I’ve been interacting with a few customers over the last few months, and our core discussions have focused on data governance with respect to the new age of data discovery and predictive modeling. One of the repeated discussions we had was about the gap between the governed and ungoverned, and many of them see that it’s widening. Several of the executives worried about the mainly known perils of ungoverned data discovery, predictive modeling, and ultimately, the applied decisions.
These discussions inspired me to write this blog post. The intent is not to boil the ocean regarding the parts of …
Those of you familiar with the children’s story, “The Three Little Pigs,” know that a big bad wolf visits each of the pigs’ houses in anticipation of a savory meal. However, (spoiler alert here) only one little pig’s house ends up being strong enough not to be blown over by the big bad wolf. Well, that’s because that smart little pig knew that having a strong foundation for his house—in this case building it with bricks and mortar —would shield and protect his investment and literally save his skin when he needed it most.
Zoominfo.com recently published a nice data decay infographic (a small version is included at the end of this post), that shows the level of master data change for business information. Why is understanding data decay essential? Many times organizations think that if they establish a huge, one-time effort to clean up their key master data elements, they won’t need to do it again.
Not true, as the infographic demonstrates. Your data can decay over time. Addresses and zip codes are always changing because of postal authorities. People move and change jobs frequently.
What are the key considerations associated with starting a data governance initiative within an organization?
Although organizational readiness for governance varies by company, there are some common points that are often discussed and should be considered when beginning a governance initiative. Check out this list of five critical elements to jumpstart a data governance initiative by Chris Cingrani at Capgemini, which provides a good foundation for a successful endeavor.
Recently at Sapphire, I attended several micro-forums and sessions on data governance and data migration. It was interesting to hear about data governance and how it’s so closely related to the key issues surrounding designing new business processes. The issues are similar to what workflow and business process experts face today.
Workflow and Business Process Design Challenges
When talking about workflow and process design, three main issues always come up:
Ownership. Who owns the process? Workflow is a business-focused process that technologists help implement. The workflow itself drives a business process that’s completely owned by the business and …
When managers think about a business, they do so in terms of data: sales volume, inventory, margin, product turn, operational overhead, and other metrics. Data is the language of business. It’s the basis of functional control and, above all, of decision-making. Our ability to figure out where to go next depends almost entirely on our ability to understand where we are now.
All other things being equal, then, the better our data, the better our decision-making. Unfortunately, business managers often find themselves in the position of having to make decisions based on data that is inaccurate, incomplete, out …