In the final installment of our Data Value Chain (DVC) series, we’re diving into a critical question that well-established companies often overlook: what should I do if my business is already data mature?
Many large enterprises—like major retailers, manufacturers, or QSRs—find themselves in this exact spot. Successful data maturity is something to celebrate, but you can’t stop there. Nagging problems and the ever-increasing rate of change and disruption will eventually cause bigger issues. Or your competition may leap past while you wait.
So, to close out this DVC series, we are sharing what it looks like to break through the data maturity plateau and answer the question, what’s next?
Evolving from Mature to Strategic
As Amplifi’s DVC Infographic shows, data maturity is a journey – one that resembles a trek to the highest point of data excellence. Along the way, you’ll reach a Mature Stage. Here’s how we describe this state:
“No longer siloed, your data is now centralized and managed efficiently, likely due to an investment in an enterprise-wide master data management (MDM) platform. Historical data can be mined to drive short- to mid-term objectives: like analyzing sales data to optimize next year’s product or service portfolio.”
Reaching maturity is commendable, but it’s not a stopping point. If you linger too long, you’ll lose momentum, and several issues will eventually emerge. In our experience, we see:
- Companies at this stage often have great background systems in place, but they aren’t cultivating them to keep pace.
- Over time, certain processes or capabilities stop working as they should. Unfortunately, “learning to deal with it” isn’t a long-term solution — and avoidance can put your company at risk.
- The foundation is there to move into a strategic state, but a lack of vision and strategy holds you back.
But what if you do keep progressing? In this case, you’ll overcome many of these issues and reach a Strategic Stage.
In the Strategic Stage, your data is finally an asset used to achieve your long-term vision and goals. Tactical decisions are automated by utilizing emerging technology like machine learning (ML) and AI. This automation frees your human capital to upskill and focus on the strategic decisions that continually drive the business forward.
The Strategic Stage in Action
As we’ve shared, a data value chain is the process through which raw data is transformed into business value. A DVC follows five steps: raw data, information, insight, action, and value.
(We dive into the DVC in the first article and second article of our series)
To illustrate how it works, let’s walk through two real-world examples.
- Transforming Manufacturing Quality
Manufacturers gather large volumes of raw data about machine performance and maintenance costs. But with a bit of organization, this data can provide information about the best and worst-performing machines.
By analyzing this information, you gain insight into which machines produce the most defects. Then, you take action to optimize your production line and achieve higher and more consistent product quality.
Now, this all happens in the middle stages of data maturity. In this stage, you also start using predictive analytics to understand future machine performance. Leveraging these insights, you can proactively schedule maintenance to prevent major downtime.
But you’re not done. As you move into the Strategic Stage, you begin to automate the entire manufacturing production schedule. You leverage ML and robotics to pull in more contextual data, updating the schedule to maximize revenue and cut maintenance/QA costs. Your production planners are now free to think long-term and make strategic decisions.
- Boosting Your Marketing Impact
Now let’s look further down the product lifecycle at the demand/marketing side. As you sell, you gain extensive raw data about consumer buying and browsing patterns. You organize this data into information about regional marketing effectiveness.
In the early stages of data maturity, this information can drive insights into which campaigns should be leveraged globally. By taking action to expand these campaigns, you achieve a 3% increase in online conversions (a significant value in terms of revenue).
As you advance from Mature to Strategic, you continue to see compounding value. Now, less human capital is required to make tactical marketing decisions, as ML and robotics automatically extract the most relevant data to drive the right actions. You free your talent to focus on outliers and making long-term, strategic decisions.
What Kind of Results Can You Expect?
At Amplifi, we want everyone to harness the power of their data. We know implementing data value chains can help you get there – and when you do, the sky is the limit.
So, what kind of results can you see? Here are a few ways people apply their DVCs to drive value at every stage of maturity.
- Data Availability (Early/Mature Stages)
Business units (and users) no longer need to chase down the data they desperately need. Readily available data drives speed-to-market and efficiency.
- Information Accuracy (Early/Mature Stages)
You can boost satisfaction with your brand, products, and organization by providing consistent and accurate information everywhere it’s accessible.
- Exploratory Analytics (Mature Stage)
Like our previous examples, you can use data to drive better decisions across your operations—leading to higher revenue and lower costs.
- Algorithmic Business (Mature/Strategic)
Now, the cool factor comes into play. Companies can build “digital twins” (e.g., for factories or shipping routes) using data and data models. The goal is to test out data-driven decisions in a virtual setting. Pharmaceutical companies, for example, are testing operations and assuring compliance standards are met virtually before making operational changes. Enterprises often use this strategy to mitigate risks and slash QA costs.
- Machine Learning/Automation (Strategic)
Here’s where you really get into the Strategic Stage. Your data is readily available, your systems are integrated, and data flows automatically through your ecosystem. You start to utilize ML to drive better insights automatically. Formerly tedious, tactical decisions are made using robotics. Imagine having happy, skilled employees focused entirely on value-add activities. This is the future, and you can get there.
- New Revenue Streams (Strategic Stage)
Once you’ve freed your human capital to focus on strategic decisions, you may find that you have the data and knowledge sets to build entirely new revenue streams for your organization.
Netflix is a perfect example. Using data from their DVD rentals, they recognized an opportunity for a streaming platform that disrupted the entertainment industry. Now, from even more precise data sets about customer viewing patterns, they are cultivating a powerhouse production company.
Data-excellent enterprises use information, insights, action, and value to lead categories and leapfrog the competition.
Amplifi Can Help
With expertise across Strategy, Delivery, and Operations — Amplifi is here to help.
Whether you need help developing a data management roadmap and strategy, help implementing a new MDM project, or support cultivating a solution you already have in place, we have you covered.
Reach out now, and let’s talk about how we can help move you along the path to the Strategic Stage.