Business Intelligence Case Studies

BI Case Studies

Business Intelligence (BI) software is used in a variety of ways to serve small business goals, treat pain points, and lead to a competitive advantage. May it be a sharpening stone for better decisions, a monument to learn from the past, or a crystal ball to predict the future—there is a BI and data analytics opportunity in every business.

Choose a functional goal or industry vertical below for BI use cases to inspire your own success story:


BI | Business Innovation

Growing old with data

Faced with a greying population and not enough resources for its senior community, a city in Southern Europe looks for ways to save on required infrastructure by leveraging data analytics.


Approach:
  • Installation of a “smart” connected network of IoT devices including home sensors to monitor temperature, carbon monoxide levels, water and energy usage.
  • Analytics is applied to determine a profile of “normal” household behavior.
  • Baseline is used to identify aberrations, and alert family, neighbors, or emergency services.
Impact:
  • Lower assistance and care costs by 30 percent.
  • Reduce the need to build assisted living facilities, enabling more retirees to remain living in their homes.

Takeaway

BI and data analytics uncovers the unexplored value in existing data assets, recycling them for novel purposes and pioneering business opportunities.


BI | Marketing

Data driven marketing leads to roaring success

A small zoo on the US West Coast hopes to inspire new profits and business opportunities. Data analytics proves an important ally to increasing revenue.


Approach:
  • Analysis of historical data from 600,000 annual visitors, data collected at exhibits and event sites, social channels, and ticket sales.
  • Insights are used to craft real-time targeted marketing campaigns with the help of a BI and data analytics solution.
Impact:
  • Increase online ticket sales by 700 percent.
  • Double annual member renewals from 3 percent to 6 percent.

Takeaway

BI helps sketch an accurate profile of your customers to drive targeted marketing campaigns and better serve their needs.


BI | Customer Intelligence

Analytics offers customer insights businesses crave

A Fortune 500 consumer packaged goods (CPG) company looks to enhance their ideation process by identifying/verifying new flavors and products with relevant consumer data.


Approach:
  • Aggregate social channel data around consumer lifestyle trends, consumption habits, and preferences.
  • Narrow down 14 possible ingredients and flavors from a sample of 700 options using an iterative approach.
  • Ingredients and flavors are scored on key performance indicators (KPIs) such as volume of online buzz.
  • Use BI software to deep dive into drivers for adoption of a particular flavour and ingredient, before greenlighting to later stages of product development.
Impact:
  • 50 percent reduction in ideation and evaluation phase.
  • Rapidly identify statistically relevant test markets for each product idea.

Takeaway

Data analytics is a useful tool to unearth a new idea, as well as validate or expose an untested one.


BI | Medical

Leverage personal data to breathe life into new markets

A health solution provider based in the Northeastern US applies data driven solutions to family planning to reduce the average time it takes for a woman to become pregnant.


Approach:
  • 4 million data points from over 70,000 women collected through wearable wellness devices.
  • Self-reported information is aggregated via a mobile app, including medical history, weight, menstrual schedules, attempts to conceive etc.
  • Fertility experts and a Harvard scientist developed an algorithm to more accurately predict ovulation cycles and when pregnancy is most likely.
Impact:
  • Smart Fertility app used by 40,000 women and their partners.
  • Users report pregnancies in about 60 days (2-3x faster than national average).

Takeaway

The internet of things (IoT) and proliferation of technology receptacles to collect data has not only created novel ways to delight customers, it also offers tailored solutions to problems of the most personal nature.


BI | Operational Excellence

Going against the grain to achieve accurate forecasting

A bakery located in Northern Europe is challenged by fluctuating sales orders. To avoid out-of-stock or excess inventory, a BI tool is employed for accurate forecasting.


Approach:
  • Using an analytics solution, near-real-time and historical customer data is converted into a rolling sales forecast.
  • Patterns in demand are identified so that the bakery can have appropriate inventory levels to address fluctuating demand.
Impact:
  • 30 percent increase in sales order fulfillment; also reducing response time.
  • Achieved an on-time delivery target of 98.5 percent, while reducing risk of lost sales by improving the alignment of resources.

Takeaway

BI and data analytics can be applied as a reactive focus to shore up operational inefficiencies by analyzing historical performance data. But BI can also be used to look ahead to the future, and make highly accurate predictions and trend analysis for proactive gains.


BI | Retail Sales

The store that’s never the same twice

Unsatisfied with a static, unchanging store room floor that’s typical in many small retailers, one Northeastern US shopfront optimizes their retail space with data derived from customer traffic patterns. The frequent updates ensure a fresh experience for their repeat visitors.


