Written by Shwetha Gowda on 14 November 2022
How should an Entrepreneur think about the Company’s Data? Thus, deliver more relished customer service or meet customer expectations in their product.
As companies start up, their primary focus would be to survive. Hence, with a few customers they can adopt to setting up their internal processes. But as they grow as an organization, more people, orders, gaps, expectations, SOP’s become crictical.
Further to move from ERP/ CRM, users need automations in their systems. RPA’s and bots come in handy here to make sure the transactional automations are done. When we do any of the transactional automation, it is important to capture or infer as much as discrete information that would be possible. The fundamental purpose of this is Research. The data that is sitting with us can give us a lot of ideas, trends, indications, informations on various kinds of Business operations they are involved in.
Considering an example, a simple query on all the customer feedback collected can give useful insights on
a. Average turn around time
b. First response time
c. Escalation / SLA breach ratio
and many more as per our perspective. We need to carefully carve out intelligence from the information that would be available.
The primary reason for which we consider automations / discreation is to identify this kind of critical information. This entire process can be termed as Data Analytics or Data Science.
This often includes,
a. Data Preparation
b. Sample creation
c. Modeling
d. Inference
e. Analytics
Companies can look for IT professionals and firms which can provide this as service and harness the potential of the data. A typical Data Science role provides customers insightful information and the opportunities to dwell deeper and analyse data and mine out. It is important to make sure that our data is as much organized as possible to make sure heading to analyics would be easy.
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