Late last year I attended the ASAE tech conference at National Harbor and leading up to the conference, I also attended several related local sessions here in the DC area. Like most of what we’re hearing in the national media about the biggest tech trends, there was a focus on things like artificial intelligence (AI), machine learning, blockchain, voice and yes, big data. While all of these trends offer great promise to the association and nonprofit sectors and present opportunities to create new efficiencies and gain valuable insights, I worry that the mystique and allure around these forward-thinking technologies is in some way leading organizations to miss the forest for the trees when it comes to the more immediate value of foundational data modernization.
Currently, it is impossible to derive any of the intended value of these technologies given the current state of data quality that most organizations are dealing with. You can’t simply plug an AI tool or a voice application into bad data and expect magic to happen. You can’t demand that your organization start using machine learning and expect your bad data to suddenly start producing better and more strategic insights than it does now. These technologies, for the most part, are all dependent on fairly organized and clean data. Additionally, most organizations are ignoring the more immediate benefits that would be associated with simply cleaning up and centralizing their data and employing an even minimal level of data governance. Here are a few examples of the symptoms of bad data and the business costs associated with those symptoms (do any of these sound familiar?).
Symptom – Inability to create certain types of reporting. How often are you asked to provide certain metrics, measurements or KPI’s to the board or leadership and you simply can’t produce that information given the current state of your data?
- Business Cost – When an organization can’t make strategic, timely or data-driven decisions, what does this cost the organization?
Symptom – Manual workarounds. Related to the point above, how much time are people spending in a week or a month on complicated, manual workarounds to try and mitigate current data challenges?
- Business Cost – If you were to add up all of the hours being wasted on these activities and apply the salary costs associated with the people engaging in these activities, how much money in a given year is being wasted on this productivity blind spot?
Symptom – Inability to derive value from new data-driven technologies. If in fact you see real value or a realistic application of some of the new technologies listed above, how long will your organization be delayed in realizing that value?
- Business Cost – In terms of time-to-market and the ROI associated with AI or machine learning etc., how much will it cost your organization to delay these investments?
The fact of the matter is, most organizations currently don’t have a big data problem, they have a small data problem! There are so many new efficiencies and so many opportunities for immediate ROI sitting right there in front of us with our current data sets, some of which can be unlocked with even a minimal amount effort. Not only will modernization in this area create immediate results, you will also create buy-in at all levels of the organization for additional investment and create the foundation to begin taking advantage of all the super cool, forward-thinking technologies that are currently at the forefront.