Digital Action Field 3: Data and the Cloud
Data is raw material. It is only when data is embedded in a context that it becomes a raw material from which information/knowledge, and thus value, is derived. Information may or may not be relevant, depending on the situation. Data is the starting point for developing knowledge and making decisions. ‘Big data’ and ‘smart data’ are core buzzwords of digital transformation, mostly used in the context of cloud technologies. Most organizations are highly aware of the value of collected and analyzed data for their process flows, customer orientation, the development of new products and services, and strategy development.
The data is collected by sensors or from everyday business operations. Data can also be key metrics and measured values in a business context. With technological development, the amount of data available from all business areas of an organization is growing. The challenge is to make sense of this data and use it profitably. Today, it is no longer just about troubleshooting or process optimization. The data itself is a resource – an economic good. The term data economy refers to the fact that it is now possible to commercialize data in independent business models.
At the center is the development of a data management plan (data management framework). Based on an analysis and definition of which data is relevant for the organization, necessary for its success, and important for the future, a data management plan can be developed.
This will include corresponding quality specifications for all data activity within the organization. Among other things, it is important to know where the data is obtained (internally or externally), what the structure of the data is and how the data quality can be guaranteed. The goal should be to collect the right data and store it in the right format and in the right place.
The detailed technical implementation of the data management plan can be fine-tuned in workshops. Additionally, the team should be given the necessary resources (skills, finances, time) so that those involved can collect quality data and classify and store it securely for the future. It is important to build the necessary know-how in the organization to process and analyze the data. The data management plan also provides an overview of what data must be newly or additionally generated or, if necessary, purchased from third-party providers.
A data management plan (see illustration) includes an overview of your data sources, quality levels (data quality at low level should be enhanced), current data usage (potentially, this already provides insights on future applications for operational or strategic use), applied data management systems, and measures taken to improve data security.
A data management plan provides an overview of data in your organization. In many cases, this is also a legal requirement depending on country-specific legislation. (Marc K Peter, https://the-digital-transformation-canvas.com/).
In the next blog post, we will introduce action field number 4, new (digital) strategies and business models, that will define how you are going to capture value from adopting new technologies and leveraging data.
Strategy questions for the digital age
- Do you have a data management plan / framework (which is also in line with GDPR legislation)?
- Do you use existing data strategically and profitably?
- Do you have high-quality data in order to work efficiently and automate processes?