Finding the Right Partner to help you with AI Projects
The numbers are always mind-bogglingly large. AI will add $13 Trillion to the global economy over the next ten years according to Harvard Business Review. Sure, but if you’re not an actual extra-large sized enterprise, how does a small size enterprise find ways to engage AI when it seems all the top talent is already working for the big technology companies or at the very largest global enterprises.
What does a leader who’s been already preparing the company’s culture for AI adoption with a future based mindset, find the right vendor to help with this new world of data-based decision-making? Trust in algorithms is one thing, but how does a company find a trusted partner to help on its digital journey? It’s kind of like dating, with a lot of vendors waiting for you to swipe right. So, how does a company choose?
Here’s an approach I’d recommend. If you think of AI as a three-stage approach, start with that and try to see where you are and who you need to take you further on your journey. The first stage involves you asking yourself – Are you data ready for AI? Do you have a Data Platform capable of providing Basic Analytics and Reports? Are you seeing insights based on data you are generating? In other words, do you just have Descriptive Analytics or Diagnostic Analytics? Or, are you just trying to wrangle and centralize your data?
Second would be where the data would help you with operational efficiency with some algorithms and ML capabilities. Let’s call these Predictive Analytics. For this, you’d need to be further along, with your data harmonized. Lastly, for the serious growth stage, data would need to be centralized, in a lake, clean and clear so that it can be used to power growth, in revenues and/or margins where it would effect yield. This is where you achieve Prescriptive Analytics, where you use your data to prescribe the way forward.
This stage, to effectively increase Business Yield through Prescriptive Analytics, is a complex and multi-dimensional problem. For this a company would need a partner, who is experienced in how to solve these problems and who also have a deep technology stack.
Moving on to the partner, you have to seek a vendor who can really address the problem you have. The vendor should be able to clearly show to you that they have a straightforward view of how solving the problem would create value for your company. They should be able to show their capabilities clearly, and how those capabilities address the problem, not waffle about technology in general.
The next part is harder to figure out. Do they have expertise to actually solve your problem? Now expertise, which I’m defining as one part, understanding of your business and two part the serious ability to handle the Machine Learning which is much beyond, hire a data scientist and all will be well. Look, you’re unique, and you need someone who understands that, but the models created are the unique foundation of an AI solution. They are complicated and require experienced handling, otherwise, you might as well throw your money down the data swamp. Not only do the algorithms need to be superior, the engineering around them needs to be enterprise level software, delivered as an actual service your team can easily gain needed value from. All this is harder to gauge, so check on them. Do they have the ability to detail how the solution will be rolled out? How will it work? Who actually from the company will you be working with, not just the top people who are busy dining with the top corporations, to bother with you.
Ultimately, an AI solution will be a journey. So make sure you have a partner, who will be able to help you complete your journey from the first stage to the last, and who’ll be easy to travel with. So take the long view. Do your homework and find the right partner. Like everything else, the right partner will make the travel much easier and calmer.Share on Facebook Share on Twitter Share on Pinterest