A view from Future Camp: SAS, Accenture and Cloudera partner for IoT

Accenture's Digital Innovation Center

The flexible workspace at Accenture's Digital Innovation Center fosters collaboration.

It’s clear from the minute you step into Accenture’s Digital Innovation Center (Future Camp) in Kronberg, Germany, that you're stepping into the future of innovation. The writing is literally on the walls, and everything you need to inspire big ideas – from brightly colored furniture to racks and racks of gadgets – is right at your fingertips. This isn’t a space age workspace or a robotic-powered pod. It’s a hands-on meeting place for design thinking workshops and rapid prototyping, among other creative endeavors.

Some of the hottest tech in this center – and around the world – is powered by the Internet of Things (IoT). And what’s powering the IoT? Data. Lots and lots of data.

This is one of the driving factors in a new collaborative initiative between Accenture, Cloudera and SAS. We'll help organizations apply analytics to realize value from the IoT.

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How design thinking will re-frame IoT analytics prototyping

Data scientists are familiar with prototyping - we do this as part of a well-understood process to arrive at the optimum solution. But prototyping is more than about perfecting the math; it should also be about testing interpretability of the results. 

This need comes into stark prominence when you start thinking about the Internet of Things (IoT), and the streams of new data that will be flowing, as well as the much larger community of employees, partners and customers who will be interested in selected analysis of this data.

Putting the spotlight on user experience 

IoT success We’ve been referring to design thinking as a way to conceptualize the underlying IoT-driven change. Design thinking gives a natural focus for prototyping and use of big data: user experience. This can be helpful where there are many possible areas for focus, as it guides the process towards what really matters.

This is particularly pertinent for big data and analytics, because these areas often require innovative thinking, and consideration of new areas. The sheer volume of data can make it difficult to know where to start looking for insights. Design thinking, with its focus on user experience, often brings a new perspective to the table.

The focus on users has another benefit: It’s intrinsically democratic. It breaks down the split between ‘them’, the users, and ‘us’, the experts, by making clear that the user perspective is the most important element in design.

It therefore also has an effect on hierarchy within companies, and helps foster a more creative, and perhaps even experimental atmosphere, by making clear that everyone has equal potential to input effectively.

Why IoT needs design thinking

In many ways, the Internet of Things and design thinking have a potentially symbiotic relationship. The best way to experiment and prototype is with lots of data. In fact, the more data, the better, as this allows more potential to generate insights.

The actual quality of the data may be less important, at least in the first instance: raw data is perfectly acceptable for experimenting and prototyping. This may be a prime example of quantity trumping quality, although cleaning the data and improving its quality is likely to be necessary later, once beyond the initial prototyping.

Experimentation and prototyping requires a tolerance of failure. After all, if you knew something was going to work, you wouldn’t build a prototype in the first place. This tolerance of failure needs to run right through the company, as it’s likely to be a regular feature of any new approach, including design thinking, and therefore requires cultural change.

That said, it’s entirely possible that design thinking will actually make failure less likely, because it allows insights into customer thinking and therefore to what is likely to succeed.

“Minimum required for success” is more efficient than “perfect.” Part of a tolerance for failure is the need to work swiftly, and not seek perfection at the expense of speed.

As the Pareto principle states, 80 percent of the work can be done in 20 percent of the time. With prototyping, it is crucial to stop at the 80 percent point, and not waste time on the remaining 20 percent.

The last 20 percent is probably not essential for functioning, and certainly not at the prototyping point. It’s also the enemy of speed. Seeking perfection may mean missed opportunities to try something at the right moment.

Where to start

  1. Define the business question. It’s OK if it changes later, based on evidence and user experience, but it starts the process in a focused manner.
  2. Mine the data. Users probably won’t tell you about issues; but use the data to find the successes and problems.
  3. Review, revise and re-iterate.

