Recently, we kicked off a series on data management maturity with some “good news, bad news” on how companies are faring.
The article also highlighted a crucial component of maturity: the data value chain (DVC).
(Missed the first article? It’s a quick read – check it out here.)
To continue the series, let’s dive into the anatomy of a DVC, ways to assess your readiness, and tips for speeding up the process.
Anatomy of a Data Value Chain
As we mentioned in the first blog, a DVC is the process through which raw data is transformed into tangible business value. The value chain has several checkpoints along the way. Let’s break it down.
- Raw data: It all starts with raw data. Spreadsheets and databases are full of data points like numbers and text strings. But looking at this data provides no immediate understanding of what it means.
- Information: Now, data is organized, understandable, and accessible—often with the help of a master data management (MDM) or product information management (PIM) This information can provide basic inputs on effectiveness, efficiency, and overall performance.
- Insight: Once data has been organized into digestible information, your data scientists can analyze and extract actionable insights, i.e., conclusions from which operational decisions can be made.
- Action: The DVC hinges on this step. Without action, your data may still hold value—but that value is never realized. In our previous money example, a youngster with money sitting in a piggy bank doesn’t build wealth. The money actually loses value due to inflation. Similarly, your data becomes less valuable the longer it sits unused. So, once you’ve stored, organized, and analyzed your data: you must take action.
- Value: Once you’ve taken action, you can derive real business value. It may be immediately tangible—like increased revenue or decreased costs. Or it could be less tangible—like a boost in employee satisfaction, which then helps you attract the most talented employees.
(Prefer a visual? Check out our Data Value Chain Infographic for a graphical view of the process.)
How to Determine Your Level of Data Maturity
Determining your level of data maturity is complex. But there are questions you can use to assess your readiness, including:
- How long does it take you to find the data you need?
- Do you know where to go when you need data?
- Have you invested in a central MDM or PIM?
- Who are your top data experts?
- Are you using your data strategically?
- Do your business leaders “speak” data? Or is there a knowledge gap?
- Do any DVCs exist in your organization today? If so, which DVC is most valuable?
- What outcomes could you achieve if you enabled the correct DVC?
Your answers to the questions above should help you determine whether you are in the Early, Mature, or Strategic stages of maturity.
Not sure what the stages entail? Go back to the first article for a quick summary.
How to Accelerate the DVC Process
We’ve talked about the importance of “flipping the script” to drive more data value chains in your organization. There are several ways you can do this, but we’ll highlight two here.
Flip your thinking to focus on outcomes first.
In a conventional model, businesses look at data first and then try to figure out how to use it. But this approach is flawed. For one thing, data is perishable. The more time it takes to sort through your data, the less valuable it becomes. It’s also more challenging to get executive buy-in, because the gap between data and value is too wide.
At Amplifi, we have a different way of thinking. We help businesses start with their desired outcome, then work back to the data required to achieve it. We detail this process in our DVC Infographic. By using an outcomes-first approach, you can gain clarity, speed, and easier executive buy-in.
Focus on incremental improvement.
According to a study by BCG, many companies set ambitious targets related to data maturity, often as high as 30% growth. Unfortunately, overly ambitious targets are a hallmark of less mature companies.
The top-performing companies set more realistic targets of about 15% growth in data capabilities. According to the article, “Focusing on setting achievable targets is key to closing the gap between data champions and laggards.”
At Amplifi, this approach is core to our Delivery expertise and services. Our proven delivery methodologies help our clients experience quick wins while laying a foundation for long-term success.
What If You’re Already Data Mature?
So, what if you’re reading this and thinking, I’m already data mature. What’s next?
Many large enterprises, like major retailers or QSRs, find themselves in this exact spot. Solid data maturity is something to celebrate. But you can’t stop there. Nagging problems will eventually cause bigger issues. Or your competition may leap past while you wait.
In the final blog of this series, we’ll tackle this topic, including real-world examples of what you could accomplish in the Strategic stage.