Ep. 248: Connie Siu - The Importance of a Data Driven Culture

Count Me In®

Join host Adam Larson and special guest Connie Siu, President of CDC Synectics Inc and an author, as they unpack the complexities of building a data-driven culture in the business world. Tune in to this episode to discover the essential characteristics and challenges of fostering a data-driven environment within an organization. Adam and Connie provide valuable insights and practical advice on overcoming obstacles, assessing effectiveness, and turning data into informed decisions. Get ready to explore how a data-driven culture can revolutionize your approach to business!

Full Episode Transcript:
< Intro>

Adam: Welcome to another insightful episode of Count Me In. Today, we're delving into the topic of building a data-driven culture with our esteemed guest, Connie Siu, President of CDC Synectics Incorporated, and an accomplished author. Join us, as Connie shares her expertise on essential elements of data-driven culture within an organization, and the significant impact it has on today's business environment.

Stay tuned, as we explore key challenges faced during the transition, and gain valuable insights on assessing the effectiveness of a data-driven culture. This episode promises to offer valuable insights, into the power of data-driven decision-making in shaping organizational cultures and driving business success. Let's get started.

< Music >

Well, Connie, we want to thank you so much for coming back on the Count Me In podcast. And, today, we're going to be talking about data-driven culture and what that means. And, so, maybe, we can start off, you can elaborate what constitutes having a data-driven culture within an organization, and why is it essential, especially, in business today?

Connie: That's a great start, Adam. Data-driven culture is the consistent values and beliefs in distilling insights from data to drive informed decision making, and that's happening across the whole organization. And I would offer three characteristics that you can look for, in an organization, where there's a data-driven culture. The first one is you will see individuals and teams actively asking themselves questions like, "What information we can draw on to support and guide decisions."

You will see consistent efforts devoted to pull relevant data to analyze an issue. And you will see open and frank dialogues on understanding the root cause of a problem by looking closely at KPIs.

In terms of why it is essential for businesses today, there are four factors, two external and two internal, that are important to bear in mind. The first external factor is the competitive marketplace. Companies need focused strategies to target the right markets, to differentiate themselves to compete, and they need the market intelligence to develop focused strategies.

The second external factor is digital transformation. The ability to adopt the right technologies to drive business outcomes is critical. Successful digital transformation involves using technology to capture relevant data and analyze the results. To automate processes, for instance, companies need to know what data is important and what's not.

The internal factors: The first one is operational efficiency. Businesses need to be efficient today, and we are aware that costs are going up, labor, materials. And with the current inflation, companies need to have a good handle on the numbers.

The second internal factor is the need to treat data as a strategic asset. Every business has tons of data. Imagine if you can mine the data for intelligence, they will uncover lots of opportunities to make all kinds of improvements, such as targeting high-margin niche markets. So these four factors require an appreciation of making smart choices from data analytics. It is more important than ever, to build a data-driven culture.

Adam: Yes, I think those are some great factors to take into consideration, especially, if you recognize that your organization doesn't have that data-driven culture. Maybe we can talk about some key challenges that organizations face when they're trying to transition to that. Because it's not something that happens overnight, something that you can turn a switch and say, "Hey, we're a data-driven culture." It's something that builds over time, I'm sure.

Connie: Yes, there are two key challenges I'd like to share. The first one is the lack of technical capabilities. And when I say technical capabilities, they include the skills to identify what data, or KPIs, are relevant to look at. They include skills to analyze the numbers. For instance, how do you know you have achieved efficiency improvement?

What would you look at to monitor process performance?

Do you want to look at the results on a weekly basis or it makes better sense to compare month-over-month changes? And there are many data points you can look at, but not all of them are relevant.

Once you have the data, you need the tools to capture, compile, and analyze them. And many companies are still using legacy systems that are not integrated. So it is a tedious and often very frustrating exercise to extract the data.

And to overcome that lack of technical capabilities, start with training. Training the fundamental skills on asking good questions to identify what data do we need to look at. Training on the skills to analyze an issue. And I would suggest training everyone from the executives to people working on the front line.

We don't need to train everyone to be a data scientist, but we do need them to have the basic skills to ask good questions. To understand what they need to look at, and become good problem solvers. And in terms of the legacy systems, there's only so much you can do patching them. Eventually, you need to invest in modern technologies, and there are so many options out there today, and there's no need, and I want to emphasize this, it's not necessary to invest in the most comprehensive ERP. The key is to find the right applications that meet your business needs.

Now, the second challenge I'd like to talk about is the lack of buy-in. When you don't have the support of the senior management team and the middle managers, it is very difficult to make that shift.

Now, middle managers are accountable for the team's performance. So that fear of poor results is natural because they reflect on their leadership skills, and no one wants to look bad.

When middle managers shy away from results reporting, they tend to do the minimal, just what is needed. Essentially they create an alignment where there's little incentive for the team to embrace analytics.

Now, when we look at the senior management team, when there's no buy-in, from them, on analytics, you tend to see an authoritative management style. Top-down decisions will become directives for the teams to execute. And in this situation, the efforts made on analytics are not valued at all.

To overcome the lack of support, start with understanding what the dynamics is today and find your champion. That champion could ...