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Use Cases in Cloud Infrastructure Management

Well, with a snappy title like that,  I expect I am now all alone in this room. 😉

My cloud research this year will be focused on use cases in two areas: consumption and service. I will delve into the tasks involved, and how commercially available tooling addresses those tasks.

Consumption and Cost Management

  • Application cost performance review
  • Cost and capacity planning

Service Management

  • Service level evaluation and planning
  • Availability and fault recovery planning
  • Operations Automation

Evaluation Areas:

  • Desired outcome of the activity
  • Business and infrastructure impact of the activity
  • Roles involved
  • Tasks involved
  • What problems/aspects of the activity are addressed by a vendor solution
  • How a given solution contributes to the activity- what it does, how it works
  • Overview of tech/architecture/interfaces/data
  • Vendor’s target market, pricing, strategy

Remodeling Infrastructure Management

We are in the throes of rewriting what IT infrastructure is. The shift to the cloud changes what we pay for, how we budget and plan costs, what is costly, what can be managed, what can be predicted, how quickly systems are deployed, how easily systems are moved or replicated or recovered.

This means that we will soon be in the throes of rewriting what infrastructure management does, and how it works, and who uses it. 

We do have some inkling what to expect. The last shift in the IT infrastructure paradigm —from mainframe in data centers to distributed computing dominated by client/server—happened only a quarter century ago, and the lessons are readily available. Client/server engendered entirely new development technologies, development methodologies, operations technology —and upended how IT was controlled, budgeted, and managed.

Tools that were terrific in the mainframe environment were still useful in small ways, some of the time, for parts of a few of the problems. In other words, woefully inadequate. The replacements came from new players — think Microsoft and BMC— while established players —like IBM—were slow to catch up.  The established players thought they could bolt some distributed management onto their data center management. As it turns out, the new players eventually bolted on a comparatively small bit of datacenter management onto their vast new tooling.

With cloud, we once again face a different paradigm, a different world, that demands different tools, techniques, and opportunities. Fortunately, we can apply much more sophisticated technology today than was available 25 years ago. Machine and deep learning will save our bacon this time around.

The scale and complexity of the cloud environment will dwarf anything most of have experienced or can imagine. Humans did ok with millions of events and objects to manage, using scripts and templates. When faced with billions and then trillions, tooling made it possible to handle bundles of objects and respond only to exceptional events. But we are on the frontier of zeta and yotta scale. We will be forced to automate almost all of infrastructure management. Machines will observe, analyze, optimize and act. It will be our human job to observe, analyze, optimize and act on the machines and the models they run.

A new wave of management tooling is already emerging to replace the soon-to-be-sidelined management platforms you currently rely on. A new wave of skills should be under development: you should now be spending your time building models instead of scripts.

The Future of Machine Learning

row-of-trees-3

Row of Trees 3 by Charles Plaisted

Interview with Tom Mitchell

12/15/16

Having read Tom Mitchell’s great article “Machine learning: Trends, perspectives and prospects” published in Science in July 2015, I wanted an update. He graciously submitted to an interview.

Tom M. Mitchell is a computer scientist and E. Fredkin University Professor at Carnegie Mellon University (CMU), where he recently stepped down as the Chair of the Machine Learning Department. Mitchell, the author of the textbook Machine Learning, is known for his contributions to the advancement of machine learning, artificial intelligence, and cognitive neuroscience.

Tom foresees these developments going forward:

  • Simultaneous and synergistic training of multiple functions
  • Never-ending learning
  • Conversational agents that learn by (user) instruction
  • Collaborative learners
  • Developing understanding of uses of deep learning
  • Continued expansion of computationally intensive and huge data learning
  • Continued acceleration of ML application in industry, science, commerce, finance

Tom, ML seems to be in an explosive growth phase this year. What do you see as the trends going forward?

ML is doing great, but it is a little narrow minded. There are lots of commercial applications and successes. But 99% of what ML is applied to right now is learning a single function. You give it some inputs, you get an output prediction. For example, you feed in medical records, you get a diagnosis. You’re giving it training pairs of some function, and asking it to learn that function. It’s good to be able to predict, but prediction is not the only thing ML can do.

