Dependent on the unpredictable? To disclose the secret of upcoming environmental and weather conditions is a fundamental challenge for the energy, utilities and agriculture industries. Reliable short-term and long-term predictions of plant growth, yield, pest infestation, wind speed, rainfall, ocean currents or solar radiation – the answer lies in the analytical liaison of geotemporal information and the Internet of Things (IoT). Or in short: Data to models – this it is what the latest developments from the Microsoft Research labs are all about.

Curious about how this will reshape business models, risk management, forecasting and security of supply? Then meet the Microsoft Research team at Hannover Messe (HMI) from April 13-17 in hall 7, booth C48 in Germany. At HMI, explore three areas of our vision in connected devices, geotemporal information and cloud analytics for business development: FetchClimate, predictive modeling, and NodeAtlas.

FetchClimate: accelerate access to spatiotemporal information

FetchClimate is a fast and flexible spatiotemporal information retrieval cloud service that can be accessed via a web browser. This current public service contains a variety of common climatological information layers (e.g. temperature, precipitation) and the underlying software has been released to allow others to build their own FetchClimate. FetchClimate was inspired by the research teams’ frustrations in finding and processing environmental data. Now they’re living the dream of simply being able to specify what they want for when and where in confidence that they’ll receive the best data suited to their purposes, fast!

NodeAtlas: discover and add spatiotemporal information through a browser

Node Atlas is a cloud SQL database service coupled with an attractive user interface. This currently unreleased prototype takes working with any data that can be tagged to geographical space and time to another level. Node Atlas allows users to simply discover any information pertaining to space, time or any other number of databased properties (e.g. looking for all wind farms in Europe). New information sources (such as a new sensor network deployed in the field) can be added in real time making NodeAtlas well suited to this Internet of Things age. Advanced features like iterative search and through-the-browser schema modification not only allow users to zero in on what they want faster but also allows database developers to quickly customise existing databases to user requirements.

Machine learning meets domain understanding meets cloud information and analytics: our modelling environment

Many big data analytics applications involve combining spatiotemporal information and machine learning techniques in order to produce useful predictive models. Our new modelling environment enables that to be done rapidly. We will show how we use our modelling environment to train a new predictive model to data fetched from FetchClimate, propagate uncertainty to produce probabilistic forecasts, visualise outputs, easily iterate on the modelling pipeline to improve predictive ability and then push the model out to FetchClimate as a service. Producing valuable new environmental information has never been so easy!

The Future is Now!

The post An analytical liaison for a sustainable future appeared first on Microsoft Industry Blogs - Canada.

By collaborating on abandoned drug trials, pharmas decreased time to market from 14 years to 2 years, an 86% improvement – published by Fortune. Another figure: 50% of the new product ideas for Procter and Gamble come from outside the company. And Pfizer invested $100M over five years in collaboration with university scientists and expects to reduce time to market by 5 to 6 years.

These kinds of results and findings are endless, especially for innovation driven companies. An estimation from McKinsey indicates “R&D spending in these (advanced manufacturing) industries is generally large, ranging from 5 to 20 percent of revenue. We estimate that by utilizing social technologies, advanced manufacturing enterprises can capture value equivalent to 12 to 15 percent of costs, by gathering customer feedback, improving collaborating among engineers, and co-creating products with an external community.”

Social Enterprise: Embrace It By A Cultural Change

As we already discussed in part 1 of this blog post: The social enterprise is a fact, not an option. But best practices and business cases also show the need for a close alignment of technical innovations, corporate strategies and culture as well as HR and LCA. Here just some areas to think about:

• Access and rights management: Social collaboration changes the rules on how we have to define and protect intellectual property.

• Leniency programs and patent laws: Sharing knowledge across department and company borders as a key driver for social collaboration needs the adaption of metrics to honor excellence.

• Hierarchy structures: Today communication and knowledge transfer are influenced by formal hierarchies. This will change with fully integrated social technologies and need to be considered in corporate culture.

• Knowledge generation: The knowledge within social collaboration platforms has tremendous value as soon as it is linked with corporate data. Thus, the full integration of social collaboration with business software and data opens new dimensions of business intelligence.

• Customer orientation: The increased speed of problem solving and personal interaction with customers is a key result of social collaboration. This should not be considered as a coincidence but rather implemented as a profitable strategy for service levels.

• Ability to innovate: The advantages of social collaboration in R&D are undisputed, but it will also result in unexpected improvement initiatives for any company area. Be prepared to recognize and act on that instead of losing opportunities and frustrating people.

• Knowledge management: To support job rotation and onboarding, social technologies centrally collect knowledge in a working “pod” rather than in hierarchical data graves.

• Best practice sharing: The establishment of central Wikis, easy to contribute and searchable, helps to gather and structure the hidden knowledge and expertise within the company and increases the speed of problem solving in particular for sales and services.

Enterprises who are able to embrace the opportunities with social collaboration will experience unprecedented capacity for innovation. Need some inspiration for this? Then have a look at the video “Productivity Future Vision”. It gives a taste of what to expect for interdisciplinary collaboration in R&D: stunning technologies tap the full potential of young talents and experts globally, integrate laboratory research in real-time with exploring expeditions, visualize ideas and simulate scenarios to accelerate innovations ready for the market.

Microsoft: Productivity Future Vision

Ready to hear more insights on social collaboration? Register for our upcoming webcast – “Collaborate and Innovate Across the Globe – Embrace The Social Enterprise” – on March 31, 2015 from 9:00 – 9:30am PST.

Want to recap the insights from part 1 of this blog post? Then read it here.

The post You are a social enterprise even if you don’t know it – Part 2 appeared first on Microsoft Industry Blogs - Canada.