How Business Intelligence helped in better marketing and effective ROIs for Mondelez India
Artificial Intelligence still has a long way to go in India, according to Sachin Pendse, Global Data Modeling, Architect and Reporting Hub lead – Data & Analytics, Mondelez
Published - Sep 4, 2017 8:02 AM Updated: Sep 4, 2017 8:02 AM
Published - Sep 4, 2017 8:02 AM Updated: Sep 4, 2017 8:02 AM
Business Intelligence (BI) is used by various organisations to analyse their raw data. However, with the onset of Artificial Intelligence (AI) in almost every sector today, it is expected to better the BI systems. Sachin Pendse, Global Data Modeling, Architect and Reporting Hub lead – Data & Analytics, Mondelez, is of the view that AI and BI will always go hand in hand. He said that Mondelez is just new to the concept of AI as compared to its rivals like P&G and HUL.
Sachin shared his knowledge about AI and its adoption in Indian businesses along with his insights on how Mondelez is using BI for better marketing and effective ROIs.
How does Mondelez incorporate Business Intelligence (BI) for a better ROI?
In terms of ROI, till 2014 we were looking at it only from a reporting perspective. It was all about analytics to a certain extent. Post 2014 we changed our roadmap and now we are looking at Journey, Strategy and Outcome based ROI.
Our ROIs are now determined on different principles. Firstly, what is the route we are taking to reach the goal? Secondly, what is the goal? How we can quantify that in terms of top line or bottom line? Thirdly, the time period for reaching that ROI. We don’t expect ROI in next 15 days or one month based on type of analytical initiative.
We say that this is the long term and short term ROI. Also, certain strategic initiatives where ROI cannot be determined but it would have indirect benefits like cost avoidance and more.
Business Intelligence is the centre of every discussion at Mondelez today. It is defined as leap frog category which means we will be investing our efforts significantly in this space.
According to Gartner, the chance of a BI initiative not meeting enterprise objectives is a staggering 70 per cent. Would you agree or disagree with this? Why?
I would partially agree to that statement, I don’t know about the percentage. It varies market by market significantly. What is happening is that we always limit Business Intelligence to analytics. Because of this thought process, the needs can never be met.
What we are trying to do now is to change our foundation on a whole, by saying that it is not about analytics but designing the data for the outcome.
When we changed this approach, the thought process changed and that’s where Mondelez has defined analytics or business intelligence as a leapfrog category. Because of this, mind-set change will happen. You are also seeing that data is becoming the central point of discussion everywhere and the next five years are all about data. The thought process will change and it is a matter of time that data insights and data outcome will be at the centre to drive business decisions.
Do you think Artificial Intelligence could then be the future of Business Intelligence?
It is not AI versus BI by any means. AI will be utilised for certain strings in the whole roadmap of BI where AI will take a lead. Let me give you an example, if we take a look at driving the predictive analytics, this is where there will be a limitation as to what business intelligence can do by using historical data. AI needs to come in with macro-economic data, external data, etc. and build that intelligence which business intelligence tools may not be able to do. AI will help in doing exactly this. It is not one tool but a platform and thus it is not about replacing but in fact about complementing each other.
Is Mondelez looking at adopting AI to support and better your BI?
At this moment in near term, we do not have AI actively being pursued. The reason being that if you take a look at the metrics for CPG (Consumer Packaged Goods) businesses in terms of where they stand in analytics journey, we are embarking upon that. We started in 2014-2015 on that journey and achieved good speed in 2016. We are just a couple of years old in that journey as compared to P&G or HUL in India. In that sense we may be slightly behind, so to reach AI discussions may take a while for us to build our foundation and our data market place and that is when AI will come along to increase the value.
How has BI helped in better marketing of products at Mondelez and in turn achieving an effective ROI?
There are many case studies and I’ll share one. Sales and marketing go hand in hand and we all know that. Marketing would always look at the sales team to give them the numbers and then look at the outcome of it. In terms of our spend, there are two or three initiatives that we started. Looking at our revenue numbers by geography, brands, categories and area sales managers, we find out the white spaces. Then this information is shared with the marketing team and then they help us understand why we have those white spaces in terms of categories, brands and competitors. Then we get the information to bridge the gap and increase the coverage.
In terms of spends we have so many channels we use for our advertising or marketing spends and we ask how does it goes on? How is the ROI happening? That kind of an analysis is done using Business Intelligence again. That has given us a clear view as to where to invest more or where to optimise.
Do you think the Indian businesses are ready for the adoption of AI?
My personal view, if you particularly look at the Indian market, especially if you are asking me about the Indian businesses, then it’s too early for them to adopt AI. The reason being, you need to optimise every single opportunity for the revenue growth, top line and bottom line via BI first and then go for AI because it becomes an ROI case. You have so many opportunities in BI space itself right now and it won’t immediately make sense to you. Right now, most of the Indian companies have not optimised to the extent where they get complete ROI out of the BI itself. Who is doing predictive analysis or at least prescriptive analysis with BI analytics? Very few. AI will be the next step.
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