Our big data Guru and VP- Business Intelligence (BI), Jaspinder Singh elaborates on how BI has become a core part of Mystifly and how it is being used to serve our clients in the best possible way.
Scenario: An industry forced to contend with consumer demand, brutal competition, and environmental conditions – Airfare distribution.
Solution: An agile, advanced analytics ecosystem – Business Intelligence.
In simple words, Business Intelligence (BI) helps decision-makers dive deep into their businesses. It is a yardstick to set checks on Finance, Marketing, Operations, Technology and Development among other key business units. The BI mantra is that you never go by your gut; you always go by actual data.
At Mystifly, BI plays a crucial role in the overall operational strategy. We realize the importance of data and we make sure that all strategic decisions take into account insights and intelligence mined from data. We rely on BI to keep track of all the parameters, ranging from top line, bottom line, finance and turnover ratio to deliverables, alternatives, etc.
The BI team at Mystifly handles three key functions – Data Engineering, Data Analysis and Data Research. A data engineer gathers and collects data, stores it, does real time processing on it and serves it to a data scientist who can easily question it. The Data Engineering team at Mystifly builds the plumbing system of the data pipeline. They ensure that the data collected from various sources is ready for analysis.
Data Analysis is a process of inspecting and modelling data, with the intention of discovering useful information, to help make the decision making process much easier. The Data Analysis team is more involved with the trends and various other parameters. They solve questions with solutions as simple as a ‘yes’ or a ‘no’. Every change in the system is tracked by this team and is analysed to evaluate the success percentage of this change.
The Data Research team deals with a tonne of volume in terms of data. They do about 2-2.5 million searches a day on an average, comprising of transactional data. This enables them to get insights into various problems and suggest appropriate solutions. For instance, when we observe a drop in ticketing conversion rates, we are able to understand the reason behind it through our research data, and then take suitable action. Research data, here, is the evidence that is used to support research conclusions.
At Mystifly we use BI to drive our revenue. Since we know our customer demands and their searches, we are able to provide them with the relevant and right solutions that help maximize their revenue.
Is Artificial Intelligence (AI) the new Business Intelligence?
AI is a new industry term that has become popular these days. AI and BI are two terms that are often interchanged. Though both of them work on tonnes of data, AI primarily works on information theory whereas BI works on statistics and modelling. The gathered BI data is used to feed AI, which can then be used to map models.
Since BI needs human intervention, it doesn’t encompass data alone, doesn’t look only at encompassing business processes and doesn’t focus only on internal learning. Hence, AI is definitely not BI! But it can be, in the near future, if everything goes as predicted by technologists.
Things have changed over the past few years owing to the proliferation of data science. The forerunners of BI have been Statistics and Math. At Mystifly, we use Alteryx and Python to plug things around and match data. Visualisation tools like Tableau are used across the organisation and have become a part of our routine.
Mystifly uses BI to understand the demand and availability of fares. BI evaluates the best fares so that we can deliver appropriate airfare content from the right suppliers to our clients. By giving them real-time feedback, BI helps us become the voice of our clients. Hence, it enables us to keep a tab on internal processes and response times, making us a one stop shop for all things related to air ticketing.
The future of BI looks bright. Tools are getting better and people are getting smarter. Collecting, storing, and accessing information is becoming much easier. Since all the mundane and drudge work is being automated, we will be able to direct our resources towards innovating and improving the existing framework.
Speaking of the future, we as Analysts, avoid making predictions without data to back them up. It’s a virtuous cycle and we’re in a journey of continuous learning and experimenting. Our goal is to constantly learn new things, add them to our skillset and improve consistently. Small, incremental changes over a period of five years will lead to significant growth in our organisation. End of the day, what matters is putting our best effort, every hour and every minute.