I think a key trend will be training many simultaneous functions. The idea is to get synergy between functions that are learning: a model learns A, which makes it better at learning B, which makes it better at learning A. We’ll  start looking beyond a single task in our application of ML, to multitask learning that will simultaneously train a system.

A second related trend is never-ending learning, where a function learns to be a better learner. Currently, for most functions, the assumption is that training is turned off at some point. Or that continued feedback improves only that single function, for example, daily retraining of a single function such as spam filter, but the model doesn’t really change.

Here’s an illustration of never-ending learning: Our never-ending language learner has been running since 2010, developing along a staged curriculum that enhances itself over time. Every day it reads more text from the web, and adds more facts to its database. It now has 100 million of those facts. Every day it learns to read better than the day before. In its earliest days, it was learning to classify noun phrases, and identify simple facts. Next, it began to learn relationships between facts to create beliefs. It now can data mine its database of facts to identify these relationships, for example, it understands that if Tom is on a soccer team, Tom plays soccer. It essentially becomes a self-trainer for additional learners. It now discovers new relationships that we never told it about, expressed in the text it is reading.  For example, it has discovered the relationship “clothing worn with clothing” f(hat and gloves), “river flows through city” (Thames and London), “drug treats disease” (statins and high blood pressure). And then it looks for more examples for these relationships.

The challenge is, how do you organize or architect an agent so that the more it learns about, say, reading, the better it is at say, inference. And, the better it is at inference the better it gets at reading. I think in future we are going to see many more scenarios where ML is used in this never-ending learning construct. It seems obvious that self-driving cars need this paradigm. Or light bulbs equipped with what’s essentially cell phone functionality, that could learn about the room they are in: if someone has been lying on the floor for 10 minutes, is that typical or  anomalous?

I also expect to see the development of conversational agents that learn by instruction. Now that computers can do speech recognition, ML can take us beyond the current state of human-computer interaction. ML conversational agents will be taught by user speech, for example, “Whenever it snows at night, wake me up 30 minutes early.” The agent might then ask, “How do I know its snowing?” and the user could instruct it to open the weather app and look at current conditions. In this way, every user effectively becomes a programmer, without having to learn a programming language.

I expect to see ML open up to take on learning that is more like what humans do. Never-ending learning is still pre-commercial, but even so, our language learner is communicating with another never-ending learner, Abhinav Gupta’s image learner. Collaboration among such learners could lead to a distributed world-wide knowledge base, like the web, but understandable to computers as well as people.

The widely discussed current trend toward computationally intensive and huge data learning just keeps pushing the boundaries of what’s possible. Efforts toward better computing enable our progress, for example, new processing units such as TPU (Google’s Tensor Processing Unit) that make massive data calculations much faster.

TPU was developed in support of deep learning. Deep learning itself is the most important development in ML in the past 10 years.  It has led to dramatic improvements in learning capabilities, especially for perceptual problems like vision and speech, where it has revolutionized those fields.  Many feel deep learning is currently overhyped.  Maybe it is, but it nevertheless is the most exciting development in machine learning, and I think it will continue to progress and surprise us for many more years.

Here’s a research trend that I see accelerating: ML as an assistant for scientists. For example, in genome projects, ML finds patterns at a rate and scale humans can’t achieve. For the past decade, neuroscientists have been using ML to analyze imaging data, to decode neurosignals. I think there is a big opportunity for algorithms that could learn from the many data sets that are out there. An understanding of the brain can’t be learned from single experiment. There are thousands of published experiments, but so far, no one has found way to jointly analyze them. ML could tackle that problem. Also, in the world of ML-provided text understanding and information extraction, a science assistant could read journals for you, then extract relevant information from both the text and the experimental data associated with the article, and help you understand its relevance to your hypothesis and data. I’m describing a template that could be used in many other applications.

Finally, we are beginning the second decade of an explosion of ML, with accelerating progress and expansion of use. Decade 1 will be as nothing compared to the decade to come. There is a huge increase in the number of people and institutions working in ML. The resources devoted to ML by finance and industry are huge, dwarfing historic academic and federal funding. We are really just at the beginning of seeing the impact ML will have on our world.

Tom, what didn’t happen, that you had expected?

