Analytics Fireside Chat

Analytics Fireside Chat: Nandu Patil, CVS Health

Nandu Patil, Analytics Lead at CVS Health, shares how to build measurement frameworks to derive intelligence which aids business strategies.

Diana Daia
May 29 · 4 min read

Join Nandu Patil, Analytics Lead at CVS Health, and Diana Daia in this talk about data strategy and anchoring it in the business strategy.

You’re an experienced Data Strategist who cultivates integrated intelligence to support the enterprise communications team at CVS Health.

What are the lessons you've learned in this role, and what tactics help you drive this strategy successfully?

In my role, I help our teams build, measure and optimize the campaigns by using multi-modal research approaches, novel datasets, and triangulating across data sources and methodologies.

What I have learned is that not everything that needs to be measured can be quantified, and not everything that can be quantified needs to be measured. Knowing the difference between what you can potentially measure and what you should measure is, in itself, one of the greatest drivers of success. 

Not everything that needs to be measured can be quantified, and not everything that can be quantified needs to be measured.

Focusing on data quality rather than volume is indeed important. If we take marketing campaigns, for example, why and how does data play a pivotal role even before campaign execution?

Looking at data before executing a campaign helps you a lot. At CVS Health, we start with gleaning the insights from media conversations and audience profiling. Getting to know our audiences before we launch a campaign helps our teams finetune messaging and targeting.

Whatever initiative or campaign, you need to have the clear objectives in place beforehand in order to have a measurement plan. In that way, it becomes lot easier to reach goals, not vanity metrics, but the success that matters.

Which is your favorite metric?

Share of attention – Focusing on curated audience segments

To support our strategy, I like to use a combination of metrics that essentially joins 'share of voice' with 'impressions'. 'Share of voice' is good, but it was not enough to help us get the laser-focused analysis that we need. With 'share of attention', we are able to take a closer look at mentions while cutting through the noise and narrowing down the audience. Gleaning the insights from to specific audiences with the help of analytics helps our communications team gain better results.

Working closely with social listening must involve sentiment analysis, as well. How do you maximize its use?

Yes, although challenging and sometimes even misleading, sentiment analysis can indeed be meaningful. Let's take the example of the recent global pandemic. 'COVID-19' is an issue that can drive negative sentiments. However, there are a lot of positive and more nuanced discussions that are harder to be captured solely through sentiment analysis.

This is why I prefer to use weekly rolling averages and identify fluctuation patterns, rather than actual sentiments.

The Communications world leans heavily on qualitative metrics, it is difficult to identify and quantify attributors.

Contextualizing your work is vital. It enables you to identify areas of improvement and anchor your work in the overall business strategy.

Exactly. Working in Communications, I have experienced that it is challenging to quantify efforts and success measures because the majority of metrics we care about are qualitative, not quantitative.

Anchoring is the first part. The second part is the application of analytics and insights.

What accomplishments are you most proud of as a data strategist?

At CVS Health, being an integral part of the development of strategic initiatives by providing the measurement framework to inform our enterprise communications teams is the most rewarding feeling. The measurement framework focuses on two things I care about:

  1. performance: the performance of our team to improve company reputation through scorecards and intelligence brief
  2. perception: what we hear about our brand from general media, social media, surveys.

This is an incremental and iterative process and builds upon itself.

Combining performance and perception is really powerful because it essentially helps us know if we are moving in the right direction.

What is the biggest ‘bottleneck’ to your analytics operations?

Business teams need to strategize and set their objectives by taking metrics and KPIs into consideration at the onset of campaign building.

The quality and potential of data, once recognized and tied to the overall business strategy, helps analytics teams make recommendations and lay down the path to measure and optimize efforts.

It's impossible to accurately assess and optimize the performance if you solely look at the business application of analytics without evaluating the system currently in place for utilizing and implementing those insights.

What are the tough truths that we don't talk a lot about in the analytics world?

The success of analytics teams and their projects does not solely depend on the number of reports built or volume of insights generated.

For an analytics team to be successful, it requires a process and ecosystem which fosters insights development. Fortunately, we have that at CVS Health and it has allowed us to derive data-informed strategies.

Setting up measurable and data-supported objectives.

It's impossible to accurately assess performance if you solely look at the business application of analytics without evaluating the system currently in place for utilizing and implementing those insights.

Analyzing data and extracting insights is only half the job; being able to associate it with the business success driver is the other.

You love keeping up to date with the latest in analytics. Where do you get your inspiration? What events do you find interesting?

LinkedIn is a valuable source. Fellow analysts write a lot about different topics, problems, and solutions that they are facing.

I also enjoy following blogs, as well as reading relevant whitepapers and case studies from people in the industry. PR week, Cision, and W20 are some of my go-to sources.

What advice would you give fellow analysts working in healthcare to succeed with a cross-functional approach to analytics?

They should learn more than just the technology. Think about the different ways of deriving solutions and applications of data techniques. Analyzing data and extracting insights is only half the job; being able to associate it with the business success driver is the other.

Don’t just learn how to use the tools, look at what problem your company or industry solving. Building a good model or having campaigns that work fine are not enough if you don't solve the core challenge or reach the right audiences

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