8 minute read
Career
3Ways to Avoid Costly Organizational Decisions
BY PAM HARALAKOVA MARMON ’05
As an organizational change management consultant, I work with companies that struggle to embrace change. Grand visions can be stifled by inability to execute the work. Too many choices blur the right choice and frustration sets in.
But that doesn’t have to be your story. Leaders are made based on their ability to make decisions and manage risk. Practicing the art of great decision-making allows you to focus on growing your legacy, your people, and it can ultimately lead others to Christ.
You want to prevent your organization from making decision-making mistakes that lead to costly projects, low employee engagement, and limited growth. Here are three ways to avoid common mistakes:
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CRAFT CLEAR GUIDELINES
Without proper decision-making guidelines, our ability to make effective decisions is at risk. Minimal guidance increases the probability for indecision, limited action, and less than optimal results.
Create decision guidelines that align with your organization’s mission, vision, and priorities. It’s best if you have fewer than 10 decision guidelines and they are widely communicated. After all, if you fail to communicate, even the best decision guidelines are irrelevant.
If your organization struggles with the need for consensus, then a potential decision guideline may sound like, “We trust our colleagues to make decisions and understand that for the sake of speed, all cannot be included in the decision-making process.”
DEFINE ROLES
Some organizations thrive on a consensus-based culture. In such organizations, people may have been rewarded and recognized for giving voice to every individual. That process can generate a greater amount of ideas, but it comes with a high cost of lower speed of adoption and agility.
It’s important to remember that everyone in your organization has a role to play when it comes to significant decisions. Assign who is responsible, who is accountable, who needs to be consulted, and who needs to be informed.
EMPOWER YOUR PEOPLE
When one leader makes most of the decisions in your organization, it’s likely to result in faster task completion but with a potentially damaging aftermath. When decision-making is not adequately shared throughout the organization, neither is risk and accountability.
Leaders empower people by delegating authority, which increases team engagement. The role of a leader is to set a vision, equip people to move toward that vision, provide guidance, and enable others to lead. Decisionmaking is critical in establishing ownership, and when there’s ownership, engagement follows. Great leaders sparingly use the “golden vote,” or the right to veto decisions, and allow others to share in the commitments, failures, and successes.
Pam Marmon is the CEO of Marmon Consulting, a change management consulting firm that provides strategy and execution services to help companies transform. Growing up in Bulgaria and moving to America has taught her to be adaptable and resilient to change. Marmon and her family live in Nashville.
WISE DATA
BY SARAH POTTER JOHNSON ’00
CALVIN’S DATA SCIENCE MAJOR DELIVERS CHRISTIAN PERSPECTIVE IN BURGEONING FIELD
The data about data is mind boggling. One study shows that internet users generate about 2.5 quintillion bytes of data each day. Another says that the big data market is nearly $140 billion. Data is being collected by social media companies, banks, researchers in the natural and social sciences, utility companies, sports teams, government agencies, and even your robot vacuum cleaner.
As the deluge of data expands, so does the need for people who know how to make sense of it. In 2017, Calvin became one of the first Christian colleges to launch a major in data science.
“Learning how to deal with huge volumes of data was clearly an increasingly significant area of study,” said computer science professor Joel Adams, who collaborated to launch the program.
FUNDAMENTALLY INTERDISCIPLINARY
Because of the nature of data science, the program couldn’t just live in one department. Jake VanderPlas ’03, who has worked as an astronomer and data scientist at University of Washington, explained that “preparation to be a data scientist is inherently interdisciplinary: you have to dig-in on the math and statistics, dig-in on the computer science and software engineering, and find a field or application where you’re interested in building your expertise and applying those skills.”
At Calvin, data science majors take classes in computer science, statistics, and an applied field. The core classes students take in the humanities and arts also strengthen their ability to solve complex problems and create visual models, said Adams.
—JOEL ADAMS
– KENNETH ARNOLD
What are some of the complex problems that data scientists encounter once they start working in the field? That’s a question that Michael Bloem ’04 has helped answer for Calvin. He’s part of an advisory council that offers guidance for the major.
In his career at several companies, Bloem has used data analytics to better understand things like how many burgers a fast food chain should make and how businesses can best use their office space. Now, Bloem works at Amazon on its supply chain optimization technologies team. “Our team owns decisions about what we’re going to buy, who we’re going to buy it from, and how much we are going to ship to different warehouses,” he said.
