White Papers

 

White Papers


Workforce Planning Prediction
Mosaic Data Science

Optimizing seasonal staffing and resourcing is a key challenge for many industries, especially when the exact timing of high-volume activity can change based on complex factors. Augmenting the workforce too early means diverting profit to unnecessary personnel costs, while waiting until high-volume demand is already underway risks operating below capacity and decreasing customer satisfaction (e.g., if there are long wait times). Predictive analytics can be deployed to forecast seasonal demand, helping firms to anticipate periods with increased staffing needs.

Read More »

 


Revamping Airline Demand Forecasting
Mosaic Data Science

In the airline industry, it is valuable for management to know ahead of time how many seats will likely be occupied on any given flight. Because the number of seats booked affects resourcing demands and revenue, knowledge of booking trends can help airlines plan ahead. Traditionally, data scientists have approached this forecasting problem from two standpoints: backward—looking for trends in historical data for departed flights to inform predictions of future bookings, or forward—looking at bookings that have already been made for a future departure date to predict future demand.
Read More »

 


Advanced B2B Sales Analytics
Mosaic Data Science

If you were to search news articles for B2B sales or marketing analytics using your favorite search tool, you would likely find a number of articles stating how B2B marketing is antiquated, or how far behind B2B marketing is from B2C. One cannot be sure if this is just conjecture to drum up business for marketing agencies or consulting firms, but there does seem to be quite a few people writing about it. Here at Mosaic we don’t believe that is the case. In the following white paper, we will lay out a scientific approach to utilizing predictive analytics and machine learning using our own sales data.
Read More »

 


Applying Statistics to Email A/B Testing
Mosaic Data Science

A/B testing has been around for a while. Its beginnings can be traced back to agricultural experiments that would test which variation of crops would grow better under specified conditions. Variations of what we now call A/B testing are used in multiple fields such as manufacturing, clinical trials, web analytics and of course, marketing. In its most basic form, A/B testing compares two versions of something and determines which one results in a more desirable outcome based on a chosen metric. Many data science consultants rely on A/B testing. The statistics involved merely tell us whether or not we can believe that the difference between the metric obtained from each variation is ‘real’ or just due to randomness.
Read More »

 


Predictive Analytics for Customer Experience Management
Mosaic Data Science

Using data to inform your marketing, sales, and customer experience decisions is increasingly essential for business success. If businesses fail to provide personalized customer experiences, they face the loss of brand equity, market share and — most importantly — loyal customers. Today’s consumers have more access to information than ever before. Information like where to shop, what to buy, and how much to pay are all at consumers’ fingertips. Companies that embrace new data streams and model them with internal data sources like historical sales and demand data will provide enhanced, more focused experiences, keeping and growing their valued customer-base.
Read More »

 


Dispatch Routing Optimization
Mosaic Data Science

This case has gained popularity in the commercial market with plenty of companies needing to move plenty of product. Software providers and consultancies have jumped at the opportunity to design algorithmic approaches for minimizing transportation costs and maximizing profits. As technologies make it economical for companies to acquire and store data, organizations can integrate previously unknown variables such as weather, real-time asset locations, inventory levels, transactions, etc.
Read More »

 


Two Data Science Proofs of Concept for Utilities
Mosaic Data Science

The Energy industry holds multiple predictive analytics and data science opportunities. One large utility hired a management consulting firm to study their data process. The management consultants identified over $300 Million of value by utilizing the data this utility had already collected over many years. With the rise of the Internet of Things (IoT) and data collection technologies becoming more accessible, utility companies have a wealth of data to mine.
Read More »

 


speech-bubbleUsing Data Science to Score Marketing Content
Mosaic Data Science

The growth of the Internet in recent years has caused an evolution in on-line advertising. Static advertisements gave way to dynamic pop-up and banner advertisements which now, in turn, have given way to organic, or “native,” marketing content that blends in with the Internet viewing experience.
Read More »

 


teamSoftware AG Partnership Fact Sheet
Mosaic Data Science

Advancements in data collection and integration technology allow companies to gain access to information previously thought impossible. With this wealth of data comes the need to analyze it in real time so companies can become data-driven decision-makers.
Read More »

 


pic-reducingemployeeturnoverUsing Data Science to Reduce Employee Turnover
Mosaic Data Science

Management scientists have studied for decades how to recruit, motivate, and retain employees. These three issues are closely related, so that one cannot effectively address any of them without addressing all of them to some degree. In particular, a highly motivated employee is far less likely to leave; while recruiting an employee who poorly matches the organization culture or job requirements will make it difficult, and perhaps undesirable, to retain the employee.
Read More »

 

 


pic-casestudy1Standing up a Data Science Group
Mosaic Data Science

Many large corporations have recognized that data science creates significant revenue-enhancement or cost-reduction opportunities. Historically, data science work has mostly been the purview of experts such as industrial engineers, clinical researchers, market researchers, advanced business…
Read More »

 

 


pic-casestudy-datavalueThe Value of Information in the Age of Big Data
Mosaic Data Science

This white paper explores how traditional models of the value of information (VoI) can be extended effectively to account for uncertainties presently inherent in gathering and analyzing big data. To illustrate the challenge, we explore the VoI an automobile manufacturer may derive by engineering…
Read More »

 

 


pic-whitepaper-edwWhy Enterprise Data Warehouse Projects
Fail, and What to do About it

Mosaic Data Science

Everyone knows data warehouses are risky. It is an IT truism that enterprise data warehouse (EDW) projects are unusually risky. One paper on the subject begins, “Data warehouse projects are notoriously difficult to manage, and many of them end in failure.” A book on EDW project management reports that…
Read More »