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Smart Applications: Deliver Insights in Context

A quick look at companies disrupting well-established industries reveals a number of common characteristics. Among the most important, they’re all expert at delivering insights in context to their customers and users—and they do it by surfacing data-driven, actionable information via features in smart applications. Although smart applications were pioneered by web companies, today they are critical to enterprises across industries that compete based on how well they provide personalized software-based experiences to customers as much as on the quality of their products and services. How will your business compete?


What are Smart Applications?

Smart applications are those applications that incorporate data-driven, actionable insights into the user experience. Insights are delivered in context as features in applications that enable users to more efficiently complete a desired task or action. They often take the form of recommendations, estimates, and suggested next actions. Smart applications can be consumer-facing or employee-facing. In some cases, the “user” is not a human, but a machine or system. In these cases, smart applications automate business and operational processes based on data-driven insights.

For example, retail smart applications make product recommendations based on analysis of customer buying behavior while logistics applications provide data-driven estimates of delivery times of goods and products. Healthcare smart applications offer possible patient diagnosis and treatment recommendations to clinicians based on analyses of patient and research data.


Why Smart Applications Matter

Smart applications operationalize insights

No matter how effective your data science capabilities, data-driven insights hold no value if they can’t be operationalized and acted upon. Smart applications surface insights in context to users and systems, so they can take corresponding actions.

Personalize the customer experience

Today’s customer expects to be treated as an individual by the companies or organizations she interacts with, regardless of industry. By surfacing tailored insights, smart applications personalize the user experience, leading to higher customer loyalty and reduced customer churn.

Optimize customer interactions

Smart applications that deliver tailored insights enable enterprises to nudge customers and users to take specific actions that lead to desired outcomes in support of both tactical and strategic business goals.

Improve operational efficiency

Machine-to-machine IoT smart applications coupled with event-driven architectures allow enterprises to improve efficiency by intelligently automating operational processes based on real-time insights.

Enable new business models

Smart applications help enterprises in traditional industries, such as retail, financial services and transportation, develop new business models based on software, data, and predictive insights.



"During the next two to five years, we expect that B2C and B2B-to-consumer companies will adopt more smart app strategies. By 2018, we expect that most of the world's largest 200 companies will exploit intelligent apps and use the full toolkit of big data and analytical tools to refine their offerings and improve their customer experience."

Gartner
Top 10 Strategic Technology Trends for 2017



Considering Smart Applications?
What to Keep in Mind

Although smart applications are required to effectively compete in the digital economy, they require a rethinking of the way most enterprises develop, deploy, and manage software. Before getting started, consider the following:


Does your enterprise have a robust data science practice?

Data-driven, actionable insights are what make smart applications smart. A robust data science practice to uncover actionable insights hidden in large volumes of data is a prerequisite for successful smart applications.

Have your developers embraced Agile methodology?

By their nature, smart applications are dynamic, not static. They must be continuously updated with new features and capabilities, which requires developers that ship code early and often. This means developers must embrace Agile methodology and cloud-native microservices architectures.

Have your data scientists embraced Agile?

Agile isn’t just for developers. Data scientists must also take an Agile approach to analytics to support smart applications. Data science is an iterative discipline, meaning data scientists must be able to ask lots of questions of their data and update algorithms and models daily.

Do your developers and data pros collaborate?

Traditionally, application and software developers haven’t worked closely with data engineers and data scientists. Developing and maintaining smart applications requires enterprises to break down these cultural barriers and enable collaboration between developers and data professionals.

Are you prepared to rethink existing business models?

Smart applications aren’t an evolution of traditional enterprise applications. Rather, they are a revolutionary step forward. To get maximum value from smart applications, enterprises must be prepared to rethink business models and experiment with new ways of making money in the digital economy that leverage software, data, and analytics.



Smart Applications Versus Traditional Enterprise Applications
Smart Applications
Traditional Enterprise Applications
Data-driven. Data science and machine learning at scale that lead to actionable insights are the lifeblood of smart applications. Data blind. Most traditional enterprise applications were not designed to ingest or use output from analytical systems.
Deliver insights in context. Smart applications seamlessly present personalized insights in the context of the user experience to enable action. One size fits all. Traditional enterprise applications present similar views and features to all users with limited ability for customization.
Dynamic and evolving. Developers and data scientists continuously evolve smart applications based on new data, insights, and user feedback. Relatively static. Once operationalized, traditional enterprise applications are rarely updated in light of new data, insights, or user feedback.
Loosely coupled architecture. Smart applications require a loosely coupled, microservices-based architecture to support continuous evolution. Monolithic architecture. Traditional enterprise applications are monolithic, meaning their component parts are highly interdependent, making changes difficult to implement.


Pivotal and Customers Put Smart Applications into Action

Shipping

Shipping and logistics companies surface accurate delivery time forecasts via smart applications to both consumer and commercial customers.

Retail

Retailers recommend related products and targeted offers in consumer smart applications to shoppers.

Banking

Banks deliver personalized investment recommendations and related activities via smart applications to financial services customers.

Connected car

Auto makers use smart applications to surface traffic alerts and preventative maintenance suggestions to drivers.

Manufacturing

Manufacturers use smart applications to intelligently automate operational processes.



A Recipe for Smart Applications
Online Offline Capture Model API Decide Engage
Engage (Online)

Engage with users and machines to generate interaction data.

Capture (Offline)

Capture and process data in scale-out analytical database.

Model (Offline)

Develop predictive models to generate actionable insights.

API (Online)

Wrap predictive models in APIs to create services for scoring data against models.

Decide (Online)

Deliver insights via APIs in applications running on cloud-native platforms.




Smart Applications at Pivotal

Pivotal delivers the modern cloud-native platform and data analytics technologies required to support smart applications at scale. Pivotal also helps enterprises adopt the Agile application development and data science methodologies needed to develop compelling, dynamic smart applications.

For example, Pivotal can help organizations:

Transition to a cloud-native platform to support continuous delivery

Adopt modern data technologies for analytics and data science

Develop data-driven, microservices-based smart applications



Pivotal Moments
A financial media company working with Pivotal developed a smart application that incorporates real-time market data analysis to help users make better trading decisions.
Pivotal helped a multinational shipping company deliver a customer-facing smart application that provides real-time estimates of package delivery times.
A large U.S. university engaged Pivotal to develop a smart application that recommends actions students can take to improve their grades and prevent falling behind.



Pivotal Cloud Foundry
Enabling fully automated self service deployment


Pivotal Tracker
Proven project management for successful teams


Pivotal Labs
Transforming how teams build software—one story at a time


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