Why?
Data Science, Generative AI, Predictive Analytics. No matter the term organizations pour millions of dollars into trying to be more data driven but often end up with very little to show.
It's frustrating.
Good intentions all around and yet data projects seem to always struggle across the finish line. We wrestled with the same thing, both as vendors and clients.
Then the moment of clarity. And with all such realizations, it's obvious in hindsight. Poor ROI for data projects is born from the mismatch between the messiness of data science in the real world and the quixotic focus on perfection in our goals for it.
But there's a better way.
How?
ef·fec·tive·ness
/iˈfektivnəs/, noun
the degree to which something is successful in producing the intended or desired result
Taking a step back, we know that all projects have to compromise due to unknowns that crop up after boots hit the ground. Unfortunately too often that ends up being forced and rushed in a desperate attempt to salvage yet another sinking ship. Instead of focusing on a perfect solution, we have as our goal an effective solution.
Effectiveness means making these compromises consciously and deliberately, building them in from the start. We take a pragmatic, realistic, and scalable approach that helps you gain immediate value from your data while building the pathway to better data effectiveness in the future.
People
The majority of business data being generated by people, your data culture is as critical to your data pipeline as the actual data entry/capture mechanism.
Process
Skilled, engaged personnel need to be doing tasks that make sense. An effective approach looks at the how of your data, not just the what.
Technology
Effective technology is not necessarily the latest and greatest. You need to take into consideration your budget, capacity, and data sophistication.
We meet you where you are today to get you to where you need to be tomorrow.
Who?
Andrew has a wealth of experience in leading digital transformations at various organizations.
He has held numerous C suite positions and has been responsible for driving data innovation by moving organizations from decision driven data gathering to true data driven decision making.
He has led the creation of initial proofs of concept generative AI tools that combine the people and AI aspect to create practical, safe, and reliable solutions.