Business analytics case studies

Case studies

Business analytics case studies

Insight advantage in action

Want to know whether the insight advantage is real or not? Just ask our clients. They know the difference between garden-variety analytics insights and those that directly influence business outcomes. Here are a few real-life examples.

Algorithmic selling takes off

Faster, granular, connected…local in-store insights fuel growth

A global food and beverage giant recognized the opportunity for a new, more effective sales approach to help retailers move more of its products off the shelves on a store–by–store basis. For years, consumer product manufacturers had relied on national planning of trade tactics with light audit procedures to ensure proper merchandising and execution. Instead, the company wanted to pursue a novel approach that pushes win-win sales opportunities tailored for each and every store.

The company's recipe blended big data, data science, and digital technology to identify hyper–localized sales opportunities. These opportunities were shared with local sales teams through intuitive user experiences on tablets, which improved mobility and adoption. The innovative solution is an algorithmic way of selling that helps take away the guesswork, is more granular, and far less time intensive to prepare. Results indicate that this locally–focused, fact–based strategy is highly effective at driving incremental sales. It's a primary example of the adage "think global, act local" as selling gets instantly store–specific.

By arming its sales force with tailored assignments and recommendations for local stores, a leading global food and beverage company is winning with retail.

Driving down IT costs with data–driven insights

Analytics outcomes in agriculture

Organizations with large, distributed IT departments often find themselves struggling with an overwhelming amount of data across business units and functions. The challenges can handcuff the IT department's ability to provide actionable information to advise key executive decisions and drive operational improvements.

When a global agricultural and food conglomerate needed a better understanding of how it's departments were using IT services, the company first had to get a handle on it's data. Deloitte helped the company consolidate data from a variety of sources and developed a solution to evaluate how IT services were being used across the organization. Using tableau visualization dashboards connected to real–time data, decision makers were empowered to measure, analyze, and optimize IT spend across individual business units, regions, and countries.

Applying analytics to data from multiple service areas and geographies created a targeted, integrated solution that has delivered significant outcomes: Deloitte enabled the identification of more than $36m in cost reduction opportunities. The company is continuing to work with Deloitte to further extend analytics value across the organization.

Deloitte enabled the identification of more than $36m in cost reduction opportunities.

Global insurer embraces advanced analytics to improve predictability and service

The insurance industry’s very existence depends on actuaries’ abilities to make smart decisions based on data. Today, though, through ever-increasing amounts of information and the technologies that both gather and analyze it—sensing devices, fitness trackers, and artificial intelligence—insurers can gain deeper insights into its consumers’ lifestyles, companies’ risks, and other information. These insights can be used to predict losses, price products, educate consumers, and even build new insurance products based on consumers’ changing interests.

That’s why one of the world’s largest providers of insurance solutions asked Deloitte to help it use analytics so it could look again, dive deeper, and extrapolate unique insights from data generated across the 170 countries where it serves its customers. Deloitte pulled together a team of professionals from Switzerland, the UK, the US, and India to help the insurer build an enterprise-wide data analytics function. Deloitte also demonstrated the capabilities of its US and UK Deloitte Greenhouse™ analytics labs. As a result, the client has started to adopt the innovation and visualization of the Deloitte Greenhouse labs.

While the multiyear effort is in its early stages, the client’s biggest business units are pulling analytics-driven insights—providing opportunities to improve pricing, cross-sell products effectively, and achieve cost control through claims and underwriting management.

​New Mexico Department of Workforce Solutions uses behavioral insights to avoid overpayments

​While identity theft and criminal activity are certainly expensive for states, they are relatively rare compared with the more frequent small errors that happen when applying for benefits, which leads to improper payments. In New Mexico, only about half of the improper payments are ever identified, and, of those, less than half are recovered. In an effort to tackle the issue, Deloitte Consulting LLP helped the New Mexico Department of Workforce Solutions (DWS) combine insights from data science and behavioral science to identify and gently nudge individuals into more honest, consistent behavior. The key would be to improve design communications and notifications for claimants in three key moments: during the vetting process for eligibility, when individuals report work and earnings, and while determining an action plan to seek new employment. Many combinations were tested across three behavioral nudges: a pop-up message on the screen; a personal attestation or certification box; and clearer, simpler wording. By leveraging concepts from the field of behavioral economics, the New Mexico DWS was able to substantially influence claimants’ behavior. The State successfully increased accurate reporting while reducing improper payments.

Each person responding more accurately helps to avoid an overpayment and typically generates no additional staff work. Utilizing these behavioral insights in strategic moments as people are applying for benefits put New Mexico on track to save millions each year.

​Major travel and leisure company uses analytics to drive customer acquisition

​A major travel and leisure company was looking for ways to maximize its acquisition of co-branded credit card customers–and the old strategy of “carpet bombing” prospects with a daily email was leading to low yields and high opt-outs. We used analytics techniques to identify customers most likely to accept offers, using a mix of both internal and external data. We also created machine learning algorithms to predict offer acceptance rates by segment, going on to prioritize media usage, messages, frequency, and timing. The result? Improved acquisition efficiency for direct mail by 4x for top deciles.

​Major federal agency finds a new way to analyze critical health data sets-fast

​In driving drug discovery and development, a federal health agency required the ability to analyze disparate, complex data sets from around the world. From this arduous task rose the question, what if the agency could find a more efficient and effective way to analyze all that public and private data? Using SEMOSS (www.semoss.org), an open-source data federation and analytics tool, as well as cognitive capabilities, we helped the agency integrate disparate data types into a single analytics platform. Today, this platform allows researchers to access data and collaborate with a host of partners to accelerate scientific discovery. With SEMOSS, what once took four hours to accomplish now takes four minutes.

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