Data and analytics transformation

A transformation addresses all the elements that allow an organization to run on data. It can be an overall transformation or isolated to a specific business area.

Find out more from one of our industry experts … - Asif

About Asif:

Data science and analytics professional, focused on integrating analytics and intelligence to support strategic and operational decisions. Extensive international sales and account management experience with leadership capability, formulating unit plans and strategies, and performing in challenging, high uncertainty environments

While digitalization and connectivity have provided companies with vast amounts of data, for many this has been an underutilized resource. Data and Analytics transformation, what we would characterize as an effort to make the organization “data-driven”, is an effort to make the organization better at utilizing this resource.

Why are companies hesitant to adopt a digital transformation?

Enterprise transformations are, however, large, complex endeavors, usually driven from the top, changing large parts of the organization in fundamental ways. Doing new things is inherently risky and doing them coherently across the organization riskier still. It requires clarity of purpose, persistence, and flexibility, because the path to success needs to be created along the way.

What challenges do most companies face when it comes to developing the right digital transformation?

Clarity of purpose is prerequisite to embarking on one of these programs. It is somewhat surprising how often analytics transformations are IT led initiatives, focusing on the platforms and technology, without a clear understanding of what business capabilities will be created, and how these will lead to value. In our engagements, we typically spend time identifying the specific business ambitions, establishing why analytics is critical to the strategic priorities or the company.

How do you assess an organization’s ability to implement such a transformation?

Once we have a well-defined purpose, we try to envision what success would look like. What would be different after the transformation? What are the possibilities? What would have changed, and how? This is another crucial, and often neglected, step. Since the whole organization will be affected, this provides a mechanism for alignment across the different parts.

Once you have defined the goals of the digital transformation, how do you outline a long-term strategy?

With these components we can begin to outline the specific opportunities, capabilities required across the company, and within functions and processes. This leads to a blueprint addressing the range of structures, such as stakeholders, data, technology & platforms, organization, competence, governance and so on, that are necessary to have in place. Of course, not everything needs to be done at the same time. Things need to be prioritized and executed in some kind of logical sequence, but the blueprint provides the basis on which an implementation can be anchored. One can start with one high priority area, Sales for example, and focus on building a particular functionality, such as self-service analytics, BI reporting or forecasting and build the necessary infrastructure to deliver that. The components created can then be used as building blocks to scale out to other areas and functions.
This is an approach that can be applied whether we are looking at the company as a whole or focusing on specific areas. Just be prepared to fail, learn and improve. Continuously.

Our Services

We offer a broad range of services designed to help you wherever you are on your data journey, from building BI and analytics teams to modernizing architecture by replacing legacy environments with more versatile cloud-based platforms, developing new advanced analytics solutions or improving the performance of old algorithms that haven’t kept pace with your developing business.

Data and analytics transformation

A transformation addresses all the elements that allow an organization to run on data. It can be an overall transformation or isolated to a specific business area.

Advance to self-service visualization

Close the gap between reactive and proactive analysis. Take small steps and gain new valuable insights impact by moving from spreadsheet reporting to active Business Intelligence

Architectural modernization

We deliver capabilities by managing and storing data in flexible cost effective environments and move away from silos. We modernize businesses technology for data and analytics, often by moving legacy environments to cloud based platforms or hybrids.

Value driven advanced analytics

Utilization of AI and machine learning to develop self-contained automated solutions, in conjunction with your industry subject matter experts