Growing Up with Data Maturity

All businesses store and utilize data to some extent, to provide services to their customers. Companies are achieving different levels of insight with this information, depending on the quality of the data stored and the ability of their personnel to spot patterns.

What is Data Maturity?

In simple terms, Data Maturity alludes to how fully and efficiently a company utilizes the data they store. The company may have databases full of contact details and addresses, but if they only use a small selection of those data points on a daily basis, their data practices would be considered immature. Of course, there are differing levels of data maturity, so businesses will generally fall somewhere on the data maturity scale depending on their practices.

Backing up the benefits of data analytics, a study was conducted by Nucleus Research in 2014, revealing that every $1 spent on developing your business intelligence systems can net a return of up to $13.

At Trianz, we’ve helped countless businesses with our Data Maturity consulting services, to put their data to better use.

What will Data Maturity assessment benefit?

A comprehensive assessment of your business data maturity level can be incredibly useful for measuring transformative progress. Typically, a company will fit into multiple stages of transformation when measured against the data maturity model.

If you are unsure where you sit on this scale, consider running a Data Maturity Assessment conducted by a seasoned managed services partner.

The First Stage

For those with undeveloped data analytics procedures in place, reporting will be limited to critical systems and services you offer. Companies at this stage won’t have any meaningful business analytics software in use, relying on manual number crunching to uncover trends.

Individual teams will have proprietary methods of reporting. Many working hours will be spent compiling reports and sending information between teams, on topics such as:

  • Marketing – detailing which marketing channels are performing best.
  • Human Resources – including work attendance, employee performance reports, etc.
  • Finance – manual inputting, exporting, and sending of revenue and profit data.

As you can imagine, there are many bottlenecks with this stage of data maturity. Information requests need to be compiled and sent, with delays as the sender waits for the recipient to reply with the information they need. Employees will also have multiple logins for multiple systems, with passwords being forgotten as IT teams are overwhelmed by internal support tickets.

If you are at this stage, we strongly recommend working with a Data Maturity Assessment service provider to identify and work through bottlenecks in your IT strategies.

Stage Two

With stage two, a company will be in the process of implementing and wrapping their heads around business intelligence systems. At this point, there may be a few company wide standards, but most departments will still have niche software packages in use.

Within teams, the collaboration will increase at this stage, but there will still be friction with other departments due to a lack of standardization. Intradepartmental analytics will be taking place, discovering insights within their workflows.

Some problems that may arise here include:

  • A lack of data consistency caused by differing processes within the business.
  • The way data is formatted means employees still need to compile reports manually.

In summary, this stage will be plagued with inefficiencies due to interdepartmental friction from a lack of standardization.

Stage Three

In this stage, a business will be heavily invested in developing its analytics system. Workloads may increase as the need for data collation grows. Patterns and trends will be discovered, and these insights will be used to influence the planned trajectory of the business over the coming years. As a whole, the company will become more proactive than reactive when making business-critical decisions, thanks to these BI developments.

IT teams will be tasked with maintaining large datasets, ensuring proper safeguards are in place to conform with new corporate data policies. These IT staff will also need to proactively encourage others to follow new guidelines to maintain IT literacy across the workforce.

The biggest problems here will be:

  • Large influxes of data from various sources. These will need administrating.
  • A lack of specialization across the workforce, which will need to be nurtured.

The business will be benefitting from these new implementations, and efficiency will increase at this stage as policies adapt to the latest information. Training and development will be needed across all departments, to fully tap the potential of these new systems.

Stage Four

At stage four, the business will become increasingly self-aware. Past, present, and future data will be used across all departments to make better decisions.

There’ll be an increased understanding of the effect that different variables have on the results. Proactive responses to problems will be commonplace, with departments working in unison to optimize aspects of the business. Everything from market trends to employee performance will be easily understood, with software accurately predicting changes that may occur in the future. This will allow for the business to mitigate the adverse effects of change, far in advance of when it happens.

Problems at Stage 4 will include:

  • Insightful yet complex analytics and reporting software, which employees will need training on to fully utilize.
  • Massive amounts of data, which will need to be stored and organized properly to sustain the positive effects of your business analytics platform.

At this point, data collaboration will be commonplace. A centralized system will exist that works across departments, offering powerful and insightful reporting functionality. Staff lacking technical computing knowledge will quickly become overwhelmed here, making training and staff development vital to your growth.

The Final Stage of Data Maturity

At this stage, data analytics will be at the heart of every action you make. Every choice and decision will be vetted against automated reports and graphs to ensure maximum return on investment.

For the most advanced companies, machine learning and AI will proactively detect and inform departments of new trends and changes, allowing issues to be resolved before they have manifested.

The only goal here will be to maintain knowledge and expertise across your workforce, adopting new technologies when they arise.

Get your Data Maturity assessed!

Trianz has decades of experience working with businesses, helping them to streamline their internal processes.

Regardless of where you are on the Data Maturity scale, working with a Data Maturity assessment service provider to assess your business structure can greatly improve efficiency. Stop relying on spreadsheets, and start working towards establishing new BI tools. We can help you plan every step of the way in your journey to full Data Maturity.

Get in touch with us using the form below to leverage the value of your data today.

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