Digital transformation has always been closely linked to information. In fact, one of the first steps in the path to digital transition is to control information and remove barriers to business use. But while technology leaders are paying lip service by recognizing them as assets within their organization, they must first understand and support the potential for change in order to get the best information.
At the heart of this promise of change is a solid foundation of information. But not every organization needs to immediately implement advanced analytics capabilities to serve its customers or improve workflows – and many organizations are not ready for this. Instead, organizations that want to prioritize and be truly information-intensive can still make great strides in a more measurable approach.
In this article, I will provide some practical guidelines for organizations that want to open up the power of information to help accelerate their digital transitions.
First things first – why do you do this?
Many organizations fall into the same trap when it comes to data and digital projects. They see these technologies as a way to improve technology, with the misconception that only improved systems and new applications can improve workflows and productivity. While somewhat true, this approach lacks significant strategic focus. They did not ask themselves two key questions: ‘Why do we do this? And what exactly do we hope to change? ‘
Most digital transformation programs deal with offline migration, manual processes to online, digital environments. Because migration requires the digitalisation of information, content, and information throughout the organization, digital transformation projects are primarily data projects. The two are intertwined and inseparable.
Similarly, every organization must build the desired business results from its digital transformation strategy, but many ignore the impact of these change activities on their data. Successful changes work in two ways – digital plans have a significant impact on the expansion and use of information, and the way this information is managed has a direct impact on the success of the planned digital transformation.
That’s why it’s a good place to start launching your data and digital strategies.
But even if you do not have a complete data strategy, you can still break down a set of data and data-based principles to drive a digital transformation map marked with new tools, technologies and talents.
Prioritize data individuals and experiences – and change will follow
The results of your data strategy should be primarily concerned with data consumption. In short, they ask, “Who uses access to better information?”
At the expense of user experience (UX) teams and personal research and individual approach, the key aspect of any data strategy should be to put your users first. And to do that you need to identify data individuals and understand their data experience. For example, utility companies will have teams of field engineers, as well as office-based teams responsible for organizing maintenance calls. Information for both users may be the same, but there are many significant contextual issues that need to be addressed. An underground engineer may be equipped with a tablet device and may be working with gloves or another PPE. This means that formatting, application interfaces, and data visualization must be tailored to the user and the work they want to perform.
I am a big believer in this basic process. Get a clear understanding of who uses information in your organization, how to use it and why, and it will be much easier to build on a better data experience. Even the most accurate impressions, if presented in the wrong format or in the wrong channel, are not easily used.
Information strategy and digital transfer are both costly and adaptable, and relevant, accurate insights can move the business and its users more effectively using the best tools and systems for the job.
Technology can put you on the right track
Today, most businesses operate using multiple sealing systems that serve multiple groups. But when you release systems, it usually means that data is not easily seen or used immediately. To address this challenge, many businesses are trying to integrate all their data into a single centralized system and embark on their journey of digital transformation.
Platforms like Azure provide a single integrated solution and a complete set of organizational and information tools for exploitation. As we move toward this unique structure, we must take into account data management, data quality, security and – most importantly – the knowledge of the database and business environment in these systems. In addition, building data management pipelines that reflect all of this can quickly increase the cost of your digital transformation programs, especially if you do not choose the right stack of technology.
Another reason is the emergence of self-service and low-code / non-code utilities, such as power applications and Betty Blocks. While these can be powerful tools in your digital transformation device, decisions must be made about how these user-built applications live side by side with enterprise applications and the information they generate.
On the other hand, there is a data grid – a decentralized approach that focuses on the concept of leaving information in business domains and systems instead of moving it to central storage. This approach also focuses on information such as production, self-platform and federal governance.
There is no single approach or the right stack of technology. Businesses often use a combination of technology. Whatever your choice, make sure that business objectives and user needs are key factors influencing the adoption of the technologies you choose.
AI is just a word of mouth until your data strategy is correct
We all know that AI is on every organization’s digital transformation checklist. But without a strong data strategy and real investment in information infrastructure, companies will not be able to achieve the information maturity needed to use advanced, AI-enabled analytics capabilities.
To build on this, a good place to start is by experimenting with open source machine learning tools in the early stages of their digital transformation strategy. If high quality information is available to enable advanced analytics, it should be seen immediately — and if not, you can use this understanding to improve your data strategy. But if your models are promising — and it is a business matter to manufacture them — machine learning platforms such as Databrix can provide a specially designed way to ensure compliance and organization.
Regardless of the starting point, businesses need to understand that digital transformation has no real end point. Although the initial results and goals may be achievable, there is always much to be done to enhance digital transformation as your organization’s vast information universe grows. That’s why increasing your data-based strategy and data capabilities should always be the focus of your digital transformation strategy.
Data and Analytics Head Ryan Moore, Aimi