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Balancing the Big “I” and the little “I” of Innovation

Excerpt:
Many of us think of Innovation as that cool, new, never been done before breakthrough that completely changes the landscape of a business, its products, or the dynamics of the market. By that definition, we are referring to the Big “I” of innovation, and if successful, it can be an enormous win. These breakthrough or disruptive innovations are high risk and high return, and typically mid to long-term initiatives. It is because of the big payoff that companies should invest in these types of initiatives.

The incremental changes or improvements to businesses and products are known as the little “i” of innovation. While they are not quite as groundbreaking as the Breakthroughs, they are certainly powerful and profitable. Short-term innovations are typically focused on exploiting or optimizing existing business. They bring short-term revenue, increased efficiency, and cost-savings, which are important to keep the company going.

Having a balanced innovation portfolio is crucial to the success of your organization. Innovation has to bring tangible results and a competitive advantage to the organization by generating new revenue or reducing costs. Therefore you need a constant pipeline of new ideas, for a sustainable competitive advantage that provide short- and long-term benefits. 

#DriveInnovation   #GrowIncome   #SaveMoney  

Featured in Data Storytelling for Disruptors
http://blog.causeanalytics.com/2014/10/data-storytelling-for-disruptors.html 

Posted by +Dan Durrant 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com

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Making #Innovation a Priority

Citation:  Leaders and organizations are under more stress than ever to do two things simultaneously: deliver on today’s pressing commitments by troubleshooting and refining processes; and find and invest in innovation opportunities that will create tomorrow’s success.

How your organization responds to this stress in allocating scarce resources is a crucial but often unaddressed issue. The natural bias is to respond immediately to what is in front of you. The problem is, this instinct crowds out longer term, innovative thinking.

Kenneth Mikkelsen's insight:
Here, on average, is what leaders estimate they were currently spending their time on:

85% on day-to-day operations
5% on incremental improvements that produced faster, cheaper, better sameness
5% on small sustaining innovations
5% on big, disruptive innovations

Found via +Kenneth Mikkelsen http://sco.lt/8z658j

#Executives   #DriveInnovation   #GrowIncome   #SaveMoney  

Featured in Data Storytelling for Disruptors
http://blog.causeanalytics.com/2014/10/data-storytelling-for-disruptors.html 

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Automating Hamburgers

The Momentum burger-bot ... is more of a burger assembly line. 
. . .
Burger robots may improve consistency and sanitation, and they can knock out a rush like nobody’s business. Momentum’s robot can make a burger in 10 seconds (360/hr). Fast yes, but also superior quality. Because the restaurant is free to spend its savings on better ingredients, it can make gourmet burgers at fast food prices. 
. . . 
Earlier this year, McDonalds employees protested outside the fast food chain’s corporate headquarters in Chicago, demanding higher wages. A robotic kitchen might bring improved pay for the front of the house, and a pay cut to zero for the back. Some fraction of the 3.6 million US fast food jobs might be automated by such technology.

#SaveMoney #DisruptiveInnovation   #Automation   #Manufacturing   #Food   #USA  
HT +David Pidsley 

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Operational Resilience through Managing External Dependencies

Citation: These days, organizations are rarely self-contained. Businesses collaborate through partnerships and close links with suppliers and customers. Outsourcing services and business processes, including into Cloud Computing, means that key operations that an organization depends on are often fulfilled outside their control.

The challenge here is how to manage the dependencies your operations have on factors that are outside your control. The goal is to perform your risk management so it optimizes your operational success through being resilient against external dependencies.
. . . 
The Open Group’s Dependency Modeling (O-DM) helps you to plan for success through operational resilience, assured business continuity, and effective new controls and contingencies, enabling you to:

- Cut costs without losing capability
- Make the most of tight budgets
- Build a resilient supply chain
 - Lead programs and projects to success
- Measure, understand and manage risk from outsourcing relationships and supply chains
- Deliver complex event analysis

#SupplyChain   #Managers   #BuildResilience   #SaveMoney   #Partnerships    #Cloud  

Posted by +Dan Durrant 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com

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Swim with the tides of change to visualize data -- and decisions

