process and human resource is a challenge.
To put it another way, a digital ecosystem comprised of multiple models and technologies has a level of complexity to be reckoned with. Real-time decision-making adds another dimension of complexity.
Hence today, too many organizations are still struggling with their data-driven decisions.
Thankfully corporate awareness about the complexities of digital measurement has grown significantly—they have come to terms with the reality that up to 80% of data collected online could be wrong or irrelevant.
Emerging roles in the C-Suite, such as Chief Data Officer and Chief Digital Officer, as well as data scientists and digital analysts, are now demanding a lot more from their online data. Especially Chief Digital Officers, who are in charge of the global digitization of organizations, have higher expectations of their real-time insights than raw data.
Well-structured business processes alongside data governance automation will be the game changers the market has waited so long for. Proper governance infrastructure paired with the right technology will help more members of the organization contribute to the conversation—even if they are not digital analytics experts.
An inventory-build-audit-fix cycle is decisive to manage global projects and to execute them locally with a focus on excellence—thanks to automation. Reaching such an ambitious goal requires the appropriate set of technologies embedded into a structuring model that allows agility and flexibility to include organizations’ idiosyncrasies in the data collection process.
Thanks to this kind of approach, digital analysts will then be able to refocus on much more valuable and exciting tasks and missions. They will be able to think again about data collection strategy, about building consistent and solid longer-term projects, and, whatever the size of their organization may be, they will be able to think global and to act local.
In our era of globalization, the winners will be those who do not forget the meaning of the individual. Achieving such a goal requires a great capacity for hindsight and anticipation.
I will be presenting “Data Governance Automation in 2018: Think Global, Act Local!” at the upcoming Analytics Summit on November 9, 2017. I will speak about how the real-time digital industry relies on actionable data and insights, discussing state of the art business processes and data governance automation. Register online to attend my session where I’ll dive deeper into this topic.
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