By: Ali Daneshmand
Data Governance and Master Data Management (MDM) is a developing discipline and practice that, when implemented correctly, leads to a high direct and indirect ROI. But the question that comes to my mind is, how many enterprises are applying the principles of Data Governance in the spirit that it is meant to be implemented? Data Governance 101 says that all Governance Frameworks must address the people who have a stake in the data, the processes that they should follow, and the technologies that augment the Governance Efforts. The frameworks from various pillars in the industry (DAMA – DMBOK, et al) are very well defined, yet generic enough where it can be applied to all Data Driven Enterprises. So, one would think that if the framework is well defined, scalable, and repeatable, why is the governance effort of most enterprises lacking? This blog will address that very question.
Top (4) Challenges (and Proposed Solution) to Data the Data Awareness Journey
Many enterprises that engage in the journey of higher Data Self-Awareness have the greatest of intentions but realize that the motivation for change lies in a long history of inefficient operations practices. As with any journey of growth and maturity, initial change required is a very difficult and major shift in perspective and personality. Same applies to improving operational, data centric and data driven operations based on Data Governance and Data Management Best Practices. A major roadblock for many enterprises is that, despite their best intentions, they do not have the resources to grow their data maturity efficiently and effectively. As a results, the growing pains in this journey are higher than what it needs to be.
The four top growing pains that needs to be acknowledged and addressed but are generally ignored are “The Silo Affect”, the “Lack of Communication” despite optics, a major “Resistance To Change” as change implies a deviation from one’s comfort zone, and lastly, tunnel vision limiting the major effort in this journey with the mindset of “If You Build It, They Will Come”. Each area is addressed and paired with tactics on how to mitigate these challenges.
The Silo Effect
The largest “People” problem is what the author likes to call the “Silo Affect”. In referencing a previous blog article (http://w2m.3b8.myftpupload.com/2020/07/17/origins-of-bridge-the-gap-data-business-operations-it/), silos are a serious business problem. We gather machine data in one place, security data in another, customer experience and support data in another — the list goes on. This structure may make sense at a departmental level, but it prevents collaboration necessary to ensure competitiveness. Companies need an operational data layer that is core to business processes and supports data sharing.
Many times, there’s the assumption that “the other team will update the data”. So, when applying Data Management Technologies across their existing ecosystem (i.e., incorporating a Data Catalog for the first time), the perceptions of the pulse of the enterprise data are severely challenged. The first surprise is the level of disorganization of the data. Most Metadata is not consistent with their expectations, assuming that the metadata is curated at all. Surplus data is found that was previously not known. The Data Quality (accuracy, precision, thoroughness, relevance to current operations), is a mystery with no obvious quality framework. Enterprise-wide lineage is practically non-existent. The ownership of the masses of discovered data. No one silo wishes to take ownership of any data.
Acknowledge that your enterprise is having issues with your silo’s. As the saying goes, acknowledging the problem is half the battle. For the good of the enterprise, decide whether your enterprise is ok with the current silo arrangement, or if a change is needed. If you feel a change is needed, there are a few pills that need to be swallowed.
First pill to swallow is to understand your corporate history, it’s mistakes and what not to repeat. Like any major change, a serious commitment from all levels and silos are required, not just from a select few, and not for a short amount of time. Otherwise, you’re back to square one. As mentioned in a previous blog article (http://w2m.3b8.myftpupload.com/2020/07/17/communication-and-knowledge-transfer/), often cross-functional teams and business units develop a silo mentality and tend to withhold information and communication from their counterparts. This type of Tribal Knowledge negatively impacts the projects these groups are working on and the company. In the first instance, withholding information from others working on the same project prevents efficiency and progress. In the second instance, it diminishes the feeling of unity and replaces the common organizational goal with group and silo focused goals that are not aligned with each other.
Second pill to swallow is the need for assistance in this journey to data and knowledge self-awareness from a 3rd / external organization that have not been adequately vetted. A common sales strategy is to tell the client what they want to hear to make the deal. There is always a productive use for honest mirroring in the journey of improved self-awareness. But it must be honest for the best interest of the client. Honest mirroring is the basis for trust and for the journey to progress effectively from the start.
Lack of Communication
Another noteworthy challenge is a lack of clear, transparent, and practical bi-directional communication between upper management, middle management, and the lower management. Due to a fear of job security and office politics, problems at the lower levels of the enterprise are not communicated upstream to the middle or upper management. At the same time, the needs of Upper Management do not affectively get communicated to lower management. This often leads to sloth-like progress on the corporate vision with a high rate of issues. Lower Management is unfamiliar with what is expected of them. In turn, circling up their work to the Mount Olympus of the enterprise becomes politicized.
As mentioned in a previous blog (http://w2m.3b8.myftpupload.com/2020/07/17/communication-and-knowledge-transfer/), “Clear and effective communication helps businesses achieve efficiency and accuracy in both internal and external operations. As such, it is imperative to identify barriers and find solutions for having better communication and knowledge transfer. An important obstacle to knowledge transfer and overall Enterprise Operations is Tribal Knowledge.”
