Close

Data management and analytics as a competitive edge – getting started

Digitalization has led to an explosive increase in the amount of data. Different systems and platforms are part of our daily lives for both consumers and businesses. Development of e-commerce, mobile devices, social media, sensor data collected by various devices with cloud technology make huge amounts of activity data are available.

It is a well-known fact that the amount of data does not in itself make anyone blissful. A significant advantage of data is obtained only when it can be utilized in a correct and efficient way.

The cornerstone of data utilization can be considered the applicability of the methods and solutions used for data management, as well as the methods for using analytics in the presentation and distribution of information. A company that incorporates data and analytics in its operations is able to create a major competitive edge by using information that has been transformed into an understandable form. At the same time, this gives rise to real benefits that support business development. The key to success is built on transforming data into information and information evolving into understanding.

 

data-analytics-image-1.png
Source: Underwood

 

Analytics and data management growing in importance

Gartner, a leading ICT research and advisory company, predicts that in the next few years, more than 90% of corporate strategies will define data as a critical enterprise “asset” and analytics as an essential competency.
(source: https://www.gartner.com/en/conferences/emea/data-analytics-germany/featured-topics/data-analytics-strategy).

In practice, this means that the traditional themes used to measure competitiveness will be complemented by an indicator that assesses the capabilities of a company’s or operator’s analytics and how efficiently the information that is gained from the data is used to guide and develop the operations.

Means for achieving real business benefits

With data and analytics solutions, data used to guide operations can be collected from various information sources (systems, equipment sensors, open data, etc.) and directed, in a usable format, into storage and utilization solutions that have been optimized for various purposes. For example, transaction data is typically saved based on a data warehouse (DW) or, for real-time monitoring, stream services are used.

The captured data can be used to support decision-making by bringing analytics to processes and people. Streamlining business processes (sales, purchasing, production, warranty, etc.) using “traditional” business reporting and BI tools is an excellent area for developing analytics – concrete results are often achieved quickly. The digitization and streamlining of optimized customer service, quality control and predictive actions using analytics are proven means of enhancing the use of resources, improving the end customer’s service experience and reducing time loss or costs.

Effective insight-driven management and data analytics management enable the innovation, development and continuous improvement of new revenue and service models. Automated – i.e. machine-learning and AI-utilizing – analytics processes make it possible to identify and create new business models, for instance, around self-service, life-cycle management and remote functions. For example, the rethinking and digitization of order/delivery chain management, maintenance and spare parts services and various customized, end-user-based services becomes considerably more effective with a well-thought-out analytics solution.

How to get started or accelerate the pace of development

Development demands investments in the form of time and capital. In terms of developing analytics, a practical approach is to start with a chosen case or scope that is relevant in terms of operations but also agile enough to implement. Development work always involves major expectations of concrete results. By drawing the line right from the start, you enable the achievement of visible results and build credibility towards your organization and trust in the usefulness of the development.

The architecture, tools and development process should be coordinated with other operations from the outset. For example, a pre-study will help you easily gain an understanding of the big picture. Technology, processes and people are at the core of developing insight-driven management – it is important that this be taken into account right from the start and that building the process starts with the best overall operating model, one that can, above all, be duplicated or scaled as the development advances, and the business needs grow and become clearer.

Technologies and solutions enable data to be utilized in the form of information. The final breakthrough takes place, for example, with the creation of a competitive edge, as the organization is able to add its own understanding on top of the information. Communications, change management, training – identifying data’s possibilities and limits and integrating analytics as a part of the processes demands change management and strategic planning.

data-analytics-image-2.png
Photo: Integrating data management and analytics as part of strategic and day-to-day operations, taking into account and optimizing the business benefits.
(Source: Bastone)

 

If you would like to hear more and are interested in discussing the development of Insight-Driven Management in your organization, we would be happy to tell you how Etteplan can help you. Contact us!

Ask Tero Syrjä a question or challenge us

When you submit this form, our specialist will be in touch with you by email or telephone. By submitting the form you accept our Privacy Policy.

More stories you might like