In many respects, “data” is to analytics what gold was to the gold rush. There is an immense value that can be taken from every ounce of data, more than the average person would expect. AI and ML, specifically, have limitless potential to dramatically shape how enterprises entirely conduct business.
Data accumulated by organizations over the years is invaluable to their longterm success. Artificial intelligence and machine learning are instrumental in extracting the inherent utility of said data. AI/ML generates insights from the data that leads to more efficient operations, and an increased sense of competitiveness.
But if this is obvious, why has this technology been met with so much resistance? How can we, as experts in this field, convince corporations that AI/ML adoption is in their best interest?
These insights are key to significant, incremental and strategic changes for those who are ready for it. AI/ML could be BIG Science terminology, and at the end of the day it at its core a Data Detective Mechanism.
Most businesses have their blinders on. They take problems at face value, instead of thinking about the ripple effect. The key is to work smarter — not harder — and these technologies can be a tool to do exactly that.
Say a business plots their data but isn’t able to take away any insights. Perhaps there is a microcosm of other questions they’ve failed to consider… chock it up to human error. It’s even possible they have a huge volume of data sitting there without anyone considering its significance. Want to increase performance? Want to understand your sales at a SKU or Customer Level? AI/ML is your answer.
There simply is not enough manpower or resources to consistently maximize the value of data without the assistance of AI/ML. It significantly diminishes the amount of time it takes to identify a problem and devise a solution. It offers actionable insights in near real time, preserving resources and time that could prevent the execution of time-sensitive decisions. AI/ML outperforms current methodologies and tools, hands down.
So how do we — as data analytic professionals — bridge this disconnect?
A company is the culmination of a diverse range of expertise, skillsets and experience. This conglomerate of what some could view as a source of ‘meta-intelligence’ empowers companies to execute business critical decisions, and strategically interact with customers, suppliers and enterprise personnel. Artificial intelligence is the combination of all those facets.
So how do we showcase this reality to those hesitant to abandon their legacy models?
Many customers are hesitant to explore the viability of this technology within in their enterprise, for fear that it will be a Herculean effort with very little monetary return coupled with infrastructural disruption. What many fail to realize is that building algorithms is easier than ever before because of all the tools available in the marketplace. The combination of these will help identify the right variables to redefine the model, precisely.
Helping your customers build a data and analytics empire is as simple as showcasing how effortless it is to be a forward thinking, modernized organization. Show them a proof of concept. Highlight how the introduction of AI/ML can expose hidden parameters and variables, opening their business up to new analysis, improved prediction modeling and improved operations. Educate executives at the company and explain how AI/ML can positively impact their wallet. Create enterprise-wide initiatives to ensure adoption and execution of the technology on a consistent basis. It’s not enough to change the technology, you also have to change the culture, itself.
AI/ML is the equivalent of a team of data analysts and analytic experts working 24/7, tirelessly, to identify trends and relationships that are obvious to the untrained eye. There is a learning curve for businesses and organizations to learn how to work with this virtual team and surrounding yourself with those who have dedicated their life to this industry can help you get up to speed in record time. This is where we make a difference. Our extensive experience shortens the learning’s curve and allows the prompt and effective implementation of ML/AI.
My expertise as a data analytics professional compels me to advocate for my customers and help them succeed and achieve their goals. Any responsible professional in my position understand the immense impact AI/ML can have on an organization.
If we — as a collective — have any foresight for what lies ahead, we will help our customers, we will encourage them to adopt a full-scale AI/ML takeover. It’s not a strategy as much as it is an inherent duty.
Until then, we lay waiting for the opportunity to help them reap the benefits of what some could deem a ‘Data Gold Rush.’
The Systech Solutions, Inc. Blog Series is designed to showcase ongoing innovations in the data and analytics space. If you have any suggestions for an upcoming article, or would like to volunteer to be interviewed, please contact Olivia Klayman at firstname.lastname@example.org.
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