Strong Leaders, Strong Results: Our Path to Data Analysis, Literacy, and Governance
While success is everyone’s goal, identifying the secret behind success is nearly impossible. Outside circumstances—and even your competition—can influence how we define victory.
But there are a few factors that we know play a role in successful outcomes. Leaders must have an eye for strategy and making data-based decisions. But they can’t simply internalize that vision—a large part of their success lies in communication. Appropriate resources are also required for success. Many business projects fail because they’re not willing to commit the necessary financial or human resources to get the job done right.
Other elements of success are industry-specific. The sheer size and level of complications related to projects in geological fields require a more strategic approach to decision making. Because of this, creating the right architecture for our data analytics system is a critical element—and it has to be done right, no matter how long it takes.
Making the Commitment
Celebrating our 25th anniversary in 2020, the is now one of the top three oil-producing companies in Russia. We continue to strive to become the global benchmark in safety, efficiency, and the effective use of cutting-edge technologies in the oil and gas industry. We are involved in every stage of oil-based products. That process begins with hydrocarbon exploration and the production of high-quality oil and gas. It ends with the retail sale of a wide variety of petroleum products, much of it going through gas stations spread around the region. We are truly a one-stop-shop for energy.
Even though we’re based in Russia, we have operations in many areas of the world, including South America and Africa. With more than 70 subsidiaries related to production, refining, and direct sales, we are one of the largest energy operations in the world. In 2019, our net profit was over $5 billion USD and we currently employ over 50,000 people.
An engineer by education, I found a career home in Business Intelligence operations. I joined Gazprom Neft in 2013 as the BI Department Head. When I arrived, they were already a year into their journey with , and I was tasked with further developing our internal Qlik-based processes.
My first task was obtaining all financial information for the company, along with any information I could find regarding best practices for Qlik solutions. This was quite a daunting task, as I comprised the entire BI department. I was solely responsible for the development, implementation, and deployment of our Qlik operations.
As anyone who has led a one-person office on a new initiative can attest, the allocation of resources can be a huge challenge. At the time, server resources were a major problem. In addition, the company was not always on schedule in the purchasing of new equipment.
Despite these concerns, I did have a few reasons for optimism. Perhaps most importantly, I had full support from top management. The CFO was especially interested in the potential benefits of a robust BI unit. I cannot emphasize enough the importance of leadership support. Change management is difficult enough, and without clear signaling from company leadership, it is especially hard to overcome internal resistance.
There were a number of times over the years where failed calculations or incorrect indicators could have derailed our progress. But our leadership's support set a tone for the future, and their firm commitment to the journey led to a revolution of sorts. There was no doubt that our leadership wanted a real transformation into a data-driven culture, and that made the path in front of me a little easier. We were able to take our time and develop expertise and structures for data analysis, data literacy, and data governance.
Developing Data Literacy
Perhaps one of the central premises of becoming a smarter organization is acknowledging the need to evolve. No major project or initiative reaches the finish line looking exactly the same as it did when it began the race. Accordingly, our team evolved as our data analysis competence grew.
By the end of 2014, there were three of us in the BI office: one developer and two analysts. In addition to having basic analysis skills, every staff member was required to know structured query language (SQL). A year later in 2015, we required mathematical statistics and languages like Python. As our functionality developed, so too did the various categories of staff expertise.
As part of our effort to recruit top analysis talent, we worked closely with a number of universities. We have a long history of offering internships to students from a variety of backgrounds. Many of these students eventually joined our organization as full-time employees. That allowed us to help shape students and develop the kind of skills we would need from our future employees.
Fortunately, we also had a number of existing employees outside BI that wanted to understand more about data analysis. We worked to develop their skills through a series of internal training courses. These courses had a number of purposes, such as getting staff comfortable with utilizing Qlik. Employees also needed to develop trust in the data itself, which required the ability to test analysis results.
However, the ultimate goal was helping employees to develop data literacy tools. They needed to fully understand how to analyze data. Qlik provides some powerful tools for managing and presenting data, but without the ability to interpret the information there is no benefit. Building a data-driven culture meant training staff to make trustworthy decisions based on data.
As our BI skills expanded, our team increased further. We created a number of specialties in order to fully serve the needs of our company, including a variety of developers, analysts, architects, and data quality experts. Today, we have more than 100 specialists all using the Qlik platform to power our data intelligence projects.
Providing Structure with Data Governance
Our data governance structures have also developed significantly in the past few years. We knew that becoming a data-based culture meant providing each employee with the tools they needed to reach their individual goals. This in turn meant giving each developer the freedom to make discoveries relevant to their work. Our stakeholders and leaders were also committed to giving the team increasingly complex challenges. That kept our staff excited about the possibilities of BI.
As the number of Qlik users grew, it was also necessary to establish a number of standards. We focused heavily on data quality and developed a single dictionary. This document established standard terms for dimensions and expressions for all departments. That made it much easier for data literacy growth and the sharing of dashboards or reports across the organization.
As a result of our training and outreach efforts, by 2015 the number of users had grown significantly.
The Challenges Of Scale
We were excited to grow our analytics capabilities as our data literacy and governance practices improved. But because our organization is so large and diverse, scaling presented a number of additional challenges. While we were able to establish standards, there was no way to create a company-wide infrastructure. We instead had to allow several areas to develop their own solutions.
For example, finance management offices use data for planning and forecasting according to production operations. Human resources staff, on the other hand, need to manage recruitment and staff training and development. It wouldn’t have been efficient to try and develop solutions that attempted to do everything for everyone. Instead, we allowed each functional unit to develop their own infrastructure and rules according to their resources and needs.
Similarly, we needed to develop different organizing principles for data processing and storage. Architectural needs often change based on the data source and the necessary layers. Some Gazprom Neft divisions needed special formulas and specific data sources to analyze financial performance. Retail unit managers may need an expense analysis, for example, to analyze sales in the regions of presence.
Taking a more individualized departmental approach also allows us to offer specific benefits to staff outside of traditional BI functions. To encourage Qlik adoption, we created an internal certification program for users in different layers. Each user was able to learn the knowledge and skills specific to their work environment. We used this system to develop 250 champions, who complete and share reports across the organization. The courses are now offered online, making them accessible to the entire company.
On the Right Track
Of all the signs of our emerging data-based culture, perhaps our dashboards are the most telling. In the beginning, we used simple displays with only a few data points. Today, our dashboards are filled with a large number and a variety of data points. In addition, each level of the organization is able to access information specific to their tasks.
Executive-level employees can set high-level visions and standards based on their dashboards. This information then flows down to department heads, who are charged with translating these goals into more specific objectives. The process continues down to frontline staff, who are able to access information specific to their daily tasks. This arrangement provides a powerful method for conveying data-driven decisions with clarity and speed.
We’ve taken a long road these past seven years, but we learned something every step of the way. We’ve transformed BI from a small office to an intricate part of the company culture. We are proud to consider Qlik a partner in that transformation. Qlik is now the gold standard for data management, data quality, and decision making. Thanks to their platform and our commitment, we will keep our customers moving for decades to come.