Downstream data have been electronically available on a weekly basis since the late 1980s. But most companies have been slow to adopt downstream data for planning and forecasting purposes. Let's look at why that is. Downstream data is data that originates downstream on the demand side of the value chain. Examples
The Internet of Things is coming fast and furious. We clearly know what these “things” are, and were able to see prototypes at last week’s Mobile World Congress (MWC) which hosted some 93,000 attendees. Things = connected life = cars, homes (thermostats, washer and dryers, vacuum cleaners, security systems, refrigerators, etc.),
Innovation within hospitality drives awareness, service delivery, guest engagement, and brand differentiation. SAS asked a panel of experts to comment on how innovation is shaping the hospitality industry. According to many of our experts, analytics is at the heart of innovation. Learn more in this white paper on building
Today in manufacturing there has been a lot of investment in automation, supervisory controls, quality, and execution systems. The amount of data produced and now being captured is staggering. The data captured in industry will re-define what is “big” in big data. Yet, for all this investment: Equipment still fails. Scrap
“When it comes to the Internet of Things, the future clearly belongs to the Things”. I made this brash statement in a previous post (“Cloud encounters of the Fifth Kind”) referring to machine-to-machine (M2M) being the fastest growing component of non-human traffic on the Web. I say “brash” because that
Chess as a team sport? Sure, it’s like singles tennis as a team sport: the team score is an aggregate of individual results. Team chess is everywhere from local three-round weekend afternoon chess tournaments to the biennial Chess Olympiad where national chess teams compete for the Hamilton-Russell Cup. Just like tennis teams, chess
You may be intrigued to know how the average person compares to a gold medal winning Olympic athlete when it comes to things like height, body mass, resting heart rate, arm span, body fat etc. Or, perhaps more frightening, how you measure up? I know this will resonate with my
The old adage is that “Data is the lifeblood of the insurance industry.” However, for many insurance companies, data is like the red-headed stepchild. No one is willing to take care or have responsibility for it. In the past, insurance companies have created data governance programs, but these have often
Warranties have a long - and some might say - interesting past. But the future is even brighter. New technologies and data sources are transforming our understanding of field quality, enabling deeper insights into product performance and customer preferences. These breakthroughs are accelerating the quest to reduce defects and satisfy customers.
From the pressures of a highly competitive marketplace to changing economic conditions, to the evolution of the distribution network - the challenges facing the hospitality are many and varied. In this video, SAS asked a panel of experts to share their views on the issues that will challenge the hospitality
