The synergy between predictive analytics and decision optimization is critical to good decision making. Predictive analytics offers insights into likely future scenarios, and decision optimization prescribes best-action recommendations for how to respond to those scenarios given your business goals, business dynamics, and potential tradeoffs or consequences.
Together, predictive analytics and decision optimization provide organizations with the ability to turn insight into action—and action into positive outcomes.
In this white paper, you’ll gain a better understanding of:
The difference between predictive and prescriptive analytics
How predictive and prescriptive actions complement one another to help you achieve optimized business decisions
IBM’s approach to creating a powerful end-to-end decision management system
With the advent of big data, organizations worldwide are
attempting to use data and analytics to solve problems previously
out of their reach. Many are applying big data and analytics
to create competitive advantage within their markets, often
focusing on building a thorough understanding of their
High-priority big data and analytics projects often target
customer-centric outcomes such as improving customer loyalty
or improving up-selling. In fact, an IBM Institute for Business
Value study found that nearly half of all organizations with active
big data pilots or implementations identified customer-centric
outcomes as a top objective (see Figure 1).1 However, big data
and analytics can also help companies understand how changes
to products or services will impact customers, as well as address
aspects of security and intelligence, risk and financial management,
and operational optimization.
High-priority big data and analytics projects often target customer-centric outcomes such as improving customer loyalty or improving up-selling. In fact, an IBM Institute for Business Value study found that nearly half of all organizations with active big data pilots or implementations identified customer-c entric outcomes as a top objective (see Figure 1).1 However, big data and analytics can also help companies understand how changes to products or services will impact customers, as well as address aspects of security and intelligence, risk and financial management, and operational optimization.
Leading businesses have aggressively adopted prescriptive analytics to assess the different outcomes of potential decisions and identify the best one(s) for handling a future scenario. As companies progress their use of advanced analytics, they derive exponentially more value from their data and decisions. These five case studies highlight how five banks are using FICO optimization to boost portfolio profits by 26% or more; increase approved transactions by $100+ million; and even generate 6:1 ROI in just six months.
Companies of all sizes have a critical need to match supply and demand as efficiently as possible, in order to quickly capture maximum demand at the lowest possible cost. This tutorial will walk you through a demand forecasting and planning solution that can help you deliver more accurate demand forecasts, optimized operations to satisfy demand, and a complete operational and financial plan that the business can use in practice.
In this tutorial, you will explore the following key capabilities:
Improve decision-making in a single workspace with IBM Planning Analytics
Deliver timely, reliable plans and forecasts with the addition of SPSS Modeler
Create optimal demand plans with the addition of IBM ILOG CPLEX Optimization Studio
Sales and Operations Planning (S&OP) isn’t just about aligning supply and demand. Ultimately, businesses across all industries need to synchronize plans across all functions to strike the right balance between demand, resources and other constraints. Companies are realizing that their use of analytics to help improve decision making needs to evolve beyond just reporting to include machine learning and optimization.
Download our latest Q&A now with published author and supply chain expert Mike Watson, and learn how virtually any S&OP decision can benefit from advanced analytics and automation. You’ll get practical advice to help build a strawman, so you can move forward quickly – before your competitors!
Read this Executive Brief to know the Top 7 Questions to ask before deploying your Sales and Operations planning.
Businesses today certainly do not suffer from a lack of data.
Every day, they capture and consume massive amounts
of information that they use to make strategic and tactical
decisions. Yet organizations often lack two critical capabilities
when it comes to making the right decisions for the business:
the ability to make accurate predictions about the future,
and to then use those predicted insights in conjunction with
organizational goals to identify the best possible actions they
The combination of predictive analytics and decision
optimization provides organizations with the ability to
turn insight into action. Predictive analytics offers insights
into likely scenarios by analyzing trends, patterns and
relationships in data. Decision optimization prescribes
best-action recommendations given an organization’s
business goals and business dynamics, taking into account
any tradeoffs or consequences associated with those actions.
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