I kept thinking this would happen and it hasn’t: explanation based learning, which is like human learning. For example, you have a deep network and you want it to learn to play chess. One way to learn is to run a million games and see which ones you win. This is how the Go champion was defeated. This is very un-human learning. We humans like to find explanations for why things go wrong. “I lost my queen because I had to move my king to safety. That’s the last time I put both king and queen that close to a knight.” The explanation only mentions three pieces, not all the pieces. I, a human, can generalize from just one example, if I generate an explanation to determine what went wrong and why., instead of a zillion examples and statistics. Not every chess piece in every position is equally important (which is the initial statistical approach). Explanation-based learning can create a less-data intensive approach. But, I’ve been waiting 20 years for what I think should be this big trend. Meanwhile simpler algorithms applied to bigger data sets with faster computers weaken the motivation to pursue this.

Evolution to Personalization: 3 Maturity Levels

How will you mature your digital marketing?

If you expect to excel in your market via superior customer experience, targeting, or personalization, you need a culture of optimization – measuring, improving, and predicting.

The strategy of using audience data to improve customer experience and optimize results has become this decade’s gold rush — for marketers and solution providers.The underpinning of that strategy will surely involve the technologies that come under the umbrella of optimization. 

When you’ve reached that step, you need to take the next quantum leap: a culture of personalization, embracing content strategy and curation, and automating the delivery of the right audience experience using prediction.

I attempt to explain the maturation via this prezi: (if you are new to prezi, you click “start prezi” and then use -> to move thru it; close your eyes if you get motion sickness…)

 

 

 

 

 

 

 

 

 

 

 

 

3 Foundations for Personalization

“Personalization” online has its roots in the mid-90’s, when industry leaders such as HP and Wells Fargo had big buttons on their home pages, “PERSONAL” and “COMMERCIAL.” From today’s perspective, that’s pretty lame: those categories represent myriad audiences and personas with very different needs.

To meet today’s customer expectations, marketers need to recognize dozens, hundreds, eventually thousands of audiences. And then design and deliver the best possibe content to each of those audiences.DSC04216.JPG

Three audiences is about as many as an individual can manage.

 

You can’t do that without a lot of data gathering, predictive intelligence, and great content. And you don’t get those without a rich conent library, tools that automate analysis, prediction, and content selection — and a culture that will allow the tools broad scope to do so.

Here’s what the leaders who are delivering effective personalization have:

Content

  • Content that ranges from images to ads to articles to ebooks, to fit every major audience, at every step of interaction
  • A content strategy that guides the development and evaluation of content

Culture

  • Every opinion as a hypothesis to be tested – and insists on experimenting and testing to learn about audiences
  • Culture that wants to create content to support myriad audiences
  • Culture that recognizes data driven prediction will outperform human opinionated prediction
  • Culture that recognizes the transitory nature – and value – of audiences

Tools 

  • Easy to create, manage and evaluate experiments
  • Easy to create, manage and evaluate content
  • Analysis that is consistent across marketing tasks, filterable, and relates to business goals

 

Digital Transformation: Turnaround at Malaysia Airlines

[with co-author Patricia Seybold, CEO Patricia Seybold Group]

Leaders in digital transformation foster a culture of experimentation, customer experience management supported by mature optimization programs, and measurements relevant to their goals. They demonstrate how an integrated platform, skilled people, and mature optimization capabilities are the keys to success.

One such leader is Dean Dacko, SVP of Marketing at Malaysia Airlines, who recognized that the company needed a new digital core and needed to embrace a whole new way to engage with customers.

As a result of his efforts, Malaysia Airlines doubled its Facebook followers, doubled its site visitors, and tripled its online revenues in 14 months.

Then, with the disappearance of Flight 370 on March 8, 2014, the entire airline company, including the marketing team, had to react nimbly to the mysterious tragedy of the missing Boeing 777. And, again when Flight 17 was shot down over Ukraine on July 17, 2014, the marketing team used the same crisis management process to respond. The digital platform that Dean Dacko had put in place was a vital asset.

Recapturing Market via Digital Transformation

In 2011, Malaysia Airlines began its digital marketing transformation. The company was far behind competitors in customer experience, marketing, and profitability, having underinvested in marketing for many years. The loss of customers and revenues and a net loss of two billion ringett (roughly USD 600 million) finally convinced executives that the company faced a crisis, and that incremental improvements to the business would not save the day.

