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March 12, 2015

People and Data: Two Important Assets

Over the past couple of weeks, I have come in contact far too often with the starkest impact of low commodity prices on our industry. Whether the elimination of positions in a company is called a layoff, a reduction-in-force, a redundancy, or a strategic trimming, it's still the same. People lose their jobs. During my career, I've been on both the giving and receiving end of this situation and I can assure you that it is not pleasant on either side of the desk.

The price of oil and gas is set on the global market and we all react to the cash flow implications of low commodity prices. In the operating companies, first capital budgets are trimmed, then projects delayed or canceled, and finally all that is left for trimming is personnel. In the service companies, the reality hits much sooner as they are quickly impacted by the operators reduction in capital budgets and the resulting reduction in the rig count.

Our industry is known for technological innovation; fiber in wellbores for monitoring, subsalt seismic imaging, nanotracers in fracking fluids. Unfortunately, we are also an inefficient industry. With the advent of the shale revolution, that's changing, but the base cost of operating has a new hard deck and companies are facing very real challenges. The most common metric of efficiency for a long time has been cost per barrel. The numerator in this metric (cost) gets most of the attention. We've seen the cost of wells in the shale plays significantly reduced over a relatively short period of time. Thankfully, some companies are now also focusing on the denominator (barrels). Whether I achieve my lifting cost goals by cutting the cost in half or by doubling the production, I end up with the same result when measured in $/BOE. How can we get more oil with fewer wells? Once again, the answer lies in taking specific actions, monitoring the results, tying those results back to the actions, and analyzing what happened. After a while, lessons are learned and the actions can be changed or prioritized to gain more favorable results. Of course, this means that the data is in a state that it can be trusted: that it's current, correct, complete and consistent. And this means the decision makers realize the efforts and people that are now being viewed as a purely discretionary cost are in reality a cost saver once the total cost of ownership is taken into account. We don't drill a well or bid in a license round without due diligence and running the economics. The same should apply to how the data and information are handled.

Every decision the business makes is based on the data and information at its disposal. If data and information projects and support are cut as discretionary overhead, those business decisions may get very expensive indeed.

And also remember, when you meet that former colleague in the market, they are the same person that they were before the redundancy. They were a victim of global politics, economics, and the resulting corporate decisions. Most importantly, they deserve to be treated with the same dignity and respect as they were when oil was over $100 a barrel.

March 4, 2015

Best Way to Reduce Data Governance Resistance

Have you ever wondered why the most brilliant data governance implementations don't reach their full potential? The answer often has more to do with people resisting the new technology, not the technology itself!

I agree that this is not shocking news. What is shocking is that most data managers know this and just don't know how to address it.

The best way to reduce data governance is simple ─ focus your efforts on influencing the people who have to adopt the new technology or solution.

For that to happen, everyone (managers and staff) needs to shift from "my data" and "my way" to "our data" and "our way." Thinking a New Way
The shift from "my data" to "our data" is not a slogan; it is a shift in how people view themselves, their data, and their role in the company's data quality.

Think about how the solution will impact each of the roles and groups of people. Consider what they need to hear to overcome the natural resistance to change and embrace the new solution; and who would most effectively deliver those messages, such as managers, executives, or subject-matter experts. You must find ways to motivate people to be involved, give them opportunities to take ownership of the data, and then adopt the new solution.

Focusing on People: A Case Study
Let's take one simple example of creating enterprise-wide definitions for well attributes. An oil and gas client created a new data governance team tasked with drastically improving data quality, so people trusted the data and made better decisions.

To do this, they started by establishing enterprise-wide definitions. Our client's new data governance team brought representatives from every business unit together in a conference room. No matter what the term - whether it was "first production date" or "spud date" - there was little agreement. It quickly became apparent that there were many different definitions. Some business units even had two answers driven by different management groups.

This also meant the client couldn't make trustworthy decisions about any other data attributes. This realization brought new meaning to the concept of "data-driven decisions."

Over the next several months, the data governance team ended up sitting in that conference room with their business counterparts and defining hundreds of terms. As they worked through the definitions, they built a team, appreciated how each business unit was different and learned how to collaborate so that the data worked for everyone. Then the business representatives reviewed every definition with key subject-matter experts (SME's) in their business unit. This elevated the way their business colleagues viewed them. It also engaged key people within their business unit. Any concerns raised were eventually resolved in the conference room.

Once the team reached an agreement on the definitions, they used the same process to build rules for each definition, such as minimum and maximum ranges for the input, or the best options for a drop-down menu that would satisfy all the business units.

It took a long time. Sure, it would have been much easier just to give them the best industry definitions and rules; but, it was so worth it. Our client now had a data governance team who had new insight into differences between the business units. The team created a partnership with business representatives who were data leaders for their business. Silo walls were disappearing within the business unit and across units. The business reps saw how they were making a difference for their business and their company by being stewards of their business data, building their motivation and commitment. Moreover, the business representatives created a partnership with the SME's in their business unit who were also becoming champions for this new way of working with and thinking about, their business unit's data. Our client was building a key group of "influencers."

Results from Focusing on the People
There was finally the ownership of the definitions and rules within each business.

As business rules were implemented, the business representatives facilitated the data correction within their business. Business staff corrected data that failed to meet the rules and started to focus on data quality at the time of entry.

Everyone gradually gained more trust in both the data and each other.

Most importantly, resistance to the new data governance solution - roles, processes, systems, and tools - was significantly reduced.

Let us know
What do your stakeholders need to commit to the new way of working; and how will you engage them so they will change how they think and work?