Celent Seeks Nominations For Model Bank Awards

Dan Latimore, Celent SVP, said that after attending multiple conferences, including Sibos and Money2020 back to back, not to mention Finovate earlier in the autumn conference season, the Celent team remained coherent and was able to define some conclusions.

 

Now Celent is looking for nominations.

“I’m excited about the initial response to our Model Bank Awards (see below for details on how to submit). Last year we had over 150 submissions, half again as many as 2016, which was itself a record year. Our hypothesis: banks, who’ve historically been very shy about trumpeting their technology successes in any detail, now see that they need to demonstrate to their stakeholders – investors, management, and employees – that they’re being innovative. Winning a Celent Model Bank Award is a great way to do that.

“For 2018, we are again accepting nominations in five categories: Customer Experience, Products, Operations and Risk, Legacy Transformation, and Emerging Innovation , although if you’re not sure where your initiative fits, just take your best guess – we’ll be happy to slot it in appropriately as we assess the nominations.”

Send nominations to Dan through the Celent contact form or Twitter…

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Big Data = New Oil — What’s That Even Mean?

During Teradata’s annual Partners conference in Anaheim, CA toward the end of October an executive  almost inevitably referred to big data as the new oil. Antony Peyton, deputy editor of London-based Banking Technology asked what that meant, which led to a certain amount of inconclusive rambling discussion.

As a college friend said long ago, the only thing worse than reasoning by analogy is reasoning by bad analogy.

The analogy of big data and oil has apparently been around since 2006, much to my surprise.

For example, marketing commentator Michael Palmer blogged back in 2006: “Data is just like crude. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc., to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value.”

Steve Brobst, chief technology officer at Teradata, said he is more interested in using big data in areas like health care to see if it is able to predict when someone is heading to the hospital.

“That’s more interested than selling stuff.”

Teradata 2017 6 622

Steve Brobst, CTO of Teradata

A health expert predicted heart attacks could become obsolete within a few years because sensors and analytics could detect changes days ahead, providing time for treatment before an attack.

In 2012 Ann Winblad responded to a CNBC question about the next big thing by saying “Data is the new oil.”

Big data is also Google and Facebook selling their users to Russian info warriors who are intent on disrupting American society. And it’s Equifax collecting details on American individuals and businesses and then allowing it to be hacked

Jer Thorp argued in HBR in 2012 argued Big data is not the new oil. “Information is the ultimate renewable resource.”

We have already seen “data spills” happen (when large amounts of personal data are inadvertently leaked). Will it be much longer until we see dangerous data drilling practices? Or until we start to see long term effects from “data pollution”?

Niraj Dawar in HBR last year wrote :

“The questions that need to be asked of big data are not just what will trigger the next purchase, but what will get this customer to remain loyal; not just what price the customer is willing pay for the next transaction, but what will be the customer’s life-time value; and not just what will get customers to switch in from a competitor, but what will prevent them from switching out when a competitor offers a better price.”

 

 

 

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To Compete, Companies Need To Use Data Better

Corporations have to decide what they want to be when they grow up, said Oliver Ratzesberger, EVP and chief product officer of Teradata. They need to learn how to incorporate data in their corporate strategy and decision-making, added Ratzesberger, co-author with Northwestern University professor Dr. Mohan Sawhney of a new book, “The Sentient Enterprise”,

The Sentient Enterprisewhich looks at how leading companies are doing just that. Their examples include Wells Fargo, Verizon, Dell, Siemens and General Motors.

“We wanted to put concepts of data agility in the hands not just of top executives, but any business user who interacts with data and wants to improve that interaction,” Ratzesberger wrote in a blog post.

Ratzesberger, who was a leader in eBay’s pioneering use of Teradata, said that incorporating data into the core of a corporation’s takes time and C-suite commitment

“Mohan and I are trying to advance an idea where data and analytics can do more than just act as a bean counter of what’s happening within a company . The sentient enterprise actually does some of the understanding itself and takes on aspects of operational decision-making, freeing the human mind to focus on high-level strategic analysis and creativity,” he wrote on Teradata’s Forbes page recently.

Disruptive technology won’t succeed if executive protect their profitable business from the potential change said Ratzesberger.

