The business impact companies are making with big data analytics is driving investment in digital transformation across the board.
Faced with multiple waves of disruption in a COVID-19 world, almost 92% of companies are reporting plans to spend the same or more on data/AI projects, according to a recent survey from NewVantage Partners.
Small wonder.
Data mature companies are citing business-critical benefits from using big data, including:
Faced with multiple waves of disruption in a COVID-19 world, almost 92% of companies are reporting plans to spend the same or more on data/AI projects, according to a recent survey from NewVantage Partners.
Small wonder.
Data mature companies are citing business-critical benefits from using big data, including:
- Informed decision-making
- Cost reduction
- Better understanding of customers
- New product development
- Data monetization
Offensive drivers such as new competitive advantages, innovation, and transformation override defensive ones as change is becoming the only market constant nowadays.
Let’s explore what business benefits exactly companies are achieving with big data to edge out the competition.
But a few words about big data first
Big data came into prominence a decade ago, with an explosive growth in data generated every second in the new world of digital everything. A quick fact: we created roughly 2.5 quintillion data bytes daily in 2020, with almost 90% of all current data generated in the last couple of years.
Combining structured, semi-structured, and unstructured data (imaging, text, videos, social media posts, sensor data, etc.), big data is not just big but complex for traditional analytics systems. This is perhaps a reason that 60% to 70% of all data within organizations has never been analyzed for insights or larger trends (another quick fact).
Advanced AI solutions and new techniques, however, have made it possible to unearth hidden patterns and correlations in the massive volumes of data companies have been collecting for years. And big data has started talking, and making big business impacts too.
Combining structured, semi-structured, and unstructured data (imaging, text, videos, social media posts, sensor data, etc.), big data is not just big but complex for traditional analytics systems. This is perhaps a reason that 60% to 70% of all data within organizations has never been analyzed for insights or larger trends (another quick fact).
Advanced AI solutions and new techniques, however, have made it possible to unearth hidden patterns and correlations in the massive volumes of data companies have been collecting for years. And big data has started talking, and making big business impacts too.
So, what is the impact of big data on business today?
As all kinds of companies are trying to ride the big data wave for various business benefits, big data adoption doesn’t come easy. This is because just like anything else with big data, challenges are big as well, from poor data quality to silos, lack of coordination, and business misalignment.
There are a few success stories, though. Dive in.
There are a few success stories, though. Dive in.
Retail & Ecommerce
With heightened customer expectations, the rise in online shopping and returns, and Amazon being a major competitor almost to everyone, increasingly more retailers are relying on big data analytics to capture a business impact.
Big data/AI technologies in retail bring leading companies a lot of business benefits, including the ability to win customers with personal recommendations, forecast demand and revenue, improve day-to-day operations, and prevent fraud.
Big data/AI technologies in retail bring leading companies a lot of business benefits, including the ability to win customers with personal recommendations, forecast demand and revenue, improve day-to-day operations, and prevent fraud.
- Take Walmart, a leading retailer in the world that’s been on a transformational journey for a few years. Putting data democratization at its heart, Walmart has set up an analytics hub to provide employees with controlled access to data from hundreds of sources. Data-driven teams can now find quick solutions, like it was with a grocery team puzzled by a drop in sales for a particular item. Data manipulation helped them discover that the product price was uncompetitive due to simple miscalculations, and take prompt action.
- Major retail stores use video analytics enabled by CCTV and data mining techniques to understand customer behavior patterns. This provides them with insights into questions about dead spots in the store ignored by customers, optimum staffing, say, on a Friday night, products that are in demand in the hot weather, and many, many others. Using market basket analysis to explore customers’ demographics and purchasing patterns, retailers are making their products look like a total steal with adjusted prices and layouts.
- Ecommerce sites, on the other hand, can better target users with product recommendations by tracking clickstream data and other customer activity. The data gives them insights into channels driving the most traffic, pages or products attracting the most visits, who their most profitable customers are, and where the site might be losing users. By applying text mining to queries, they also help customers find the desired product much faster.
- Big data analytics empowers inventory management with end-to-end visibility. A 360-degree view of stock helps prevent missed opportunities that stem from product unavailability, non-synchronized stock levels across sales channels leading to overselling, or slow delivery. Amazon, for instance, has presented a patent for its ’anticipatory shipping‘ system that can predict what people want to buy before they even place their orders.
- Finding new customers has also been made easy with sophisticated big data/AI technologies when implemented in CRM systems. These platforms not only track unstructured email and calendar data but automate follow-up sequences and flag warm leads.
Marketing
“The aim of marketing is to know and understand the customer so well the product or service fits him and sells itself,” — Peter Drucker, a celebrated management consultant and educator.
Marketing and sales teams are leading the way in big data analytics, making a great business impact with big data. The three types of data they are gathering — customer, financial, and operational data — enable a more accurate analysis of target audiences, financial performance, and business processes.
- Netflix is a great example of how data-powered advertising can fuel subscriber growth despite counterintuitive decisions like a VPN ban and a price hike in 2016. Those who are in the fan club know how they send you recommendations of the next show to watch. Netflix’s recommendation engines and new content production decisions rely on what titles people search or watch, time spent selecting movies, how often playback is stopped, ratings given, etc. Hollywood screenwriting star William Goldman said, “Nobody, nobody – not now, not ever – knows the least goddamn thing about what is or isn’t going to work at the box office.” Well, Netflix knows!
- Google and Facebook also know a few things about data-driven advertising, deriving huge business benefits from big data. By collecting and analyzing massive volumes of personal data we share, they serve better targeted and more personalized ads of products and services that we might be actually interested in buying.
- With the proliferation of smartphones, big data analytics has enabled hyper-localized advertising (which, let’s admit, is quite creepy). Capturing location and demographics data, analytics platforms can send shoppers near the store an ad offering discounts or other initiatives.
