TRAI’s recommendations will increase transparency & accuracy: Pankaj Krishna
There are mixed industry reactions to TRAI’s recommendations on Review of Television Audience Measurement and Rating System in India, with most industry experts that Adgully spoke to considering these as an interference in a ratings system that has been running fairly smoothly.
On the other hand, some called the regulator’s recommendations a very progressive move that will improve the quality and robustness of data and make the BARC management team efficient and independent.
Giving his take on how TRAI’s recommendations will impact BARC India’s functioning, Pankaj Krishna, Founder, Chrome Data Analytics & Media, said, “There is always scope to build upon accuracy in any form of research based on a sample. TRAI’s recommendations will surely increase the transparency in the ratings methodology, data accuracy, sample size and neutrality in the ratings system.”
When asked whether the structural reforms suggested by TRAI would dilute BARC’s autonomy, Krishna was of the opinion that once any input to multiple stakeholders is decentralised, the process of democratising automatically begins. “The structural reforms suggested by TRAI are definitely in the right direction, they will ensure transparency in the system and credible data as opposed to the current structure,” he affirmed.
TRAI, in its recommendations, had called for multiple rating agencies. The Authority is of the view that competition in rating service would bring new and innovative methodology and better data quality, and thus, limiting the state of monopoly. According to Krishna there were various ways in which bringing in competition and multiple agencies for data collection and processing would enhance accuracy of the ratings:
- It will broaden the base of the sample.
- It will further facilitate check and balances in case of any outliers amongst the data collection sources and BARC takes on higher role.
- Enabling and mandating RPD technology in STBs will increase transparency and accuracy in the data collection.
- Archival of collected data will help in query resolutions in case any going forward.
- Review of outlier policy based on time to time market surveys and scientific study will add to data accuracy.
- Annual external audit by an independent agency would ensure neutrality.