'Communitized' Stewardship Along Your Data Value Chain - Part 2
We tried painting some colors around the lack of cumulative responsibilities of stewardship around our data value chain 2days ago by peeling off the onion to expose some examples of common quality issues in such an environment. Cost of the Absence of 'Communitized' Stewardship
Like I said there's no magic to governing the ungoverned and trusting the untrusted data in your ecosystems. You simply need to address this.
Quality issues, gaps, and leakages in your data will continue to short circuit the potentials of your data asset and future innovative initiatives until you build the foundational accountability around your data value chain with 'communitized' stewardship.
Activating Stewardship with assigned roles and responsibilities is definitely the starting point for operationalizing an effective Data Governance adoption in any organization aspiring to harness the full potentials of their data asset. In my checklist for Governance success, I called out the fact that stewardship activates Governance adoption by bringing the desired 'governance on paper' to life with the needed cultural transformation of turning every data citizen to a responsible steward of the data they engage in their day to day operations as the data travels through its lifecycle and value chain.
Your governance desires can only be truly actualized when you engage effective stewardship to drive your adoption journey. Hence, 'Communitizing' Stewardship is highly recommended as a mandatory prerequisite for every organization desiring to position Data Governance as the success driver for all its competing data demands.
Why Communitize Stewardship?
The lifecycle and data journey of every organization's data is always very unique as data moves across our ecosystems in different ways. Data once created are intended to be used for multiple purposes and in combination with other data throughout its lifecycle to achieve the organization's internal and external needs.
To this effect, data typically travel hub to hub and a lot happens along the journey from the authoring or origination of data to its final consumption and reporting points for several needs.
A typical data journey involves authoring, sourcing, collection, aggregation, and transformation at different points along the journey. This journey typically involves data movement from one technology platform to another and one business process to another with different actors engaging the data along the way.
To this effect, a lot can happen to the data along the way i.e.
· Data Quality issues may be introduced at the onset of a data journey at origination. Quality issues at origination often account for the highest percentage of data quality issues in most data.
· Other quality issues may be introduced as data journeys from hub to hub and change actors and players that engage the data due to a number of reasons.
· Quality issues introduced at the onset of a data journey might create compounding issues and impact downstream platforms and consumers across the data journey.
Simply put, the more hubs and handshakes along a data journey the more data is prone to data quality issues.
The best way to mitigate the introduction of quality issues along a data journey is to build cumulative stewardship of due diligence with formalized roles and responsibilities around your data value chain.
Building cumulative stewardship as part of your Data Governance adoption ensures that each handshake along the data journey is reviewed, validated and attested between each stewardship actor(producer & consumer) as the data makes its way across the enterprise landscape for various reporting and decision making. Your actors and stewards along the data journey are strategically positioned to ensure defined quality rules around data at the onset of its journey is enforced and maintained throughout the lifecycle.
So, what are some of the benefits of building cumulative responsibilities around your data value chain?
· Cumulative Stewardship allows due diligence to be enforced and monitor by all actors and data citizens that engage the data around its lifecycle.
· Cumulative stewardship builds a sustainable guardrail around governed, trusted data once established to prevent recurrence of leakages, gaps, and re-introduction of quality issues.
· It provides a sense of responsibility to every data citizen engaging the enterprise data one way or the other. Thereby, cultivating the desired cultural transformation of data governance across the enterprise.
· It allows data citizens to be equipped and empowered to play a critical role in enterprise data maturity.
· Traceability of Data Issues becomes easier and simplified
· The cost of data fixes and temporal remediation of data quality issues is significantly reduced once an organization ‘communitize’ stewardship along its value chain.
· Ultimately, the enterprise data maturity and trust around your data asset increases at an accelerated rate once stewardship is built around a data value chain.
In a nutshell, ‘Communitizing’ stewardship around your data value chain will not only help accelerate your Data governance adoption, but it will also help optimize the ROI on all your other initiatives. i.e. MDM, AI, ML, and other regulatory initiatives.
For more detail and to help kick off Cumulative Responsibilities around your Data value chain. Book a Free Call with me to discuss your challenges and we can explore simple strategies for actualizing your governance success.