Approach:
  • Gather foot traffic data from historical video feeds captured by existing security cameras.
  • Apply video analytics and visualizations of shopper profiles in order to create buyer personas and chart shopping traffic patterns.
Impact:
  • Heat maps identify the locations where customers most often cluster, this information along with average queue times enable the businesses to make improvements to store flow.
  • Optimize relative product placement.
  • Improve employee assignments and scheduling improve customer service satisfaction.

Takeaway

With data analytics, you can subvert expectations of what is possible, and discover disruptive strategies to reach your customers.


BI | Risk Management

Data helps to detect and destroy cyber security threats

A US based endpoint-threat detection and security company relies heavily on system information gathered from company devices to flag irregularities that may be related to security threats. However, their MySQL database backend has been outpaced by the increasing velocity and volume of data needed to effectively perform threat analysis. This has lead to the pursuit of a big data analytics upgrade.


Approach:
  • Leverage a big data solution built on Hadoop to boost scalability, as well as benefit from the speed of on-demand provisioning.
  • To move large amounts of data efficiently, Apache Hbase is used as the repository for endpoint data, and Apache Flume is used for data migration.
Impact:
  • Dramatically increase the ability to scale big data cyber protection from hundreds of devices to hundreds of thousands
  • Time to process large amounts of data, and by extension detection times, is reduced from years to minutes.
  • Near real-time response to threats works to further close the window of vulnerability to attack.
  • Flexible deployment options offered by the big data solution allows deployment across multiple software environments.

Takeaway

In terms of processing speed and scalability, data analytics solutions are providing a quantitatively better way to manage business big data and leverage it for positive business outcomes.


BI | Transportation

Data analytics takes the wheel for employee retention

Safety, performance, and retention of drivers are key factors for the human side of fleet management. A risk management consultancy serving the fleet and transportation industry in the Southern US offers a view of its business model, using advanced data analytics to maintain the condition and quality of its customers’ drivers.


Approach:
  • Telematics from drivers are gathered into a data warehouse and are combined with employee data from other integrated systems.
  • BI and data analytics tools assess drivers for risk factors such as miles driven, sleep schedules, and pay levels, as compared to company averages.
  • Detailed analysis of drivers’ pay compared versus peers and industry averages, in combination with other variables such as stress factors and employment history.
Impact:
  • 20 percent overall reduction in accidents; 80 percent reduction in severe accidents (e.g., roll-overs).
  • 30 percent reduction in employee turnover leading to savings on recruiting and training.

Takeaway

Employee data tells a story and when applied to human resources, actionable insights derived from employee data and BI tools can lead to better hiring relationships that benefit the company and the individual worker.


Research

All use case information presented on this page comes from publicly-available case studies published by the following publishers:

  1. Business innovation:
    http://www.cwhonors.org/case_studies/2012Finalists/Innovation/2510.pdf

  2. Customer Intelligence:
    https://www.latentview.com/case-study-leveraging-customer-insights/

  3. Operational Excellence:
    http://public.dhe.ibm.com/common/ssi/ecm/en/ytc03588usen/YTC03588USEN.PDF

  4. Risk Management:
    http://cdn2.hubspot.net/hubfs/150964/Cloudera_CaseStudy_CounterTack.pdf?t=1431701383332

  5. Marketing:
    http://www.zdnet.com/ibm-analytics-help-small-zoo-museum-engage-visitors-7000017044/

  6. Medical:
    http://www.informationweek.com/big-data/news/big-data-analytics/big-data-knows-when-youre-fertile/240158208
    http://www.ovuline.com/
    https://itunes.apple.com/us/app/id570244389

  7. Retail Sales:
    http://online.wsj.com/article/SB10001424127887324412604578514541384395664.html?mod=WSJ_JRIntl_4_2_LEFT?Mod=e2fb
    http://www.inc.com/john-brandon/this-start-up-is-shape-shifting-the-retail-store.html
    http://www.stores.org/following-trail#.UMfMWJPjma5

  8. Transportation:
    https://www-01.ibm.com/software/analytics/learn-center/index.jsp
    www-01.ibm.com/common/ssi/cgi-bin/ssialias
    http://presidionwp.s3-eu-west-1.amazonaws.com/wp-content/uploads/2014/09/FleetRisk.pdf
    http://www.ccjdigital.com/predictive-analytics-fleetrisk-advisors/

Buyers guide
Thomas LaMonte
Thomas LaMonte
Senior Content Analyst at Gartner
This buyers guide will help you understand the key features of business intelligence and analytics (BI) software, its benefits and challenges, information on who uses BI software, and industry trends.
Case studies
Thomas LaMonte
Thomas LaMonte
Senior Content Analyst at Gartner
Our Business Intelligence (BI) Analyst shares real-world case studies of BI implementations.