“Too many executives are telling teams not to cannibalize their high margin business,” he said during at interview at the Teradata Partners conference. “That leaves a company open to disruption from the outside.”

He likes P&G as an example of a company that is using technology to get closer to customers, although the only example he cited was an electric toothbrush that links to a mobile phone and can show a user which parts of his mouth he is neglecting. Apps and links to phones can help even a company that sells through retailers to connect directly to customers more effectively than trying to track them with coupons. A big wholesaler like P&G didn’t have direct customer data for analytics 10 years ago and has recently faced startling competition from such innovators as online razor blade sellers.

Oliver sees an organizational issue here…a company has to pay attention to its culture, its people, and process change and learn to become agile at scale, with governance built in. They also need to think long-term — 5 to 10 years out — to build sustainable change.

The Wild West works — for 30 to 90 days — and then crashes down like a house of cards, he added. “We talk to C-level executives and ask how they are thinking about their roadmap and disruption in their companies.”

He said they need “faster collaboration, learn to build at scale and get algorithms which will change business processes such as supply chain.”

When companies are faced with exabytes of data, they need to to something smart.

“At eBay, where the company had 800 analysts there was still too much data and we would miss changes in the market.”

Fortunately new capabilities are coming together, he added.

“Most corporations aren’t ready for data — they have silos and data drift. They often argue and can’t agree on even basic data such as their number of customers.”

Leading companies have learned what can be done with data such as Kaizen, Six Sigma and Lean to predict certain outcomes.

“We’ve learned in the last decades…that a you can predict certain outcomes very well.”

For Maersk, the huge global shipping company, when engines break at sea it is a big problem.

“With enough sensors you can predict failures and change pistons while the ship is in port.”

Artificial intelligence (AI) is a popular term these days, but Ratzesberger warned that the intelligence is only as good as the data, citing that old warning: Garbage in, garbage out.”

Chief Data Officers

In a corporation, “Chief Anything” doesn’t amount to much, Ratzesberger said.

“You see Chief Data Offices everywhere; the big new title is Chief AI officer. But
Chief whatevers are powerless offices; they are not Level 1. They are below the CIO or CFO. Many companies lie to themselves when they have a CDO who can’t change anything — it just turned into a blame game…they’ll just blame the CDO. The CEO needs a person who works directly for him and can make decisions [based on data] that may be disruptive. Boards around the world need to challenge the CEO on what they are doing with data, it is often just a check-the-box exercise.”

For company, becoming data-driven is a journey, he added.

“GE is getting it, Siemens knows they have to disrupt themselves. There are new kinds of companies that are based on this — banking, telecom, retailers — are starting to wake up. Technology is pushed by Walmart, they know they need to do things differently, often their tech leadership sits in Silicon Valley. I think most companies get a B- at best. eBay was great; now it is a legacy company. “

“Using data well is a board-level topic — how to build the next generation platform that leverages data at its core.”

Not everything can be based purely on data, he added. People can mis-interpret that data and confuse correlation with causation.

“Companies need to define their strategy and leverage data whenever possible. Data alone won’t make a strategy.”

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Teradata Focuses On Top 500 To Leverage Scarce Resources — Data Scientists, Analysts

Teradata faces a challenge – how to grow a company when a key resource — data scientists and top data analysts — is limited.

Victor Lund, who was named president and CEO of Teradata a year and a half ago, said the company is focused on the top 500 corporations around the world.

“We limit ourselves to 500 companies because we can only deploy X number of people,” explained Lund. Focusing on the largest companies makes sense with Teradata’s capabilities. “We scale better than anyone else, and in real-time analytics that matters. We look at long-term relationships with our customers.”

The company is training its sales force in how to interact with the business users without threatening the IT buyers who have been the company’s usual point of contact. As data, organizing it and making use of it become a topic for the CEO and in many cases the board, the Teradata sales force has to adapt.

“We need to understand how to interface with the business but avoid threatening IT so they don’t think we are driving over them.”

At the company’s annual Partners conference, senior executives briefed reporters and analysts on the company and the growing understanding of the importance of data and analytics.

