Companies today risk extinction 10 years from now because they fail to maintain and establish profitable, sustainable markets. They fail because they are losing grasp of the essential data that drive the digital economy rising around them.
Businesses (and their CEOs) usually have adequate funding, vision, and assets at their disposal. Among those assets are lists of customers, suppliers, and proprietary methods for delivering products and services.
But they fall short in applying those assets. Customers, employees, suppliers, products, and ingredients are becoming digital, and we struggle to accept that assets such as customers are digital and personal at the same time. Without a clear strategy for managing digital assets in a personal way, they become disruptive or meaningless.
Simple Mistakes, Big Repercussions
I have never received a printed mailer that started with “Dear [Insert Customer Name Here]” instead of “Dear Will.” But I’ve received dozens of emails from businesses large and small that forgot to introduce the data that would offer up my name instead of “Insert Customer Name Here.”
That complacency is caused by the depersonalization that occurs when organizations consider data an afterthought and lose touch with the digital means by which they conduct business.
Of course, that misstep and others like it come down to data governance: the process of assigning value, meaning, and accountability to digital assets. It’s the organizational movement almost every business will struggle with in the next five years.
Many businesses misunderstand data governance to be risk management associated with data, but the performance value of data is often far more important. In reality, the value lies in businesses repatriating responsibility for digital assets back into the line-of-business functions.
Said another way, the number of businesses that fail because they did not manage compliance risk is limited, but the number that fail because they lose track of what they “know” about a customer or a service is high. Therefore, to govern data right is to scale up knowledge in parallel with system complexity. It’s to build a body of execution knowledge that provides meaning to data in the context of a business process or delivers analytical insights by assuring the business a level of trust through ownership and quality.
Businesses are also losing valuable opportunities because they lack confidence that their data have a consistent meaning and discipline of ownership. And when businesses lose opportunities, they have to learn why.
Historically, the “authorship” of data has been considered a back-end clerical function, but it’s becoming less tolerated for management to blame its minions. Many organizations mistakenly relegate data quality to their IT departments, forgetting that a database administrator will rarely know a customer as anything more than a row within a vast data pool.
Data governance is not a problem exclusive to big businesses, either. Small businesses are also amassing data rapidly across systems that are on premise and in the cloud — what we often refer to as the “hybrid environment.”
Many of those systems are fragmented and focused on departmental functions. But the fragmentation puts businesses in states of unintended complexity — especially when solving key challenges in visibility, such as how to create 360-degree views of customers. Or, more fundamentally answering the question “What is a customer?” so that everyone can leverage the data with a common viewpoint.
How Data Governance Can Help
The stigma of data’s complexity needs to be debunked, especially given data’s benefits, which are strikingly simple.
- Your business will perform better.It’s as simple as running on higher-octane fuel. A business that runs on trustworthy, high-quality information runs faster, smarter, and leaner because it encounters fewer bumps in the road.
Delivering improved insights for better-leveraged spend or improved customer experiences will occur with fewer touchpoints and greater simplicity if your data policy enables aggregation from across systems. Moreover, businesses can innovate faster because the cycle time for introducing new products is largely determined by data collaboration below the task level.
- Your organization will feel empowered.Don’t wait for the army of data scientists to arrive. Start making the entire organization more data-savvy. Developing business ownership of data is not easy, but once businesses have overcome the inertia, they see significant boosts in confidence and spirit from their teams. Building a knowledge base of data context through data policy gives leaders a better platform for connecting vision, strategy, and tactics with clear outcomes.
Clearly, data suffer from a likability crisis. It seems easier to blame data or the people in IT than to learn what the data represent. But building a data citizenship model that maps the company’s core values to the work product and consumption of information empowers the organization to act on information more effectively at all levels.
- You will experience a more agile business environment.Organizations that trust their data require fewer meetings and fewer debates on interpretation. A better output of results means organizations become adaptive rather than reactive.
Many organizations today suffer from an “upward delegation” of decisions because they lack the insight and leadership to execute within the level. This upward delegation grinds organizations into reactive positions. Data governance empowers the many layers within the business with an ownership of data and the insights drawn from it, resulting in fewer upward delegations and more agility.
Turning Knowledge Into Action
Whereas the benefits of governing data right are countless, the ways to do it are finite. The two overarching strategies are simple and effective.
- Leverage the community.Industry and user group-based communities dedicated to data governance have been studying the successes and failures of their field. Many are fluffy marketing displays, but a few user group-based communities, such as one focused on SAP, have strong backgrounds in stimulating business-centric dialogue. Those venues demonstrate that the opportunities to manage the quality of information, to syndicate information, and to compile large data sets to achieve big data opportunities are mature and capable.
The primary problems, though, are leveraging actual experience and repeating success. Entry into the community dialogue should happen with an upfront understanding of “rules before tools.” Don’t let the tool-value discussion disrupt your learning path.
- Take a guide for this journey.This step epitomizes Marshall Goldsmith’s mantra of “What got you here won’t get you there.” Data governance is a management and organizational learning event that should be based on iterating toward success so that the organization can adapt and develop the skills to connect your values system to the new standards of work product.
Therefore, look to find a partner who has the pedigree and experience to teach your team how to fish. You will never outsource data governance because no third party will be able to tell you “who” your customers are or which address is a shipping address and which is a billing address.
These are business-led segments of knowledge, and your team must learn how to be accountable for the data, understand its context in the business, and drive decisions by its use.
By, Will Crump, president and CEO of DATUM.