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The systematik data maturity framework helps organizations better understand where they are in their data journey and where they want to be in the future. The guide below shows what your results mean and how our experience can improve and increase your data capability.
Organizations in the explorer stage of maturity are in the first steps to becoming a data-driven business. They have moved on from the foundation level, and parts of the data strategy are coming together.
Companies at this level of data maturity typically have data they can trust, but any additional information is either incredibly difficult to find or is not considered at all. There may still only be one person responsible for data and no analyst to help turn it from information into actionable insight.
“The goal is to turn data into information, and information into insight.”
– Carly Fiorina, former executive, president, and chair of Hewlett-Packard Co.
Leadership teams do not have universal confidence in the data as collection processes are primarily manual. There is no clear UTM strategy to allow a deep dive. The building of reports and dashboards is siloed to a single person or team. Each of those factors places barriers in the way of the organization becoming data-driven. A data culture requires everyone to embrace using data with access to what they need so that new projects utilize data at their core.
A lack of big data enterprise tools causes data to be spread across several platforms, making it challenging to produce valuable insights. As a result, many decisions are based on instinct rather than data, where decision-makers do not value the information they see and cannot act upon it. A “gut feel” approach can easily lead to problems with limited facts to back up the decision.
“It is a capital mistake to theorize before one has data.”
– Sherlock Holmes
Although data collection processes exist at this stage of the maturity journey, they are not well-documented. Explorer stage organizations do not have resilient GDPR or PII compliance procedures, putting themselves at risk of fines. Unless actions are taken to improve data privacy and governance, the risk level increases year on year.
While the organization trusts the basic data it has access to, it cannot be leveraged to identify business opportunities and create a competitive advantage. The available data is mostly retrospective and not predictive enough to help inform business decisions, which is why decision-makers rely on their instinct over insight.
The Systematik team of experts can offer a 100% free no-obligation thirty-minute strategy session call to start guiding you along your data maturity journey. Contact the team today to see how we can help get your organization from where it is today to where you want it to be in the future and turn your data into a more valuable business asset.
We are not marketers who dabbles into data analytics. Data is all we do.
We build and advise on end-to-end data solutions. Our team comprises measurement specialists, data analysts, data engineers, data architects, and data scientists.
As with anything in life, you get what you pay for. Sure, you could hire a freelancer, an agency from a third-world country, or a marketing generalist who dabbles in a bit of everything. In fact, most of our clients tried one of these solution before contacting us.
Here’s why we think you should save yourself the hassle and hire us directly.
Yes, we will work as extended part of your team. You can let us know about your processes and we will just white-label the service package for you.
Yes, this is exactly the type of work we specialize in. We’ve built over 25 modern data pipelines. Consolidating data from more than 100+ data sources.
Think of it like this: all-in-one solutions in data are a bit like those Swiss Army knives. They promise to do everything – cut, screw, open bottles. Sounds great, right? But when you actually need to do a serious job, like screwing in a tight screw or cutting a tough material, that tiny knife or screwdriver just doesn’t cut it. You need specialized tools.
Now, apply that to data solutions. If an all-in-one is super flexible, it’s like a Swiss Army knife with a hundred tools. It can do a lot, but it’s so complex that you need a specialist just to find the right tool. And specialists aren’t easy to come by.
If it’s too simple, it’s like having a Swiss Army knife with just a couple of tools. It works fine at first, but as your needs grow – say you need to manage more data or your analyses get more complex – that simplicity becomes a limitation. You’re stuck trying to do a professional job with a basic tool.
And what if the all-in-one doesn’t have the exact tool you need? You end up having to get additional tools anyway and find a way to make them work with your Swiss Army knife.
Plus, these all-in-ones are often like fancy gadgets where you can’t see how they work inside. If something breaks or doesn’t work as expected, good luck figuring out why without a detailed manual or an expert.
And to top it off, they’re like high-end gadgets that cost a pretty penny, especially as you start using them more and more.
In a nutshell, that’s why many companies prefer building custom data pipelines. It’s like having a tool belt with exactly the tools you need, chosen by you. Sure, it takes time to assemble and you need a range of tools, but in the long run, it’s more efficient, scalable, and tailored to your specific needs.