Data can be used for asset optimization, they said, and this refers to physical assets, not financial. As an example they pointed to Maersk, the shipping company, which has millions of containers. Sensors can show where the containers are, monitor them for changes in temperature or air pressure, and feed a database with all the information — real-world example of the internet of things (IoT). With Teradata firms can analyze anything, display anywhere, buy any way, including pay as you go, and move the data anytime from in-house to cloud at no cost.

Teradata is the only company to use the same code across all deployments, whether AWS, Azure, or on-premise hardware.

The company said its solution is faster and cheaper than a leading competitor’s. One million queries on the competition costs $605,000 and takes nine months, while on Teradata it can run in 10 minutes for $60.

Companies still have a way to go in their use of data, said Rick Farnell, senior vice president at Think Big Analytics, which Teradata acquired in 2014. Fifty-two percent of firms in a survey said they are at a basic level of analytics maturity and 41% of CIOs said data scientists, business intelligence and analytics are among their top skills gaps. Nonetheless, 80 percent are investing in artificial intelligence even though 34% said they don’t have the right in-house skills.

To help companies fill the gap in skills, and to leverage the people skills at Teradata, the company is building accelerators composed of best practices, code, IP, and proven design patterns to help accelerate deployment of AI solutions and ensure quick ROI. They include AnalyticOps Accelerator, which provides an end-to-end framework to facilitate the generation, validation, deployment, and management of deep learning models at scale. This accelerator is available now.

The Financial Crimes Accelerator uses deep learning to detect patterns across retail banking products and channels such as credit card, debit card, online, branch banking, ATM, wire transfer, and call centers. It continuously monitors and thwarts fraudulent schemes used by criminal actors to exploit the system. This accelerator is being deployed in Q4, and will be available more broadly in the first quarter of 2018.

“We’re building capabilities into the product,” said Oliver Ratzesberger, EVP and chief product officer of Teradata.

A recurrent theme at Teradata is around analytics at enterprise scale, not in a lab or running as a proof of concept.

“Companies need to embrace analytics at scale,” said Ratzesberger. “Prepare to disrupt, put outcomes into production at scale. Companies struggle to derive the outcomes they aim for.”

Part of the trouble is finding clean data.

“It comes down to a single source of the truth,” said Rick Farnell, senior vice president, Think Big Analytics. “That’s difficult if you have multiple organizations [with their own data silos] out there. You need to base everything off the right data.”

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Fidor Packs In The Clichés

The product, called Fidor FinanceBay, is an online marketplace which connects curated Fintech, InsurTech and TradeTech offerings from the wider ecosystem, to consumers, all with the aim of bringing both much closer together in an easy and value adding way. With Fidor FinanceBay, customers can easily browse financial and insurance products, as well as convenient tools, all in one place.

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Monocle’s Best 25 Cities — Metro Population and Murders Per Year

A sampling — not all the cities had murder rates listed. The ratings often included new homes built, number of museums and galleries and number of independent bookshops and miles of bike trails.

Tokyo 9.4 million people/75 murders
Vienna 1.8 million/16
Berlin 3.5 million/37
Munich 1.5 million/58
Melbourne 140,000/37
Copenhagen 600,000/5
Sydney 210,000/42
Zurich 380,000/10
Hamburg 1.8 million/15
Madrid 3.3 million/38
Kyoto 1.5 million/9
Hong Kong 7.4 million/28
Vancouver 630,000/11
Amsterdam 853,000/22

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Can Amazon And Whole Foods Solve Urban Delivery?

Amazon boxes NYC 564The scene on upper Madison Avenue, just below the Whitney earlier this summer…Stacks of Amazon boxes and padded envelopes sprawling across the sidewalk as delivery people sort through what appeared to be the contents to two trucks.

How do you deliver to apartments when no one is home, where can packages be stored at buildings with doormen? Where do you sort packages when it is raining?

Whole Foods has a contract with Instacart for home delivery in at least some cities. The NY Times recently did a story on Sinclair Browne who does deliveries in New York for the grocery store, Peapod.Amazon is experimenting with same-day or same-hour deliveries of orders.

Could it develop a database of every customer and the hours they are typically at home, coupled with current orders from Whole Foods, Amazon, Amazon Prime Pantry and perhaps dry cleaning ready for delivery?

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