Citation mix:
Completing a three-part series on his blue ocean strategy for decision visualization, Lee Feinberg explains how you can take decision making to the next level by giving more people access to business intelligence and data visualization capabilities. / #DecisionMaking    #DataVisualisation   #BusinessIntelligence   
. . .
Have you heard of democratization of data, a trending term in business intelligence? To someone outside your company, it would seem unbelievable that data is being held captive by a central governing body. However, most organizations do, in fact, control the flow of data and provide access to it on a need-to-know basis only. But doesn't everyone in the company need to know about the business? / #Collaboration  
. . . 
Data openness is really about democratization of decision making. By allowing more people to have better and faster access to data, you foster better and faster decisions by more people -- a powerful concept that will transform organizations. A common argument against this idea is that people don't know how to use the data properly. If that's really the case, the organization needs to make significant investments to ensure that everyone properly understands their jobs and the business. / #BuildResilience  
 . . . 
Training is another key aspect of support. You might create an amazing dashboard, but don't assume that your customers will know how to use it to analyze data. It's likely that many of them have never done a true analysis; most are used to looking at a mix of charts and hoping an insight appears. Some training ideas: Make a video walking through an example analysis from the view of different users, hold lunch-and-learn sessions (everyone loves a free meal), form internal user groups. / #HumanResources  
. . . 
It's better to start with a simple set of requirements and build iteratively. By using Agile development techniques to rapidly create a product people can use to analyze and visualize data, new ideas will surface about what's most important to do next. And, by not going too far or deep with detailed specifications, it's much easier to move in a different direction and not have to defend a big investment. / #DriveInnovation   #SaveMoney

cc +David Pidsley 

Posted by +Dan Durrant 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com

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Affordable Analytics in the Cloud

Re: #BigData:
“As more businesses use ‘Big Data’ to boost profits, track trends and grow, the influx of analytics and “Big Data” will just become ‘Data’. In other words, massive data sets will become common data that more businesses use to propel growth and will be fully integrated within everyday operations.” — Andrew Urbaczewski, PhD
. . . 
Re:  #SaveMoney #Cloud #OnDemand
Affordable #Analytics : “Business analytics will become more affordable, with on-demand cloud based services that allow small businesses to spend less money. They won’t require the same massive capital investment of technology, server space and expensive programming, licenses and hardware that formerly only larger or wealthier companies could afford.” — Andrew Urbaczewski, PhD 
. . . 
Re: #LocalGovernment   #DecisionMaking  
Smarter Data: “As data becomes more readily available, usable and understandable, local governments will utilize existing data sets to make smarter decisions. For example, cities will utilize crime reports, school information and housing prices to make wiser decisions and more efficient investments.  This intelligent data will mean more government efficacy and smarter consumers.” — Andrew Urbaczewski, PhD  

Also see: #Entrepreneurs Reign http://goo.gl/HB3S0g

Posted by +Dan Durrant 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com

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Treating Your BI Project Like an Entrepreneurial Startup

Citation Mix: 
As a proponent of agile data warehousing and business intelligence, I [Ken Collier] am constantly looking for new techniques for delivering value to customers faster, adapting to their feedback, and evolving toward the right business solutions (regardless of initial requirements). I recently read the new book, Lean Startup by Eric Ries (Ries, 2011) and it has rocked my world. In the short time since this book hit the shelves in September, 2011, it has exploded in popularity. Be forewarned, this book is about entrepreneurship and high-tech startups. It isn’t about data warehousing, BI, or analytics ... or is it? / #BusinessIntelligence #DataWarehouse    #Entrepreneurs  
. . . .
Ries points out that “The fundamental activity of a startup is to turn ideas into products, measure how customers respond, and then learn whether to pivot or persevere.” Lean Startup techniques follow a Build-Measure-Learn feedback cycle. This cycle begins with an idea or hypothesis immediately followed by building a minimal viable product (MVP). Customer response to this MVP is carefully measured and the resulting data provides the basis for learning and adjustment. The goal is to move through this cycle as fast as possible, and as many times as necessary to converge on the product that customers want.
. . . 
Two critical elements of this cycle are the MVP and the validated learning that is based on scientific testing of customer acceptance. The MVP is the very smallest, fastest thing you can introduce to your customers to gauge their response. For a business intelligence “product,” this might be a disposable prototype report or dashboard mockup populated with snapshot data. For analytics, it might be a mockup of a scoring algorithm based on a rudimentary predictive model. It is the simplest version of what we think customers want, so that we can find out if our assumptions are correct. / #Dashboards   #Analytics  
. . . 
Once we have correctly discovered what customers want, then we can use agile BI techniques to build, refine, and mature the solution. Ries describes this approach as “…killing things that don’t make sense fast and doubling down on the ones that do.” This theme makes as much sense for BI directors as for startup entrepreneurs. / #BuildResilience  
. . . 
Data warehouse and BI program leaders are entrepreneurs within the enterprise. It is the job of these entrepreneurs to quickly determine which efforts are value-creating and which are wasteful. / #GrowIncome   #SaveMoney  

Posted by +Dan Durrant 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com

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Some of the basic benefits of #BusinessIntelligence

