Coach Hero is a platform that offers coaching experts to support individuals with their personal and professional growth. The coaches work remotely via digital means to offer 1-on-1 coaching at a lower cost, in their own environment, at their own convenience.
Coach Hero is a start-up spin-off of existing coach enterprises. Their question to the JADS MKB Datalab: how can we merge data sources from different enterprises in a good way? We call this: setting up a data infrastructure.
Coach Hero wanted to set up their data collection so that they could easily understand the effectiveness of their coaching services. On an individual level: how much effect is the coach’s work having on the client’s problem? But also at an aggregated level: how well do all coaches together remedy clients’ problems?
By making this data accessible to both coaches and management, they both gain better insight into results and can then steer for optimization of coaching. To do this, a data infrastructure frame was needed that provided insight into an optimal database structure. In other words, how do we collect the data in such a way that it is suitable for analysis, dashboarding, etc. Also, recommendations were needed on, for example, what queries to ask and what storage to use.
For Coach Hero, the JADS MKB Datalab helped draw out how to properly merge the various data streams from the various existing enterprises. For example, within one company client data may be stored in Excel, and at another company in a CRM system. In this way, we can work towards a solution for bringing together different data streams.
The student made an overview of which data are in both systems, but also which are missing. To make it comprehensible for Coach Hero, this was drawn out and visualized in a diagram showing the relationships between the various data sources. Also included in the documentation is a lot of advice regarding how to collect the necessary information from both coaches and coachees. Finally the outcomes of the student’s conversations and sparring sessions with Coach Hero were submitted. This provided input for a proper design of the data collection. There now is a starting point and roadmap to eventually bring together all data from all systems into a central database.
Your data maturity determines what kind of results you can get from your data. How data mature is your company or department? By knowing where you stand, you can also better estimate what a logical first step is. Can’t get out of here yourself? We are happy to help you discover this.
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The JADS MKB Datalab supports Dutch SMEs that want to make the transition to a more data-driven way of working. The JADS SME Datalab carries out projects with SME entrepreneurs and Data Science students. In addition, we offer various tools to help you define a Data Science project with impact, such as workshops, a Data Maturity Scan and a Data Project Canvas.
So if you want to take up a specifically designed short-term data science project for your SME with a JADS MSc student, visit the SME Datalab Website. 150 SMEs have already participated!