Join WhereScape at Big Data & AI World—the...
Why Quick Wins are the Bedrock of Data Delivery
Quick win: An immediate improvement that delivers obvious value to the business. Because of the short deadline (two to three months), quick wins tend to be easy to implement but limited in scope. The best quick wins can be built on or repeated at a later date.
In 2009 the Corporate Executive Board surveyed 5,400 leaders who were new in their jobs. The survey asked these leaders what they were focusing on. Cleverly, they also asked the bosses of these leaders to rate their performance so far.
The responses were sorted into two groups: those whose bosses thought they were succeeding, and those whose bosses thought they were struggling. What was the difference?
What the Research Showed
The outcome of this research was written up in the Harvard Business Review. (Van Buren, M E and T Safferstone, 2009), “Among the high-performing new leaders, one attribute stood out,” the authors wrote, “a strong focus on results.”
Item one on every new manager’s to-do list is a quick win. The new leaders who had found themselves a quick win were rated 20% higher by their bosses than those who had not. As the article points out, a quick win reassures your boss that it was the right decision to give you the job, and it also sends a positive message to the people who are working for you (it’s OK to follow you because you know what you’re doing), and the people who work alongside you (you’re going to make a difference).
Great, but I’m in a data team, so what does this mean for me?
Delivering Value
One of the key factors that stands out in the success of any team is the ability to deliver value. This is as true of data teams as with any team. There are lots of things a data team can do – build data warehouses, data feeds, dashboards, reports, design and build data architecture, develop people capabilities, training, stakeholder engagement, analysis … the list goes on. These, however, are doing activities and are only relevant when they combine to deliver value to the business. By value to the business we mean one of five things, things that our CEO, CFO or COO would recognize. This means increasing revenue, reducing costs, reducing risk, increasing customer satisfaction, or increasing employee satisfaction. So when delivering a data capability you need to think about in the same way as your CEO. Talk their language.
Telling them that you have built some important data capability such as a data warehouse, data lake, or data vault will have little meaning. What it does do is beg question “So what?” The ‘So what’ here is very important. Turn this into “We’ve built a dataset that enables us to identify customers who are at risk of churning. We then share these data sets with the operations and sales teams delivering clear insight so they can respond in a timely manner to retain our customers.” This is far more relevant to the CEO, and a great quick win. Really what we mean is a quick ‘business’ win.
This may be one element of your data warehouse but it is by every definition a win for the business. So as you go about designing and building your data warehouse, it becomes a collection of wins. And we all know that a data warehouse has to be more than a collection of quick wins. Many ‘quick wins’ are not the same as a strategy. So whilst your design may need to be strategic, the functionality should be delivered through quick wins. Your CEO will then relate your data warehouse as a source of delivering business value rather than a technology delivery with a significant cost. Which would you prefer?
Quick Wins and Why they Work
So what’s the anatomy of a quick win?
A quick win must be quick, and by this three months or less is ideal. Think small. One thing that you are certain of delivering. Quick fails don’t count! So not the smartest, or shiniest project or someone’s pet project. Think about how you can scale the quick win afterward to more areas. Ensure that you take the learnings from it and share those with the business.
Imagine this scenario: “We reduced churn by 7%, so now we can do the same for the other business areas.” Think about using the quick win to leverage your strategic, but hard-to-sell data initiatives. Try this version of the same message: “We reduced churn by 7%, but had the data quality been better we could have reduced it by 12%. So now we recommend working on data quality in the next phase.” This is a great way to kick start your data quality initiatives. Imagine how you can use a quick win to kick start your data governance, data warehouse or other initiatives that are harder to sell?
So in summary, quick wins deliver value, which in turn drives the success of your teams which may help underpin your strategic data initiatives. Whether you are just starting out, or need to reinvigorate your data activities quick wins and talking about them in a language your CEO will understand are the bedrock of your data delivery.
