We have more data than ever before – both collected digitally in connection with the primary business process – but also collected in the digital contact points with customers.
Creating value from this data is a discipline that many customers want to optimize. Creating data-driven insights and getting a business value out of data requires several basic discussions and actions to be carried out in your company.
Where is the value creation in data? What data insights give your business value? And how do we ensure the validity of data? These are three questions that you should ask yourself as a digital company.
We support the utilization of data through a series of phases:
- Vision for data – what difference can data make for your business?
- Roadmap – Establishing a sequence of "enabling". We investigate where to find the value most quickly and validate our efforts.
- Rollout / Deployment – We avoid desktop projects and make sure that the data-driven projects become part of our daily lives.
- Definition of initiatives – An assessment of what we can do in the short term to get more value.
The last point is the beginning of an iterative process where we repetitively will examine how initiatives can follow each other to get through the given roadmap – focusing on reaching our vision. This may include a mix of investigative studies (e.g. whether intelligent data analysis/machine learning can impart new knowledge) and concrete implementations of data-insights dashboards and data analytics, for example.
As a fundamental task, we should cover and possibly classify the data sources we hold to ensure that we utilize the relevant data sources where needed. And where the validity of the data is known in relation to the analysis and insights we want. It should safeguard us from making assumptions where data is not actually qualified to be the basis for such.
We work with Data Management on a wide range of platforms. As there are many different initiatives that can be included in this, the tool selection is made with the customer when the work is done.
However, we are experts on the Microsoft and Salesforce platforms – why Power BI, Azure Data Lake, Azure Data Fabric/Logic Apps, SQL Server Analytics, Tableau, Salesforce Einstein and Salesforce Analytics and Reporting are tools commonly used in our projects.