You can read a perfect example on how to exploit data coming from the IoT to drive revenue, cut costs and innovate in this IndustryWeek Special Research Report: The IoT: Finding the Path to Value

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Don’t make your marketers experience a spaghetti junction

Throughout my 10 years at a leading direct marketing and CRM agency, a chief issue we solved for our clients was what we affectionately referred to as a spaghetti junction.

180469566It’s a nickname often given to a massively intertwined road traffic interchange that resembles a plate of spaghetti, like this one in Los Angeles that I used to commute on every day. How did I endure that? Podcasts. Many, many podcasts. But as you can imagine, it also resembles how customer data in many companies appears before it’s integrated.

Times were simpler then – before we took Uber anywhere or could order pizza with just an emoji and a tweet. But it was still a significant challenge for us to integrate disparate data sources for big brands. Our clients (major automotive, gaming and satellite TV brands) had mountains of customer data but needed help using it to understand their consumers and create better experiences.

How much more complex is your spaghetti junction?

A new report from Forbes Insights sheds some light on this. In the study, more than 350 global executives share their current challenges and achievements in integrating data to enhance customer experience with their brands.

What they found is that even among leaders whose organizations provide a data-driven customer experience (CX), only one-third can see most of the activity related to their customers. That leaves two-thirds of customer behavior and activity unaccounted for.  What’s standing in the way?  Internal processes and organization – of both people and of data. And it’s no wonder. Most companies more than a decade old have data infrastructures originally designed to account for only a handful of data sources. Now, our data sources have multiplied exponentially.

Making sense of an organization’s current spaghetti junction of data is overwhelming. So it’s not surprising that only 36 percent of companies say they’ve been able to do it.  Yet, we all want to (and even expect to – within just two years).

And we’re on the right path: a majority of organizations surveyed are fully embracing data analytics as a means to improve CX.

What we have to look forward to

There is a sizeable pot of gold at the end of this rainbow. Here are some of the organizational, customer and financial benefits we can look forward to as we strive to deliver highly data-driven CX:

  • Faster decision making.
  • Increased sales and revenue.
  • More repeat business from customers.
  • Greater ability to target and optimize for specific customers.
  • Improve consistency across channels.

Where to start?

To see where your company stands on the journey towards a more data-driven customer experience, take the Marketing Confidence Quotient. This online assessment is designed to help you understand how modern your marketing organization is and what the next steps are. Along the way, you’ll get tips and tricks to help get you there faster. You’ll also see how your status compares against other companies in your industry and of your size.

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IFRS 9 impairment: Time to get ready for the new standard

Starting in 2018, IFRS 9 will require banks around the world to change their processes for accounting of credit risk. This new impairment standard will move banks from the backward looking incurred loss model into a forward looking Expected Credit Loss (ECL) modelling approach.

When talking with banks around the world about how they deal with the challenges introduced by IFRS 9 Impairments, it seems that what attracts the most of their concerns is how to perform the assessment, simulation and deployment of the IFRS 9 Impairment methodology in a robust, timely and efficient manner while still being sufficiently flexible.

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The 'I's have it for improving utility asset performance in an IoT world

Two men viewing large monitors in a utility control roomOver the last ten years, utilities around the world have have invested billions of dollars in the Internet of Things (IoT). Better known as smart grid and smart meter initiatives, this massive intelligent infrastructure is moving utilities into a future that’s beginning to look radically different from the century-old business model that has provided reliable, affordable, safe electricity to billions of people.

Smart grid and smart meters are scoring big time on the customer side of the business, but operationally the benefits have yet to be fully realized. One area where utilities can leverage IoT is by making better use of the available data to improve asset management practices. There are several bright spots in the U.S. utility landscape where there is movement toward a data- and analytics-centric approach to managing assets in the transmission and distribution space. As an industry, though, we have a long way to go.

Having worked in the utility asset management market for 20 years, I’ll suggest a few concepts that may help us take better advantage of the resources available. I call them “the four Is.” Read More »

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To understand IFRS 9 challenges, start with a shared language

505727553For banks across Asia and Europe, a new accounting standard is of increasing importance – IFRS 9. With the first IFRS 9 reporting deadline looming January 1, 2018, banks are trying to understand what they need to do to be ready.

