Over the past 30 years, most companies have added new C-level roles in response to changing business environments. The chief financial officer role, which didn't exist at a majority of companies in the mid-1980s, rose to prominence as pressures for value management and more transparent investor relations gained traction. Adding a chief marketing officer became crucial as new channels and media raised the complexity of brand building and customer engagement. Chief strategy officers joined top teams to help companies address increasingly complex and fast-changing global markets. Today, the power of data and analytics is profoundly altering the business landscape, and once again companies may need more top-management muscle.
Time-critical decisions in transportation, risk management, security, disaster response, manufacturing, and other operational domains require continuous real-time situational awareness and intelligence. Most enterprise systems do not provide this today.
How much electricity is all of retail's e-commerce, big-data analytics and mobile shopping devouring? No one has calculated that, but a report out this month argues that all IT now consumes about 10 percent of the world's electricity.
Real-time monitoring already happens in intensive care healthcare settings, where patients' vital signs are constantly monitored. Now, use of the technology is being extended to less intensive settings, like remote at-home monitoring of the elderly or patients with chronic conditions.
Wider adoption of standards is key to supply chain efficiency and meeting new consumer needs, according to a report entitled The Future of Standards in the Consumer Goods & Retail Industry: Cut Costs and Meet New Consumer Needs. The authors call on the industry to introduce simplified programs to help users embrace and deploy standards while enabling provision of standardized product data to consumers.
Analyst Insight: "Big data" software and analysis will be the most important supply chain technology for forecasting and demand planning in the years to come. Through analysis of huge quantities of data it provides a competitive advantage by providing unparalleled insights. The challenge for companies will be staying ahead of the technology in a cost-effective manner, and developing organizational processes to effectively utilize the huge amounts of data and absorb the information into their organizational decision making processes.
- Nada R. Sanders, Professor of Supply Chain Management and Iacocca Chair, Lehigh University
In today's environment of Big Data and analytics, effective supply chain decision-making is only as good as the data influencing the decisions. Drawing actionable conclusions based on the best information possible is critical to maintaining a supply chain that is efficient and effective, but also acts as a continual driver of strategic and competitive advantage. But how can your organization ensure that the data used to draw conclusions and make decisions regarding the supply chain is clean, relevant and accurate?
Even in today's data-hungry analytics environment, collecting and keeping every tiny granule of retail data - down to the level of each individual transaction and web click - might seem like overkill. But Sears Holdings has discovered that data storage costs have gotten low enough, and analytical tools have grown powerful enough, that this approach to Big Data has shortened the time needed for analytics projects by 60 percent to 70 percent, while also improving promotion conversions, lowering inventory levels and boosting sales.