Every Enterprise requires bi-directional communication, from Top Down, Bottom Up and most especially across the middle. Each enterprise should decide which direction is the priority when starting the re-establishment of communication. But both directions need to be addressed. All required information should be relayed from bottom to the top. Otherwise, roadblocks will compound to such a level where the future operations of the enterprise will potentially be at risk. If the Enterprise dissolves, doesn’t matter who’s to blame. But also, from the top down, the vision and direction of the enterprise must be made crystal clear to all human resources (with minor exceptions). If middle and lower management do not know what is expected of them, roadblocks will most certainly arise.
A commonly ignored tactic is the communication across the middle of any enterprise. We are combatting the concept of “left hand doesn’t know what the right hand is doing”. Many times, different silos need to work together to accomplish a mission. This is where cross-silo communication is vital. Non-Overlapping Functional Ownership and custodial duties must be clearly defined at all levels. This is called Stewardship.
Another key tactic in combatting poor communication is developing and maintaining a central venue for Enterprise Terms and Terminologies in an Enterprise-Wide Accessible Glossary. A common habit amongst the current workforce is the misunderstanding of the meaning of a colleague’s expression(s), whether in verbal expression or written expression. This is not an issue with a diverse workforce. Quite the contrary. This is the residue of “assumption”. Assumptions on the meaning of terms used in everyday communication are made regularly. We forget, many times, that the meaning of some words and phrases have different meanings to different people, based on their past experiences. So, it behooves any enterprise to develop, maintain and make publicly available a common repository of terms.
Resistance To Change
A cultural mindset that all too often causes roadblocks in the journey of Data Self-Awareness and Data Maturity are philosophies like “If it ain’t broke, don’t fix it”; “We have always done it this way”; “It’s not my job”; “If I share what I know, I’ll lose my job”. Many times, people believe that the journey to Data Self-Awareness means loss of jobs, loss of value, or a roadblock to their career goals. Some are so accustomed to “the old ways” that they have mastered the relevant skills down to a science. Some are overwhelmed with their current duties. Some have perfected a much-needed skill that sharing their skills and knowledge is a threat to their value that they are or have monopolized for so long. In these cases, they feel threatened by any change in function.
Consider repurposing the “Hero Mentality” to a Leadership role. If someone has expertise in a particular area, and they are the sole proprietor of that knowledge, instead of hoarding that knowledge, make them a leader of that Functional Area. That way, they are not bound to one skillset to prove their value. And they are put in a position of helping the enterprise leverage multiple human Resources in that functional area.
Invest in Training, Training, Training. Training doesn’t have to necessarily be an expensive proposition. All enterprises have “Hero’s”, and “surplus” resources. When the enterprises understand their resources’ knowledge landscape, internal training becomes a valuable effort without any additional cost. This will also show the knowledge gaps in the enterprise. This will also what external training is and is not required. It is quite possible that not as much external training is required. However, this skillset discovery needs to happen.
Pursuing Functional Leadership and investing in internal training will preserve lots of jobs while facilitating the new culture of data centricity.
“If You Build It They Will Come”
Many times, enterprises are aware of their Data Self-Awareness Shortcomings, yet they smugly make use of old or incompatible processes that score more points in Office Politics than in actual increate in Data Self Awareness. Many enterprises invest heavily in a particular tool to manage their data, but have not invested in the proper internal training, with the “If you build it they will come” mentality. Some of these enterprises would hire outside consultants to do the initial work to build out their Data Ecosystem to compensate for not wanting to invest in training of their own people. Eventually, this model causes a plethora of operational headaches, and inevitably causes the enterprise to either shelf the technology because it becomes too expensive to use, or they invest in other technologies.
Prior to investing in tools, technology, or implementation partners, DO YOUR HOMEWORK. Invest in a major internal strategy audit of your data ecosystem from the people, operations and technology perspective. Either reassign internal resources to conduct the strategy audit or hire consulting firms whose niche is Data Governance / Data Management Strategy Assessments. This audit should have four general objectives:
1. Perform a Current State Analysis via consultation with relevant stakeholders across ALL silo’s, to understand the “Good / Bad / Ugly” of the enterprise’s People, Processes and Technology
2. Perform a Future State Analysis via consultation with relevant stakeholders across ALL silo’s
3. Perform a GAP Analysis on your People, on your Processes, and your Technology to understand what is working well, and what is not working well
4. Based on the Gap Analysis, develop a Roadmap that guides the effort of transitioning from your Enterprise’s Current State to its Future State. The roadmap should also include concepts of Internally and Externally sponsored Training, and a plan for Occupational Change Management, incentivizing the people to implement the desired changes.
Ultimately, automation and technology can take your enterprise so far in your enterprise’s journey to Data Self-Awareness. The journey starts and ends with people and their attitudes toward their data, their knowledge, and the process to transform one to the other. If the business does not provide a construct for Metadata Curation, even the most sophisticated technology won’t be able to help. If the Business Processes or Business Rules are lacking or non-existent, so will be the technologies’ workflows. If functional areas are not clearly defined, if expectations are not clearly communicated, if the work does not deviate from one’s comfort zone, all the investments and technology in the world would not help in the long term.