At its core, the IFRS 9 accounting standard introduces a new approach to calculating impairment allowance of financial instruments, now based on expected credit loss (ECL) modeling. This will have a significant impact on the way banks account for credit losses on their loan portfolios.

Recently, I participated on a panel via webcast with other IFRS 9 experts to discuss what banks need to focus on to meet the 2018 deadline. The good news is that all of us on the panel felt IFRS 9 challenges are being taken seriously. The banking community is also starting to realize IFRS 9 implementation is more complex than originally thought, especially when connecting risk and finance. Read More »

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Taking customer experience to heart

swimming-659903_960_720When I joined SAS nearly 32 years ago, I didn’t set out to be its first Chief Customer Officer (CCO). I made it here by setting small goals for myself over the years, sharing those goals and attaining them step by step.

It’s been a lot like training for a race or a long-distance swimming event. You start by getting to the pool three times a week, then aiming for five. You focus on refining your stroke, then increasing your speed. Then you work on going longer distances and improving endurance. All with a larger goal in mind: being the best you can be, making your health a priority or leaving your big brother in your wake on race day.

At SAS, I started by helping customers learn how to get the most value out of their SAS software in Technical Support. I loved working directly with our customers. I learned as much from them as they did from me. During my time in that role, as well as my next position as a trainer in Education, I always tried to share my experiences internally to enhance our software, improve our processes and deliver a better customer experience.

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Big: Data, model, quality and variety

The “big” part of big data is about enabling insights that were previously indiscernible. It's about uncovering small differences that make a big difference in domains as widespread as health care, public health, marketing and business process optimization, law enforcement and cybersecurity – and even the detection of new subatomic particles.

But the "bigness" of your data is not its most important characteristic. Here are three other considerations when it comes to getting value from big data. Read More »

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Analytics transforming the 2020 U.S. Census

Don't let the age fool you, the Census Bureau is modernizing government. Photo by Flickr user takomabibelot

Don't let the age fool you, the Census Bureau is modernizing government.
Photo by Flickr user takomabibelot

One of our country's oldest institutions, the U.S. Census Bureau, is at the forefront of modern government efforts. Those efforts are numerous and disparate, from general directives to do more with less, to digitization and consolidation initiatives, to the “Cloud First” mandate, and the pushes for agile and open source development.

At the heart of almost all modernization initiatives is the ability to collect and parse through massive stores of data. The effective use of "big data" is driving brand-new insights in government, insights that would not have been possible without analytics technology.

Recently recognized as a finalist in the ACT-IAC Igniting Innovation Awards, the U.S. Census Bureau exemplifies the transformative potential of Big Data analytics. The Census Bureau is tasked with the unenviable task of accounting for - down to the person - an increasingly diverse U.S. population of 330 million people, spanning 140 million households. In preparation for the upcoming 2020 Decennial Census, the bureau has revolutionized its approach, using the latest technology and solutions to address challenges that have been inherent since the first census of 1790.

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Disruption from the Internet of Things: Are you ready?

Some estimates suggest that the number of connected objects will be more than 50 billion by 2020. Each of us will own between six and 10 connected objects. But what exactly is the Internet of Things (IoT)? Wikipedia describes it as “the network of physical objects — devices, vehicles, buildings and other items — embedded with electronics, software, sensors, and network connectivity that enables these objects to collect and exchange data."

From product to service: a paradigm shift?

The numbers show that the industrial sector is very much an early adopter when it comes to seeing the added value of connected objects.

The IoT, or Internet 4.0, has given industry a new way to organize production. This Internet of smart factory objects is characterized by continuous and immediate communication between the various tools and workstations integrated into production lines and supply. The objective is to make a smart factory, capable of greater flexibility in production and more efficient allocation of resources. Read More »

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