With the development of current data storage and processing technology, it is relatively easy and inexpensive for businesses to start owning a data warehouse or building their own reports/dashboards. But to gain value from that data, one must create a close link between business strategy and technology. This requires an investment in the right tools for each stage of the data lifecycle.
So what are the right tools? And how does one implement them properly to achieve maximum impact?
To answer that question, each company needs to know where they are in the journey of digitization and data platform development. At the same time, this journey needs to follow a methodical route because it will take time to convince the staff to believe in the value of technology and accept the transformation of habits to digitization.
The following 4-stage data maturity model introduced by Dell Technologies and Intel will answer the question: Where to start to become a data-driven business? What stage of the data evolution roadmap is your business? How will the company face the challenges at each stage, and what should be prepared?
What is a data-driven organization?
A data-driven organization is a business that can make decisions based on data rather than instincts, hopes, general observations, or personal opinions. And this applies to every level of the business.
Becoming a data-driven organization is more than simply buying and installing the necessary applications and tools, hiring data experts, and investing in your data infrastructure. It’s about making data and analytics an important part of your overall business strategy, culture, and all business processes.
A data-driven organization typically has the following characteristics:
- Employees at all levels can easily access and make use of data that is germane to their jobs.
- Business leaders see data as an asset and rely on it to make decisions.
- Teams use data to find consensus in meetings and group projects.
Dell Data Maturity Model
The data development model introduced by Dell is probably the most popular data development model today. This model consists of four levels of data development, as shown in the figure.
1. Data Aware
Skip stage 0 – when data aggregation efforts are almost non-existent. At the Data Awareness stage, businesses recognize the value of data and begin manually collecting data from various systems. The enterprise has a lot of tools/software for operation, but it lacks database planning. The data is fragmented, the data quality is inconsistent, and the reports are tailored to the needs but the accuracy is low due to a lack of multidimensional data collation from multiple sources.
If this describes your organization, you’ll need to prioritize the following tasks in order to advance to the next stage:
- Create a data model that reflects the business’s value chain.
- Using tools/software, collect data at each link of the value chain.
- Construct a data pipeline to consolidate data into a single database.
- Create and standardize a management reporting system to extract valuable insights from data.
2. Data Proficient
Data quality has improved, and businesses have standardized data at the production site. Departments in the enterprise have clear and strict rules about what data to access and with what quality requirements. At this stage, businesses also begin to track key performance indicators (KPIs) and experiment with data-driven decision-making. However, most of the data used are still structured data; companies still lack experience in controlling & using unstructured data (image data, voice, etc.)
At this stage, businesses should focus on continuing to improve data quality and increase integration between applications, deploying new technologies to handle unstructured data. Optimize the data warehouse and implement a Master Data Management strategy. The ultimate goal is to establish all standardized reports on a centralized platform. By then, the organization has already begun to use its resources more efficiently.
3. Data Savvy
At this stage, businesses are using data to make important business decisions. The business and IT departments are closely linked with leadership support to eliminate data fragmentation across the organization.
When business departments have a need to use data as a competitive advantage, it will require the development of corresponding information technology systems. The IT system must now respond by implementing new technologies that can integrate all data sources and applications to: (1) efficiently provide and store data; and (2) provide analytical reports that meet the needs of relevant departments.
4. Data Driven
The final stage of this model is Data-driven – all decisions in the organization are based on the database. The goal of this phase is to expand the data strategy while continuing to cut costs. The IT department and the business function as a tight, cohesive unit. The IT system has the ability to integrate all data sources inside and outside the platform, and apply advanced analysis methods. The business has identified where and how to embed analytics in its processes.
The challenge at this stage is to seamlessly embed data analytics into operational workflows; expand the database; and move from descriptive and predictive analytics into prescriptive analytics.
Becoming a data-driven organization allows end users to perform their own data analytics without IT support, on a trusted and supported architecture.
Conclusion
There are many methods and models to transform your business into a data-driven organization. Dell Data Maturity Model is one of the most popular and methodical models. Hope this article can help you map out some great ideas for the path to becoming a data-driven business.