In this series, we earlier covered how big data is being used across industry verticals. Though our coverage of most of those applications hovered around modern, IT-based industries such as banking, retail, and analytics, here we have identified some big data applications in traditional industries such as manufacturing and the food industry. Although big data isn’t being widely used in these sectors, it only means that there’s potential for gaining an early competitive advantage for those who can sense the opportunity.
DaaS and Big Data in Advertising
Traditional advertising was all about communicating in the same way to the whole set of your target audience. But this changed with the advent of the internet (especially behavioral targeted ads). But even that saw the Click-Through Rates (CTRs) plateauing after a point of time. Lately, you might have noticed a lot of highly targeted ads, sometimes even annoying remarketing ads. But this seems to have worked, at least that’s what can be deciphered from an increase of 62% in CTRs in 2013 over the previous year, according to one research.
Today brands have access to a lot of data in the form of reviews, tweets, followers, clicks, likes, etc. which contains great untapped potential. This unstructured data when coupled with macro-level data from ad agencies can provide valuable communication opportunities. Two questions that companies using Big Data Analytics in advertising must ask are – how can they analyze the data to gain insights on and to predict consumer behavior, and how can they align the new (unstructured, disparate) data sources with their existing data to derive actionable takeaways.
Big data in Industrial Automation
Industrial data is mostly a collection of sensor data taken at regular intervals and stored. Products like Enterprise Manufacturing Intelligence apply big data to view relationships between two or more entities, for example, energy consumption and product type, or that between production uptime and shift. Big data is also being used for predictive maintenance (with real-time monitoring and trend prediction) and energy-efficient production. Though there are some who believe most system designs already understand and account for large process variations and thus the cost of additional spending on big data technologies for industrial automation is not fully justified.
DaaS in the Food Industry
While most of the traditional applications of big data are in IT or IT-enabled sectors, using Big Data Analytics can also help industries such as food processing and food service industry. Here are a couple of ways in which big data could work out for the food industry –
To know how they’re performing, restaurants have so far relied upon written feedback collected from patrons after a meal. Now they can crawl restaurant review sites or monitor chatter about their (and competitor) brands on Facebook and Twitter. Apart from brand monitoring and sentiment analysis, those involved in the restaurant business can also crawl restaurant menu data.
Restaurants have access to valuable past ordering data which they can use for making recommendations for dishes they would be interested in, thereby providing a more personalized experience.
2. Operations and Supply Chain
Big Data Analytics gives businesses access to micro-level information that wouldn’t otherwise be recorded, for example, sensors and barcodes to track food from farms to homes. Supply chain optimization using big data technologies can open doors to higher preservation levels, lesser spoilage due to supply chain inefficiencies, and fresh food for the consumers every time.
Can you think of a vertical that’s leveraging big benefits out of big data? Do let us know in the comments section.