This really is about giving our teams, our executives, superpowers.
"The world's most valuable resource is no longer oil, but data." -The Economist, 2017
Without a doubt, we are in the age of data. We create and consume more information than ever before.
Believe me when I say data is the most critical aspect of your job.
A company would have only two scenarios. Their data is still a cost center, or it has the potential to become a profit center by using the data to improve everything, day by day.
Companies must begin treating data as an asset while also managing the data locally within business units. This enables sharing of data about products and customers – which provides opportunities to upsell, cross-sell, and improve customer service and retention rates.
So, why do data projects still fail if this is so critical and companies invest heavily in this matter?
Here is my professional view on this subject;
Unable to define the problem. Companies cannot define precisely what the analysis or data or IOT/AI is supposed to do for the end users, or for the business.
Data is an immensely untapped valuable asset. There is a massive opportunity for every company in the world to create new products and services across lines of business. But, despite the claims and proliferation of data promises and products, data projects are failing at alarming rates.
Overlooking Culture. "Culture still eats strategy for breakfast."
Companies implementing data analytics projects are not used to collaborating at the level required. A piece of enormous evidence that reveals this is when you’re asking an engineer to rewrite a data science model created by a data scientist.
Data scientists are hired to work in companies that aren't ready for them.
Managers hire analytics professionals who really aren't.
Projects stall. Money is wasted.
A fundamental truth, this stuff is complex.
- One of the biggest reasons is that sometimes people think, all I need to do is throw money at a problem or put technology in, and success comes out the other end, which doesn't happen.
- Another professional experience I've heard and discussed in meet-ups and conferences is "we're not doing it because we don't have the proper leadership support to ensure we create the conditions for success."
- Not having the right talent
- Not having the right data.
- One of the most challenging issues with data is always that it lives in different formats, structured and unstructured, video files, text, and images, kept in other places with different or extra security and privacy requirements, meaning that projects slow to a crawl right at the start, because the data needs to be collected and cleaned.
- Lack of clear, explicit, and agreed goals and outcomes.
- Finally, the lack of collaboration and ownership is intimately connected to those silos.
One of the most significant opportunities is to figure out how to educate business leaders across the organization.
I've witnessed people feel threatened when data projects work because the first thought is: "a machine or AI will replace my job."
“AI is not going to replace managers but managers that use AI will replace those that do not” - IBM cloud and data executive, Rob Thomas
Keeping it simple is essential to success; it is a problem if everyone is involved.
If you are a data head, a project manager, a data engineer, or a data scientist, I recommend you; define a clear problem, a pain point to solve. Not everyone is on board with your data initiatives. Meet those who are uncomfortable where they are.
Go out and talk to your customers 1 on 1.
Working with professional data scientists or automated AI programs only requires the ability and the curiosity to ask good questions and make connections between business issues and quantitative results where you can show demonstrable progress.
This really is about giving our teams, our executives, superpowers.
It is also true that you can’t deliver projects successfully 100% of the time. If you do, you have a low definition of success or have just worked on one or two fortunate projects. If you identify and plan for the potential failure points, apply some of these tips, you’d be more likely to succeed.
"Progress over perfection." - JC
What are your views or experiences on this topic? This blog would appreciate your thoughts.
