Forward-Thinking Businesses Are Strategically Adopting Dynamic Technologies

“Exponential price/performance improvements in technology are driving disruption because they enable new ways of adding value for customers and new business models.”

To survive and thrive in this fast-changing business environment, companies must be customer-focused, agile, and continue to innovate. How can organizations achieve this? Their infrastructure must enable agility and flexibility to allow the organization to rapidly innovate and pivot.

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How Growing Companies Benefit from Intelligent Capabilities

To stay competitive in today’s volatile marketplace, growing companies depend heavily on having a coherent, end-to-end view of operations. Without data, it’s difficult to optimize the entire customer experience, pivot to new business models, take advantage of new productivity opportunities, or increase and maintain workforce engagement. Midsize businesses grow in many ways, such as securing partnership investment, allowing owners and employees to take a vested interest, and securing personal loans to strengthen operations. The success of these companies comes down to the company’s valuation, which is measured by the ability to generate revenue, keep customers happy and loyal, and spark and maintain the interest of talented employees and leaders. Underlying these key factors is an even more critical asset – a strong foundation for collecting, leveraging, and operationalizing data.

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Achieving Data-Driven Workflow Process Optimization

The demand for data analysts, tools and resources is at an all-time high, with advanced data analytics presenting exciting opportunities for business process optimization. Using data analytics, finance teams can quickly monitor, report and analyze business processes to make informed decisions. Many businesses are adopting a new way of product data management as collaborative tool that meets their unique requirements based on their product revisions, lifecycle, and deliverables within their workflow process. The goal is to solve complex data management issues and streamline system integrations to deliver flexible process automation, team collaboration, visibility, data integrity and seamless sharing between multiple applications.

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Next-Generation Manufacturing Processes Are Here to Stay

Industrial machinery and component manufacturers are stretched thin, addressing global challenges like the need for clean energy, smart cities, and a circular economy. In addition, they are confronted with ever more demanding customers and the transformation of their business ecosystem, including customers, partners, and competitors. Innovative industrial machinery and component manufacturers are tackling these challenges by pursuing new business models based monetizing data assets. These companies are embracing new technologies as they focus on strategic priorities to drive digitalization. These strategies are helping them realize their vision.

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Do You Have the Tools to Promote Agility in Your Organization?

An agile way of managing application changes allows requirements to be delivered to the business in shorter, more frequent releases. This goes further than leveraging only an ERP system. Companies that are trying to improve operational efficiency and implement process improvements need more agile methodologies that can deliver continuous business value. There is nothing inherently wrong with delivering applications that are pre-planned, budgeted and have a well-defined scope. But just because it is done this way doesn’t mean that risk is removed. A tool that promotes an agile business environment allows the business to react quickly and strategically to change, and therefore create a more efficient workforce overall.

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Data-Driven Analytics for Financial Services

Data-driven analytics are key to the current and future competitiveness of financial service companies. By capturing and leveraging massive volumes of data, financial services companies can capitalize on new data-driven business opportunities. The first step toward realizing this goal is a solid data management foundation that supports the analysis of both enterprise data and Big Data. Once this foundation is established, financial services organizations can begin implementing machine learning algorithms to support automated decision-making and data-driven process optimization- helping them generate insights that create better customer experiences, improve operational efficiency and drive sales.

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[INFOGRAPHIC] Broken Promises: Is it Time to Break Up With Your Analytics Tool?

Many ERP and business process vendors claim to offer analytics tools that can provide advanced business insights and actionable information. However, one shortcoming of most business analytics programs is the inability to fully integrate data systems from across the company for dependable insights. If your analytics platform is not measuring up to your expectations, this infographic is for you. The only way to find true analytics love is finding the right software for your business.

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Facilitating Powerful Analytics in a Data-Driven Culture

Demand for advanced analytics is increasing, and so is the expectation that management accountants will perform the analytics. Finance leaders want a data-driven culture to maximize the value of data through analytics. Specifically, they aim to make business decisions faster and more accurately through automation and predictive modeling. Trust in data analytics is the foundation of a data-driven culture. Fortunately, progression through the stages of analytics maturity also builds a foundation of trust, and eventually business decision makers gain enough confidence in predictive models to let the models themselves make the decisions

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How Drill-Down Capabilities Can Increase Customer Retention

A world market leader of power tools and accessories manufacturing launches hundreds of new products each year across various brands. Until recently, the company relied on a traditional manufacturing process. Product teams worked with end users to identify needs and then build features around these needs to roll out around the world. However, they lacked insight into their user’s needs and how to leverage their data to become completely customer-focused. Once they gained the ability to drill-down into their data for important business insights, they were then able to create meaningful and fulfilling experiences for their customers.

Read More at Forbes Magazine >