Simplify Cloud Migrations: Webinar Highlights from Mike Ferguson
Migrating your data warehouse to the cloud might feel like navigating uncharted territory, but it doesn’t have to be. In a recent webinar that we recently hosted, Mike Ferguson, CEO of Intelligent Business Strategies, shared actionable insights drawn from his 40+...
2025 Data Automation Trends: Shaping the Future of Speed, Scalability, and Strategy
As we step into 2025, data automation isn’t just advancing—it’s upending conventions and resetting standards. Leading companies now treat data as a powerful collaborator, fueling key business decisions and strategic foresight. At WhereScape, we’re tuned into the next...
Building Smarter with a Metadata-Driven Approach
Think of building a data management system as constructing a smart city. In this analogy, the data is like the various buildings, roads, and infrastructure that make up the city. Each structure has a specific purpose and function, just as each data point has a...
Your Guide to Online Analytical Processing (OLAP) for Business Intelligence
Streamline your data analysis process with OLAP for better business intelligence. Explore the advantages of Online Analytical Processing (OLAP) now! Do you find it hard to analyze large amounts of data quickly? Online Analytical Processing (OLAP) is designed to answer...
Mastering Data Warehouse Design, Optimization, And Lifecycle
Building a data warehouse can be tough for many businesses. A data warehouse centralizes data from many sources. This article will teach you how to master data warehouse design, optimization, and lifecycle. Start improving your data strategy today. Key Takeaways Use...
Revisiting Gartner’s First Look at Data Warehouse Automation
At WhereScape, we are delighted to revisit Gartner’s influential technical paper, Assessing the Capabilities of Data Warehouse Automation (DWA), published on February 8, 2021, by analyst Ramke Ramakrishnan. This paper marked a significant milestone for the data...
Unveiling WhereScape 3D 9.0.5: Enhanced Flexibility and Compatibility
The latest release of WhereScape 3D is here, and version 9.0.5 brings a host of updates designed to make your data management work faster and smoother. Let’s dive into the new features... Online Documentation for Enhanced Accessibility With the user guide now hosted...
What Makes A Really Great Data Model: Essential Criteria And Best Practices
By 2025, over 75% of data models will integrate AI—transforming the way businesses operate. But here's the catch: only those with robust, well-designed data models will reap the benefits. Is your data model ready for the AI revolution?Understanding what makes a great...
Guide to Data Quality: Ensuring Accuracy and Consistency in Your Organization
Why Data Quality Matters Data is only as useful as it is accurate and complete. No matter how many analysis models and data review routines you put into place, your organization can’t truly make data-driven decisions without accurate, relevant, complete, and...
Common Data Quality Challenges and How to Overcome Them
The Importance of Maintaining Data Quality Improving data quality is a top priority for many forward-thinking organizations, and for good reason. Any company making decisions based on data should also invest time and resources into ensuring high data quality. Data...
Related Content
Simplify Cloud Migrations: Webinar Highlights from Mike Ferguson
Migrating your data warehouse to the cloud might feel like navigating uncharted territory, but it doesn’t have to be. In a recent webinar that we recently hosted, Mike Ferguson, CEO of Intelligent Business Strategies, shared actionable insights drawn from his 40+...
2025 Data Automation Trends: Shaping the Future of Speed, Scalability, and Strategy
As we step into 2025, data automation isn’t just advancing—it’s upending conventions and resetting standards. Leading companies now treat data as a powerful collaborator, fueling key business decisions and strategic foresight. At WhereScape, we’re tuned into the next...
Building Smarter with a Metadata-Driven Approach
Think of building a data management system as constructing a smart city. In this analogy, the data is like the various buildings, roads, and infrastructure that make up the city. Each structure has a specific purpose and function, just as each data point has a...
Your Guide to Online Analytical Processing (OLAP) for Business Intelligence
Streamline your data analysis process with OLAP for better business intelligence. Explore the advantages of Online Analytical Processing (OLAP) now! Do you find it hard to analyze large amounts of data quickly? Online Analytical Processing (OLAP) is designed to answer...