CHRISTIANS IN DATA
Ethical issues arise when human beings consider how and why to collect, analyze, and draw conclusions from data. And the potential for Christians to influence the field includes and extends beyond ethics, Bloem said.
“As Christian colleges scramble to launch data science and analytics programs, we have a unique opportunity to create distinctive programs that go beyond churning out data wizards,” wrote computer science professor Derek Schuurman in a recent article in The Christian Scholar’s Review. “Christian colleges are well-positioned to train faithful and responsible computer scientists who recognize that not everything that counts can be counted, even with the most complex algorithms,” he wrote.
Professor Kenneth Arnold agrees. “A lot of the secular narratives around tech ethics are pretty narrow,” he said. “If you look at the conversations happening in data and ethics, they’re trying to correct power imbalances. But what we’re trying to do at Calvin is cultivate virtue.”
Arnold joined Calvin’s faculty in 2019 and teaches several data science courses. He completed a PhD at Harvard University in 2020 and received his master’s degree from the Massachusetts Institute of Technology (MIT).
“Virtue and integrity as a data scientist involve a lot of humility. You don’t just show a result, but you also show the process and explain the limitations of your findings,” he said.
DATA FOR GOOD
Ivanna Rodriguez ’20 was drawn to study data science because it was an avenue for her to act justly. She intended to study economics and international studies, but got a taste for data science through a job with the Calvin Center for Social Research her freshman year. “I was getting data from different sources, cleaning it, and making visualizations to present it to clients,” she said. “It was really interesting and exciting work.” She decided to add a data science major and now works in the Youth Policy Lab at the University of Michigan, using data to understand and find solutions to social challenges youth face. She uses available information like census and spatial data and performs computational operations and statistical modeling to answer specific research questions.
“Calvin taught me that data science can be used to advance the gospel,” she said. “I want to use data science to bring justice to people who have been marginalized historically.”
The details and intricacies of data can also reveal new layers of understanding about our Creator. “I’m interested in thinking about how data, and data science, can help us worship,” said Arnold.
“Data science mimics the kinds of intelligent processes that all living things have: they receive information through the senses, recognize useful patterns, and act appropriately,” Arnold said. “In our attempts to mimic this, we can marvel at the complexity of the creatures that God made. We are able to take the raw input in our eyes and ears and construct something that’s a reasonably faithful representation of what the world actually is. As flawed and limited as our perceptions can be, it’s still pretty amazing.”
ONLINE EXTRA
Read Derek Schuurman’s article “Weapons of Math Destruction” at calvin.edu/spark.
WHY CONSIDER A CAREER IN DATA SCIENCE?
In astronomy, the last few decades have seen rapid growth in the amount of data available, and it’s meant that the set of skills that we call “data science” has become central to much of the research in the field. That move toward answering questions with large datasets seems to be happening across research and industry, and is why this skill set will continue to be valuable.
— Jake VanderPlas ’03, software engineer in Silicon Valley and previously an astronomer and data scientist at the University of Washington
Data science is still a new field. There are a lot of exciting opportunities in a variety of domains. It’s allowed me to explore and learn about different things in the world. It’s a great field for people who are intellectually curious.
— Michael Bloem ’04, senior applied scientist at Amazon
A career in data science will expand your worldview. Depending on the role, you’re learning so much more about the world either through digging into one type of data or a variety across different topics. It definitely encourages you to have a wide range of skill sets from mathematics and computer science to communication and a deep understanding of the business domain of focus.
— Beka Agava ’17, quantitative Researcher at BlackRock
HOW THE DATA SCIENCE MAJOR WORKS
DATA SCIENCE
In their first or second year, students take “Data Science for All,” which introduces problem solving and ethical issues. Other courses teach data visualization techniques and standards for encoding data.
COMPUTER SCIENCE
Data scientists write computer programs to analyze data, so students get hands-on training in programming languages, machine learning, and parallel computing techniques.
STATISTICS
On the statistics side, students take two calculus courses, intro to statistics, applied statistics, and other high level math courses.
COGNATE
Because data science is applied, students take 15 hours in another discipline, like biology, business, economics, geography, political science, or public health.
