In the world of leadership, one of the hottest topics is how artificial intelligence (AI) is changing the way we design, conduct, and execute work to improve organizational performance. At the same time, in the world of technology, one of the hottest topics is how to consolidate and integrate large quantities of disconnected data so AI tools can use it to predict future organizational performance.
Although the rage, AI is not new. It has been around for over fifty years. What is new is the advanced applications of AI to propel organizational performance. In this regard, the recent advances that have been made are nothing short of mind boggling. AI is changing organizational life in ways that rivals the industrial revolution. Truly, there is a lot riding on AI!
Perhaps more fascinating is that the AI evolution is in its infancy, which further boggles the mind. By all accounts, we are only scratching the surface of how AI will propel organizational performance. And by the way, AI holds all the cards when it comes to creating the long-awaited anytime, anywhere workforce, where collaborating around performance virtually on any device is the gold standard.
So important is this stage in the AI evolution that I coined the term “AI Gold Rush” to represent what is occurring. Like the California Gold Rush, the first-in are writing all the rules and reaping all the rewards. In this gold rush, data is the currency of choice and progressive leaders are grasping at the opportunity to outperform competitors with the use of data.
However, as we wave good-by to the Information Age where the volume of data reigned supreme, and say hello to the Collaboration Age where the application of data reigns supreme, leaders must adjust quickly, or they will simply be left behind. To gain the competitive advantage greatly depends on the level that leaders achieve to predict future performance – the ultimate game changer!
To accomplish this, progressive leaders are looking to build ‘data lakes.’ For those of you that are not familiar with the term, it is a storage repository that holds a vast amount of raw data in its native format until it is needed for analytic applications. While a traditional data warehouse stores data in hierarchical dimensions and tables, a data lake uses a flatter architecture to store data, primarily in files or object storage.
Data lakes are unique unto themselves. In simple terms, they incorporate structured and unstructured data in one repository liken to a lake of information. As the amount of data continues to mount, the lake expands in depth and width. The primary driver behind this movement is to use the data to predict future results through analytics.
Two leading authorities on analytics are Jeff Deal and Gerald Pilcher. In their recent book “Mining Your Own Business” they state: “Instead of making decisions based on reports about what has happened, the organization relies on information found in these repositories to predict what is likely to happen.” According to these experts, data plays a central role in helping leaders leverage AI to manage through the windshield of tomorrow and not through the rearview mirror of yesterday.
However, it’s not simply a matter of building data lakes, it’s how leaders use the data in them that matters most. From a performance perspective aggregating and storing historical performance data to manage operations in a free-form manner opens the door to a host of application possibilities, many of which are not yet conceived.
As an organizational consultant and researcher, I have observed leaders from the C-suite to line managers struggle to keep their finger on the pulse of team progress because much needed data was not readily available at the right time nor in the right form. As teams scour a multitude of disconnected resources to find the data stored in work silos – handwritten notes, note-taking apps, workflow apps – leaders become ever-more frustrated.
Then there is deluge of emails, voice mails and text to retrieve and communicate the information that was not available in the first place which further frustrates leaders. Authorities in organizational performance, myself included, realize that the resulting loss in team productivity caused by this daisy-chain can be devastating and that lost productivity can never be recaptured – an irrefutable fact.
I refer to this egregious time-wasting exercise as ‘silo surfing.’ This is a colossal waste of resources that impedes performance. It has no place in the organization of today. We live in the age of collaboration where the democratization of knowledge trumps all else and the governing of data to predict results takes center stage.
Michael Porter, the renowned academic and business consultant at the Harvard School of Business may have said it best: “instantaneous equates to competitiveness.” This is the reality of modern-day organizational life. In the final analysis, without maximizing the speed, accuracy, and accountability to produce results, an organization cannot remain on the forefront of the competitive landscape. This means taking the collaboration game to a whole new level!
Companies are in a race to out-collaborate competitors whether they realize it or not. To optimize collaboration starts with consolidating and integrating performance information in data lakes. From this repository, leaders and teams can effortlessly put their hands on critical information when it is needed and in a form that is needed while predicting future performance.
Data! How it is sourced and how it is used matter most. As the currency of choice, building performance data lakes only makes sense. By doing so, leaders can see in their operation what competitors can’t see in theirs, giving them the competitive advantage. Progressive leaders get it and are cashing in on the AI Gold Rush as I write. Truly, there is a lot riding on AI! To learn more about how Targa, an AI-driven SaaS platform, intrinsically builds a performance data lake please visit our website at www.targatek.com.