Interview Series — Donna Thomas
Hosted by Career in Analytics
Welcome to the next installment of Career in Analytics’ interview series. This forum is designed for decision science professionals — both beginners and veterans — to meet one of our members and engage in a conversation with them. We want our group to be a place for great conversation and debate.
This week we welcome Donna Thomas, VP of Quality Excellence at Xerox.
CiA: Welcome, Donna.
Thank you Shivanku for the opportunity to share in this event. With changes happening in the marketplace, it is critical that we help each other out by sharing our journey, experiences and outcomes in the field of analytics.
CiA: Thanks Donna, can you tell us a little about your background?
I come to the forum with a breadth and depth of experience where analytics have been a critical component to helping the organization understand process, customer experience and how they relate to the quarterly results of an organization. I have been in business transformation, operational excellence and turning engagements around. My leadership role at Xerox, as VP of Quality Excellence, has been focused on federating quality assurance functions across multiple lines of business, streamlining process and assuring customer commitments are being tracked.
CiA: So, what does analytics mean to you?
It is anticipated that the role of analytics internal to organizations as well as external is very important in learning and mastering the competitive landscape and being able to anticipate and address customer needs. To me, this means that I need to anticipate the types of questions we need answered and I need access to the data to tell the story. Questions can some from senior leadership or they could come from a program manager or a bids and proposals manager. Being able to present the data in a way that is easy to grasp and quickly understand results, workflow activities and trends to each type of audience means that your methods for communication must be effective to speak intelligently to technical teams and provide key insights to business goals which must be met by executive leaders. This past March, I wrote a posting on how I see the quality profession needing to be realigned to include this trait.
CiA: What analytics challenges have you faced in your career?
As I reflect, I see a couple of trends that reoccur throughout the business world, which can and will create chaos. In particular, having a
(1) Lack of process and or understanding of process: Leaders and managers, who are what I call second degree connected to the data, don’t seem to clearly understand the importance of data governance. Any data scientist that is working with the data owners must be very careful to explain what data governance is and what it is not, and who has the responsibility of it (which is most likely someone who is the first degree connect to the access of the data). The data scientist may need to assume more responsibility in defining the related processes for collecting, analyzing, governing, controlling and reporting the data. This seems to happen in organizations that are less mature. The data scientist cannot work in a vacuum and the stakeholders all need to be trained in the processes used so that useful collaboration and communication occurs and meaningful data-driven decisions can be made.
(2) Lack of consistent use of tools: Immature organizations tend to have different, sometimes disparate systems where data exist and there may be some pockets in the organization that has no tool in use. When this happens, the data scientist needs to learn many different types of systems to extract the data and the data scientist will need to figure out a way to pull the data into a single workplace, normalize the data and create visualization that represents the organization. When an organization works towards compliance to a standard such as ISO 9001 or CMMi, a single process can be defined and likewise, a tool evaluation can be done to best serve the organization. The use of internal audit assists the organization in assuring that the selected tool is deployed and in use across lines of business.
CiA:What is the biggest mistake that you see organizations make?
I have seen people select a tool to force fit the analytics effort without understanding what systems already exist, what data exists and what are the most important questions that the organization must know. This may be a bit old school, but an organization should know what exists first and what types of questions they want to know before they set out implementing the effort. Furthermore, the processes required to do this work should be sorted out and agreed with. Responsibilities and expectations should be well-defined and attached to performance goals with a schedule that is held accountable. Without some structure, framework and requirements well-defined, organizations tend to use a tool they selected, and then because they are limited by the tool, they don’t get the value that they were expecting. I have seen organizations have false starts and switch tools haphazardly setting back the efforts.
CiA: What is the career advice would you give to aspiring data scientists?
I believe to be successful in any organization, the data scientist will absolutely need to learn about the organization you are working in. You need to understand the formal processes and the informal frameworks inside the company. You need to speak the language of what the technical teams and the business leaders. This implies that you will need to have some operational experience in various roles first. The data scientist is not just a computer scientist, a statistician or a fancy dashboard designer. The data scientist is a trusted soul in the organization that can assist program teams, HR, marketing, bids and proposals, CIO/CTO and business with understanding the data, predicting trends based on past performance and quickly identifying on risks that need senior leader decisions.
CiA: Any closing thoughts?
If you are a senior leader and you want to understand what big data and analytics are, I highly recommend reading InformationWeek’s article called “9 Free Online Courses to Pump up Your Big Data, Analytics Skills.” Frank Kane of Udemy has some great training material that is accessible and free of charge if you use this link.
CiA: Thank you, Donna. Now we will turn things over to our members and see what questions they have.
Career in Analytics is a forum dedicated to connecting beginning analysts with experienced and veteran mentors. Our topics cover a variety of interests in the area of analytics and professional career development.
We would also like to thank — Corsair’s Publishing for their help in bringing this content to you!
