In the times when data is taking the central stage in the majority of the business operations, the organizations should adopt a clear cut, customized approach to this data transformation. The different types of data should essentially be segregated and made available for use at the right time.
These are data that is vital for various digital transformations – be it an administrative move to become digital, a product development stage with involvement in IoT and robotics, or any other technologies requirements that aids in the progress of the organization. However, not many organizations realize the full potential of data.
The Wakeup Call for Data Transformation
According to a study conducted by Accenture in 2018, it is found that 80% of the respondents are actually sitting on unstructured and inaccessible data. A data transformation is necessary for such organizations as a wakeup call to see the valuable information they have missed all this time.
During any of such data transformations, organizations tend to invest a lot of money and resources to ensure that it is a success. Some may want to migrate their data to better systems, while some may struggle with trying to get their employees to embrace the benefits of data. There can be any number of problems they can face during this data transformation in the form of limitation of resources or budget, the employee skill or acceptance restrictions, the practical implementation issues, or administrative difficulties.
If one needs to ensure the successful transition of the organization to the data-centric approach, then it is vital to take up a structured system to complete this process. There are certain best practices for implementing data systems and procedures to define the data processes. But it is not all stringent. There are rooms for leniency in the way some of these processes are conducted and implemented. This controlled yet flexible approach is what agile offers.
The Agile Data Approach
While agile has been popularly used in the field of information systems wherein they use it as a single project approach, the core principles can be applied for the data transformation too.
If the main goal for the introduction of data transformation in the organization is for product development, then the process of including agile becomes simple, just like any other project. However, when we consider the entire organizational structure to work in the agile system, then there are several considerations to start with.
Let’s say the organization is bringing in the digital transformation in all aspects possible for business success; then there are numerous ways to proceed and various areas that need attention. The applications of data analysis keep increasing at a rapid pace and companies need to keep up the new technologies for data management and analysis. The traditional system, in this setting, could lead to chaos and do not have the flexibility that the data needs.
The agile is the best way to include the data practices with the normal working and still, provide room for improvement or changes in the data transformation as and when the need arises. The organization can provide quick and better services to its customers, reduce the time to market a product and enable better strategies, all of which are made possible with an agile data team. Further, in the agile process, the data is stored in its original format, which also reduces the cost of data maintenance.
The Roadmap to Adopting Data with Agile
At the beginning of the agile approach to data, the organization should make a complete list of the areas where the data transformation is needed. This list should include all possibilities where the data could be a positive influence.
Subsequently, the organization can break down this list based on several priority factors. It could be the immediate need for the business operations, the budget, the new opportunities that give an edge in the market, the availability of resources and the necessary data stuff that the competition is already using. Based on a combination of such specific priorities, the organization can choose the top few areas to start with the agile data transformation.
This detailed approach to the transformation will also provide time for the organization to weigh the pros and cons and start with suitable areas that are of urgent need and could start with a success. Such an agile method of selection of the regions will avoid unnecessary expenditure, wastage of resources, delays and improve the quality of the output.
Further, as we go into the projects itself, the organization should start with mapping the critical characteristics needed for the project. For example, in a plan that works to digitize the marketing with the data-driven approach, the essential characteristics would be the customer responses, customer expectations, company goals, budget and the skills of the employees. Such a robust foundational understanding of every employee involved with the project about where the organization stands at present and the practical ways to complete the project successfully is of monumental importance.
Data for Everyone – The Crux of Business-Driven Data Approach
A common mistake that many companies who are working for long years with data make is the walls that obstruct the sharing of data throughout the organization. As agile is all about transparency and flexibility, it promotes the availability of the same data throughout the entire organization for any employee to leverage.
There is no single ownership of the data or data analysis services; instead, only a common horizontal of data sharing. For organizations that are accustomed to the traditional system of working, enforcing a data transformation can be a huge step. Add to it the agile way of working and sharing of information can be a lot for some employees to handle.
However, soon, many employees have realized the enormous boons the agile system brings in, especially with the data. Though some many face initial resistance, once the companies are successfully past that, the agile data approach will break down the barriers and promote effective inter-departmental coordination that actively reflects on the progress of the organization as a whole.
Inter-Cultural Approach with Agile
Especially when mobile teams are travelling and working from different parts of the world and freelancers working in the same capacity as full-time employees, such an agile data approach is precisely what the organization needs.
This inter-departmental involvement with data can also be helpful at the beginning of the data transformation. Sometimes, there can be a few departments or employees who may pick up slow to new data techniques. With this inter-culture promoted across the organization, they can get the help they need from the other departments and support each other to understand data better and how to use it for their jobs.
The Agile Team for Data Transformation
Most companies focus on getting the right talent who are subject matter experts in the field that they fail to bring in the business coordinators who are equally crucial for the project’s success. In a typical agile team, there are project leaders, developers, experts, integration assistance leads and quality assurance members. With such specific roles assigned to each of the members responsible for essential tasks, the project gets into shape in no time.
There will be fewer discrepancies and mistakes with separate roles of the project and integration leaders. They ensure that the project stays on track, the employees work well with each other within and outside the team and the work done is of the best quality adhering to the regulations.