Common Ownership Challenges

Process Ownership Challenges

Governance and ownership challenges often arise in an organization for four reasons:

  1. Business stakeholders who resist assuming ownership of their own processes, data and/or knowledge, or have balkanized/siloed accountability
  2. Turf wars or power struggles between groups of stakeholders
  3. Lack of maturity in one or more areas
  4. Resistance to established governance rules

The Business Struggles with Accountability

Processes often have a number of stakeholders, but no apparent owners. This results in opportunity costs as compulsory process changes (e.g. legislative requirements, systems capacity, or company structural changes) or process improvements are not implemented because the business process owner is unaware of the change, or no clear business process owner has been identified which leads to an increase in risk.

Sometimes processes have a number of stakeholders who all think they are the owners of parts of the process or the whole process. When this overlap happens, each supposed owner often identifies their own strategy for the process and issues their own process change instructions to conform to their understanding of the purpose of the business process. These conflicting instructions lead to frustration and confusion by all parties involved.

Lack of accountability in process and system leads to inefficient processes, organizational disharmony, and wasted energy that can be better spent on process improvements.

Turf Wars

Due to silo thinking there can be subdivided processes, owned by different parts of the organization. For example, count how many types of change control your organization has. This requires silos to be broken down, and this takes time.

Lack of Maturity

Governance is challenging if process maturity is uneven across the organization.

Failure to Adhere to Governance

It can be hard to get the business to apply policy and standard consistently.

The role of a data steward

With data integrity on everyone’s mind the last few years, the role of a data steward is being more and more discussed. Putting aside my amusement on the proliferation of stewards and champions across our quality systems, the idea of data stewards is a good one.

Data steward is someone from the business who handle master data. It is not an IT role, as a good data steward will truly be invested in how the data is being used, managed and groomed. The data steward is responsible and accountable for how data enters the system and ensure it adds value to the process.

The job revolves around, but is not limited to, the following questions:

  • Why is this particular data important to the organization?
  • How long should the particular records (data) be stored or kept?
  • Measurements to improve the quality of that analysis

Data stewards do this by providing:

  • Operational Oversight by overseeing the life cycle through defining and implementing policies and procedures for the day-to-day operational and administrative management of systems and data — including the intake, storage, processing, and transmission of data to internal and external systems. They are accountable to define and document data and terminology in a relevant glossary. This includes ensuring that each critical data element has a clear definition and is still in use.
  • Data quality, including evaluation and root cause analysis
  • Risk management, including retention, archival, and disposal requirements and ensuring compliance with internal policy and regulations.

With systems being made up of people, process and technology, the line between data steward and system owner is pretty vague. When a technology is linked to a single system or process it makes sense for them to be the same person (or team), for example a document management system. However, most technology platforms are across multiple systems or processes (for example an ERP or Quality Management System) and it is critical to look at the technology holistically as the data steward. I think we are all familiar with the problems that can be created by the same piece of data being treated differently between workflows in a technology platform.

As organizations evolve their data governance I think we will see the role of the data steward become more and more part of the standard quality toolbox, as the competencies are pretty similar.