Podcasts 4 minute read
The second episode of Chai Talk Online examined how data experts spot the story in the numbers. There is often a gap between the data warriors and those who use the data to craft communication campaigns. How do these get bridged?
Pei Ying Chua, Lead Economist/Data Scientist - APAC, LinkedIn said, "In terms of communicating data, or communicating research findings, that that you might have read, the most important thing really is to make sure whoever you're talking to has the necessary information to understand the context in which you are describing the data."
Pin Ying Chua added, "One of those things that we that we struggle with, sometimes when we're communicating, because we've spent, we do spend a lot of effort, dissecting and distilling huge amounts of information into very concise, very concrete points so that we can get that across to to whoever we are talking to. But then because we've done so much to distil it, to simplify it, then sometimes I think the other party sometimes feels like it's not enough. There hasn't been enough information, then. And that's where some of some of the challenges come in trying to explain the process, and how how it is.
Aseem Sood, CEO, Impact Research and Measurement Pvt. Ltd. and board member AMEC, described his role as one, "Where we step in and help clients identify the right metrics that they should be using to measure their campaigns.
These metrics are very important because they also form a part of the language that you use to talk to the leaders in the organisation. So are you using the output metrics? Are you using the outcome metrics? Are you using the business metrics, the choice of metrics becomes very, very important.
And this is what we do when we step into an engagement with a client and help them identify those right metrics, again, on the basis of the objectives that they've set for themselves and the context that they're working in."
Concurring with the views of the co-panelists, Hin Yan Wong, SVP, Strategic Planning and Intelligence, Weber Shandwick stated, "At the outset, asking the questions around objectives, context, and also be able to understand where they are coming from, and that really help us build that communication bridge, because otherwise, they will be one party speaking numbers, the other party is speaking words, and they're actually not talking to each other. So I think having that level of understanding that mutual understanding is important."
Does real time data help or hinder communication?
The discussion also covered the all important of issue of what data matters and what does not.
Interestingly Sood pointed out that real-time data is not always useful, saying, "Real time dashboards are only useful in specific situations. It's only useful when you're managing a crisis. It's only useful when you're managing execution of a campaign on a day to day basis.
But when real time dashboards are shown to leadership, people who are working on strategic problems, then these tend to be harmful because people tend to take decisions which should not be taken looking at short duration data point. So suddenly, I step into the office and see oh, there is a 3% Fall in the volume of conversations that we have on Twitter suddenly, and as a leader, we I start thinking, Oh, something needs to be done to correct it.
Sood added, "Whereas that's not how public relations campaigns are run, because you're looking at changing outcomes over a period of time. Therefore, you need to increase the time-frame, and then look at the analysis."
Hin Yan Wong concurred saying, "I think absolutely in the case of crisis you need real time turn around so that we know if anything actually appears. Of course, a lot of times we hope nothing happens. But having that real time data and knowing that the conversation has not evolved in a very negative way, definitely will help us make our plan and make our counsel to our clients more effective."
To watch the entire podcast drop in here:
The episode also covered:
1) How not to drown in data.
2) The usefulness test in data.
3) Automating storytelling inputs.