In Forrester’s 40-criteria evaluation of omnichannel order management (OMS) vendors, we identified the nine most significant software providers in the category — Aptos, IBM, Jagged Peak, Kibo, Manhattan Associates, NetSuite, Oracle, Radial, and SAP Hybris — and researched, analyzed, and scored each. This report details our findings about how well each vendor fulfills our criteria and where each stands in relation to one another to help eBusiness professionals select the right partner for their omnichannel order management needs.
Many organizations have understandably turned to consolidation and virtualization to reduce server complexity, footprint and cost-to-scale. The next step is to optimize performance using analytics, policy-based automation and new technologies like cloud computing. Companies that focus on server optimization are seeing greater flexibility and sustained cost and operational efficiencies, with administrators able to manage 2.5 times more servers and almost twice as many virtual machines per server.
The explosion in IT demand has intensified pressure on data center resources, making it difficult to respond to business needs, especially while budgets remain flat. As capacity demands become increasingly unpredictable, calculating the future needs of the data center becomes ever more difficult. The challenge is to build a data center that will be functional, highly efficient and cost-effective to operate over its 10-to-20-year lifespan. Facilities that succeed are focusing on optimization, flexibility and planning—infusing agility through a modular data center design.
It's no longer enough to be able to predict what might happen-organizations also need to know how to respond to predictive insights. This white paper describes how predictive analytics and decision optimization can work together to create a powerful end-to-end decision management system.
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 introduction of Oracle Database In-Memory and servers with the SPARC S7 and SPARC M7 processors Oracle delivers an architecture where analytics are run on live operational databases and not on data subsets in data warehouses. Decision-making is much faster and more accurate because the data is not a stale subset. And for those moving enterprise applications to the cloud, Real-time analytics of the SPARC S7 and SPARC M7 processors are available both in a private cloud on SPARC servers or in Oracle’s Public cloud in the SPARC cloud compute service.
Moving to the Oracle Public Cloud does not compromise the benefits of SPARC solutions. Some examples of utilizing real time data for business decisions include: analysis of supply chain data for order fulfillment and supply optimization, analysis of customer purchase history for real time recommendations to customers using online purchasing systems, etc.
It’s no longer enough just to convert—to stay competitive, you need to turn prospects into lifelong fans of your brand. But with commerce channels and buying behavior changing so fast, we all know that’s easier said than done.
What were once communications channels are now becoming commerce channels, with consumers making purchases on their TVs, on Twitter, and by text message. In the past, commerce and content data and experiences sat in their own silos. Those days are gone.
Published By: Optimizely
Published Date: Apr 06, 2018
Welcome to the conversion best practices toolkit from Optimizely!
You’re already one step closer to delivering meaningful digital experiences and turning prospects into customers. In an increasingly competitive landscape where customers demand more from their digital interactions with companies across a growing number of communication channels, customer acquisition can be a big challenge. In this toolkit, you’ll find a variety of resources aimed at helping you identify conversion optimization opportunities and acquire new customers with greater efficiency.
In April 2014, Nissan opened a new production plant in Rio de Janeiro, Brazil with an annual production capacity of 200,000 vehicles and 200,000 engines.
Along with a target of reaching 5% market share in Brazil by 2016, the plant’s opening was aligned with Nissan’s efforts to achieve 8% global market share, part of the “NISSAN POWER 88” five-year mid-term management plan initiated in 2011.
To help align their strategic and business goals with their use of technology, Nissan chose Red Hat JBoss BRMS to replace their legacy system.
'Innovatively growing a consumer base, especially non-users' can be a challenging task for a CPG organization, looking for growth strategies in a world of discerning loyalty and fragmented markets.
WNS designed a personalized consumer analysis framework that enabled a CPG major to successfully target non-user target segments, and enabled a two-fold growth in consumer base
and revenue from sales.
The CA Automated Storage Optimization Mainframe Suite provides a best-practices-based and intelligent approach to SRM, delivering the tools to identify and classify your storage assets. Access this Technology Brief to understand how to maximize use of existing storage resources and ensures protection of business-critical applications and information.
Published By: Teradata
Published Date: Jan 30, 2015
It is hard for data and IT architects to understand what workloads should move, how to coordinate data movement and processing between systems, and how to integrate those systems to provide a broader and more flexible data platform. To better understand these topics, it is helpful to first understand what Hadoop and data warehouses were designed for and what uses were not originally intended as part of the design.
Published By: Genesys
Published Date: Dec 11, 2013
Gartner recently released its Magic Quadrant for Contact Center Workforce Optimization, the annual report analyzing the workforce optimization industry. Gartner positions vendors based on Completeness of Vision and Ability to Execute.
Genesys improved its 2013 position moving from Niche Player to the Challengers Quadrant. This report provides you with insights you need to determine the Workforce Optimization Solution that is right for your organization. Read Now.
Even if you have only 15 mobile workforce employees, you can reduce costs and improve the customer’s experience using optimization software. Today, it’s easy because you don’t even have to provide dedicated mobile devices to your field employees, just an app. But how do you avoid difficult transitions for workers, long implementation times, and solutions that don’t work as you really needed? This paper walks you through the 6 steps to successful decision making.
Businesses with between 15-250 mobile workforce employees are looking for optimization software. At the same time, they don’t want a complex enterprise solution with long integration times and complex IT requirements. Many vendors are offering cloud-based solutions. But what does that mean? Is it secure? In this Q&A, we answer the most common questions about cloud-based software solutions for field service management.
Complex hybrid environments can make it difficult to track interdependencies, increasing the risk of disrupting critical business services. In this research paper by EMA, you’ll learn how application discovery and dependency mapping can help you:
• Meet granular targets for availability, cost, and time-to-revenue for cloud services
• Accelerate mean time to repair (MTTR) while communicating better with stakeholders
• Manage even the most complex hybrid environments more efficiently and effectively
• Understand the impact of proposed changes and potential security risks to guide decision-making
Published By: Anaplan
Published Date: Mar 05, 2015
Many sales organizations continue to operate as they have for years: At headquarters, executives work with sales leaders to set revenue targets for the year. Sales teams receive top-down goals, which cascade across product lines, channels and other business dimensions. The end result is an account-level target, which is assigned to a sales rep. Because most companies do not have an easy way to complete this process—nor do they use a common system of record—they must resort to the quickest and easiest mechanism at hand: spreadsheets, a nonscalable, single-dimensional solution that does not handle complete data sets. This approach also poses challenges across key sales management functions, including planning, execution and optimization.
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