Collaboration and Data competency are key for Data Analytics Success

Data Transformers Podcast
Collaboration and Data competency are key for Data Analytics Success
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Episode Title : Collaboration and Data competency are key for Data Analytics Success

Episode Summary: Data analytics projects, as opposed to ERP or CRM projects, lack clear requirements. As the business owners are ultimately accountable for the outcomes of data analytics projects, they’ll be skeptical and possibly intimidated by the technologies used in analytics such as machine learning etc. The way to address this is with a collaborative platform that has workflows where multiple technology and business stakeholders can participate from the get go. The collaborative workflow based approach can also be used as a training and documentation platform for upskilling/reskilling employees as well as addressing regulatory/compliance requirements. The collaborative transparent workflow approach will also make the entire process more transparent with explainability built in.

Topics discussed in this episode:

02:01 Data analytics requires people in tech and business to work closely much more so than in ERP & CRM etc. Success in Volantsys is measured by how many people are successfully impacted in changing the org.

05:16 Unlike ERP & CRM, requirements in data analytics projects are not clearly laid out. So it’s very important for cross functional folks to work together and speak the same language.

07:00 An example is the cash flow management forecasting system that was built but the business leaders were not comfortable using it because they are not sure about how it was built.

10:00: Started with ‘Data coach’ as a consulting service which was a 2 week workshop using customer’s own data.

11:05: With Covid pandemic, changed the approach to a guided workflow platform to help tech and business folks to collaborate. The basis is the ‘Data Management’ platform and has a chatbot as a ‘data coach’.

13:08 The guided workflow documents the whole process which could be used for compliance, explainability, and help explaining ethical considerations as well. This could also be used for training purposes.

17:08 (Headliner) : Analytics problems by their very nature are driven by a business initiative. Given there are different ways to solve a problem like a more accurate way or a more robust way etc, different functions (finance, risk, legal etc.) have a stake in how the problem needs to be solved.

20:15 (Headliner): Instead of people punching holes in the final results, the approach will be smoother if multiple stakeholders are involved in the workflow process.

22:00: Interestingly data science people embrace the collaborative approach but business folks are still skeptical because they are accountable at the end of day and they are intimidated by the technology and the lack of transparency.

Resources mentioned in this episode:

Volantsys Analytics: https://www.volantsys.com

Gowri Selka LinkedIn: https://www.linkedin.com/in/gowriselka/

Podcast website: https://DataTransformersPodcast.Com

Data Transformers Podcast

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