Citation Mix:
With today’s BI tools, business folks can jump in and start analyzing data themselves, rather than wait for IT to run complex reports. This democratization of information access helps users back up—with hard numbers—business decisions that would otherwise be based only on gut feelings and anecdotes. / #DecisionMaking   #SelfService   #InformationTechnology  
. . . 
Sharing is vital to the success of BI projects, because everyone involved in the process must have full access to information to be able to change the ways that they work. BI projects should start with top executives, but the next group of users should be salespeople. Because their job is to increase sales and because they’re often compensated on their ability to do so, they’ll be more likely to embrace any tool that will help them do just that—provided, of course, the tool is easy to use and they trust the information. / #Collaboration   #Executives   #Sales  
. . . 
A broad range of applications for BI has helped companies rack up impressive ROI figures. Business intelligence has been used to identify cost-cutting ideas, uncover business opportunities, roll ERP data into accessible reports, react quickly to retail demand and optimize prices. / #SaveMoney #GrowIncome

Besides making data accessible, BI software can give companies more leverage during negotiations by making it easier to quantify the value of relationships with suppliers and customers. / #SupplyChain   #Purchasing  

Posted by +Dan Durrant 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com

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Forget the CV, data decide careers #HumanResources  

Are recruiters arriving at the point when "crunching data could replace the human touch of job interviews"? This article shares interesting examples of how HR services provider Ceridian,  Xerox, IBM, and LV= have used #BigData  and #DataMining  in their recruitment efforts.

“Big data” and complex algorithms are increasingly taking decisions out of the hands of individual interviewers – a trend that has far-reaching consequences for job seekers and recruiters alike.

Posted by +Dan Durrant w/ +David Pidsley 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com

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The #InternetofThings Ecosystem: Unlocking the business value of connected devices

This is the year that some experts predict more data will be generated by machines than by people—with that expectation comes renewed attention on the promise of IoT. In a recent survey, nearly 75 percent of executives indicated that their companies were exploring or adopting some form of IoT solution, and executives believe that integrating IoT into the main business is necessary in order to remain competitive.
. . .  .
Re: #SaveMoney  
Delays in response time; lost, stolen, or misdeployed assets; process inefficiencies; and human error all drive higher operating costs for businesses. The right combinations of connected devices, infrastructure, data analytics, and processing—specific to the industry—can help companies reduce these types of costs. This is where the real value of IoT comes into play – in being able to take advantage of the almost boundless potential provided by the 
mass quantities of data produced in IoT transactions and making it valuable through advanced analytics.

Re: #RealTime   #Analytics   #Automation   #Logistics  
For example, real-time data flowing from multiple sources, transferred automatically and without human intervention, can be integrated and analyzed (“mashed up”) to make business decisions. Specifically, a packaged foods distributor might mash point-of-sale data with weather forecasts, truck locations, and production data to predict stock-outs, reroute distribution, and reduce stale inventory write-offs.
. . . 
Re: #Lifelogging   #HumanResources #Mobile #Healthcare  
e, wearable devices allow companies to digitize employees, 
which may include tracking and providing feedback on behaviors that affect wellness or job effectiveness, and could improve productivity across the workforce with the right supporting systems. But wearables enable a far more innovative product/service in mobile health (mHealth) platforms—one that may actually disrupt the health care industry (see sidebar). These 
mHealth platforms can deliver remote monitoring for patients, especially veterans and the elderly, who are in a home environment or reside in remote areas. This allows hospitals to not only offer much-needed, lower-cost home care rather than a hospital visit, but also delivers patient care in a more comfortable setting.
. . . 
Re: #BigData   #PredictiveAnalytics   #DataVisualisation   #ArtificialIntelligence  
With the rising volume of data generated by connected devices, predictive analytics may deliver customer insights and even anticipate customer behavior. Businesses may use advanced analytics on top of connected machines to actively sense and shape customers behaviors, as well as tailor products and services at timely customer decision points. Analytics coupled with interactive visualization tools will allow not only large amounts of clean data but also sparse and fuzzy data (i.e., cognitive computing) to yield insights.
. . . 
Re: #Security   #Privacy   #Cloud  
[T]echnology is advancing to provide greater levels of security. One of the interesting developments is the ability for homomorphic processing to perform real-time algorithms on encrypted data, alleviating the need to de-encrypt and re-encrypt data, making cybersecurity purely an encryption problem. As a case in point, IBM inventors recently received a patent for an encryption technique that may become an alternative to traditional M2M security. The homomorphic encryption (HE) technology allows entities in the IoT ecosystem to perform operations on customer data without decrypting the original data, thus maintaining its confidentiality.35 According to Global Industry Analysts, the HE market is forecast to grow quickly, given the escalating need for tightened security measures at each tier of data transmission across public networks (e.g., Internet and cloud-based services of smart computing and connected devices).

For the full paper: http://goo.gl/tcgU8k

Thanks +Inma VP 

Posted by +Dan Durrant 

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

www.CauseAnalytics.com
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