- Another good example of big data and its business impacts in marketing is the coupon story of Kroger. The US largest grocery network mails highly personalized coupons to shoppers, reporting redemption rates at more than 70% within the next six weeks. Studying each customer’s DNA rather than segmenting them demographically, Kroger offers coupons for what people actually like, meaning that a Coke drinker is unlikely to be embarrassed with a Pepsi coupon offer ever.
Healthcare
Big data analytics is taking healthcare by storm, helping predict epidemics, cut down treatment costs, avoid preventable conditions, and improve the overall quality of our lives. Operational improvements are also on the list of sought-after big data business benefits.
Insights are flowing in from multiple sources that include clinical data, electronic patient records, payer records, patient portals, results of medical examinations, wearables, smartphones, genetic databases, and other.
Insights are flowing in from multiple sources that include clinical data, electronic patient records, payer records, patient portals, results of medical examinations, wearables, smartphones, genetic databases, and other.
- Electronic health records (EHR), perhaps the widest application of big data in healthcare, give health professionals access to complete information on a patient, including demographics, medical diagnoses, prescriptions, allergies, etc. EHR systems improve care through automation and better collaboration between providers, sending screening or vaccination reminders or alerts of contraindicating conditions, abnormal lab results, or drug interactions. They empower predictive analytics in healthcare, with examples here featuring an ML-driven predictive analytics tool built by North Oaks Health System to accelerate antibiotic treatment and reduce sepsis mortality using EHR data.
- Big data business benefits in healthcare include optimized staffing levels. A group of French hospitals, for instance, are using an analytics platform to address the overcrowding problem. The platform can predict emergency department visits and admissions for the next 15 days, powered by a database on more than 470,000 patient encounters and additional data on external factors such as weather, holidays, and flu incidence that correlate with hospital visits.
- Another important area where big data is making a great impact in healthcare is epidemic management. During the 2014-16 Ebola virus outbreak in West Africa, researchers turned to data on the location and frequency of calls to helplines to map the population’s movements in the region. A similar mobile phone data analysis was used after the Haiti earthquake in 2010 for targeting relief operations and predicting the spread of the subsequent cholera outbreak.
- Big data research is making big strides in improving the detection and treatment of certain conditions. Examples include technology company Tempus that has created a massive library of clinical and molecular data to enrich context on each patient’s cancer case for more personalized treatment options. In the dermatology field, modern AI algorithms trained to detect benign and malignant skin lesions have achieved the accuracy of board-certified clinicians. The automatic classification of skin lesions based on images is deployable on smartphones, holding the potential to increase low-cost access to vital diagnostic care.
Finance
The increasing use of data is named among the major trends that will be shaping the banking sector in the next decade.
For banks and other financial institutions, the impact of big data on business centers around new levels of security and better customer loyalty driven by personalized offerings.
For banks and other financial institutions, the impact of big data on business centers around new levels of security and better customer loyalty driven by personalized offerings.
- Better customer service empowered by big data analytics is on the list of top priorities for the Royal Bank of Scotland (RBS). The RBS analyzes packaged bank accounts to detect whether a customer might be paying twice for the same service and uses analytics to spot customers who could save money from consolidating their loans. Their systems also send deal renewal reminders to mortgage holders when they approach an automatic transfer to a more expensive variable rate.
- Fraud prevention is another common application of big data in the banking sector. Lloyds Banking Group, for instance, creates what it describes as audio fingerprints of customer calls by analyzing unique call features (location, background noise, calling history, etc.). Meanwhile, American Express is reporting a 100% improvement in its resolution rate for digital fraud and a 21% reduction in POS disruption since adopting AI-powered data analytics in 2014. AmEx also uses big data for new customer acquisition via online channels and the development of apps linking cardholders with merchants on personalized offers.
- Big data delivers big impacts when it comes to risk management in banking. Success stories include Singapore-based United Overseas Bank (UOB) that has reduced the time cycle of calculating the value at risk (the risk of loss for investments) from hours to minutes and Morgan Stanley that has achieved greater accuracy in financial risk prediction with the help of automated pattern recognition.
Education
Big data/AI technologies are revolutionizing education, making it possible to analyze the student’s performance and behavior in real time, improve teaching approaches, and reinvigorate entire education systems.
- By capturing data such as test scores, response times to questions, or questions that students fail or answer successfully, big data analytics systems allow educators to personalize the learning process and improve students’ results. With real-time assessment tools and sophisticated applications, Ashford School in the UK, for instance, has not only created a more optimal learning environment but reduced overall IT costs.
- Big data technologies are also used to monitor students’ facial expressions and other biometric data via cameras or wearables to gauge their learning engagement or boost safety (the ethics behind this big data application is delicate though).
- Assisting students with a career choice is another important application of big data in education. College planning platforms like Overgrad help students understand fields they are interested in, track progress toward their educational goals, and follow schools of their liking.
Ending note
Many companies across industries have woken up to big data technologies and business impacts they are delivering. The game is on, and more is coming.
According to Wikibon, the big data analytics market should reach $103 billion by 2023. Meanwhile, global spending on big data, reported at $180 billion in 2019, is projected to grow at a CAGR of 13.2% between 2020 and 2022.
This means competition will get bigger. Don’t hesitate, go big too.
According to Wikibon, the big data analytics market should reach $103 billion by 2023. Meanwhile, global spending on big data, reported at $180 billion in 2019, is projected to grow at a CAGR of 13.2% between 2020 and 2022.
This means competition will get bigger. Don’t hesitate, go big too.
If you don’t know how to get started with a big data journey in your industry or are stuck in the middle, contact ITRex big data experts. They will be happy to share their experience and expertise.