With only two months cash in the bank, it was clear that more spending on TV advertising was not an option. “We needed to embrace a strong digital platform and approach. There is a massive emerging digital environment for how consumers engage and create relationships with brands. We needed a new digital core, and to embrace a whole new way to engage with customers,” observed Dean Dacko, CMO, who joined Malaysia Airlines in October, 2012 from Aimia, a Canadian loyalty marketing company.

Results

As of 2014, Malaysia Airlines had a highly engaged audience, with a million Facebook followers, double that of a year before. It had 2.5 million Enrich loyalty program members. Internet revenues were more than 7 million ringgit (roughly USD 2 million) per day.

Success Goals for Malaysia Airlines’

Digital Transformation in Marketing

Goals Results
Consistent Customer Experience Increase conversion rate RM 1.4 Billion (Malaysian ringgit) incremental sales in 12 months
Revenue/Online Revenue Double conversion rate in 2 years Drive 35% revenue online 3x internet revenues; 40% more passengers; 2x market penetration
Digital Marketing Effectiveness Leverage information; Integrate the loyalty data 2x Facebook followers; 2x site visitors; 3x online revenues

First Challenge: Resources, Skills, Practices

Transformation started with creating a marketing organization and a strategy. Dean Dacko had just come on board and found he had nearly a blank canvas; there was no brand marketing team, and only small teams managing promotions, operations, and loyalty. Their efforts had been tactical, with no overarching plan or vision. He brought these groups together to form his nascent digital marketing organization. Dacko explained in a March 2015 interview with Robin Hicks:

“The reality was that consumers in Asia had rapidly shifted in a world that had gone social and mobile,” “We needed to position ourselves better to take advantage of that, and engage with our audience where they had moved to.”

Dean Dacko, In mUmBRELLA Interview with Robin Hicks

His immediate challenge was to convince the management team to commit resources. Executives were attached to traditional views developed over their quarter century at Malaysia Air, and reluctant to change. They weren’t familiar with the rising importance of marketing, especially digital marketing. They weren’t familiar with benchmarking or modern practices for marketing. In fact, the team didn’t really understand or believe in marketing. Dacko had a big education task, all through the organization. In Dacko’s words, “Marketing was still regarded as witchcraft.” Tellingly, the chairman’s statements to investors in 2012 mentioned branding in terms of the logo on the new A380 fleet.

In order to deliver results rapidly with his new organization, Dacko needed to rely on partners and align with best practices. He turned to Adobe, Google, Facebook, and Linkedin for best practices and resources.

Unified Platform

The new organization’s strategy and business plan required a new operating platform that would encompass all marketing activities with a central focus on Social CRM. Malaysia Airlines has 16 country sites with local language, content, and people, all under one URL.

His immediate challenge was to convince the management team to commit resources. Executives were attached to traditional views developed over their quarter century at Malaysia Air, and reluctant to change. They weren’t familiar with the rising importance of marketing, especially digital marketing. They weren’t familiar with benchmarking or modern practices for marketing. In fact, the team didn’t really understand or believe in marketing. Dacko had a big education task, all through the organization. In Dacko’s words, “Marketing was still regarded as witchcraft.” Tellingly, the chairman’s statements to investors in 2012 mentioned branding in terms of the logo on the new A380 fleet.

In order to deliver results rapidly with his new organization, Dacko needed to rely on partners and align with best practices. He turned to Adobe, Google, Facebook, and Linkedin for best practices and resources.

Unified Platform

The new organization’s strategy and business plan required a new operating platform that would encompass all marketing activities with a central focus on Social CRM. Malaysia Airlines has 16 country sites with local language, content, and people, all under one URL. Adobe Marketing Cloud provides the technology to support all the capabilities and data to support complex campaigns, social efforts, and loyalty programs. It provides the technology to support all the capabilities and data to support complex campaigns, social efforts, and loyalty programs.

Wisdom

Dacko’s view of the critical steps in the digital transformation journey:

  1. Create A Strategy And Business Plan, And Get The Financial Commitment. You need infrastructure and technology to power digital marketing. Moving in a new direction requires substantial resources from the CFO, but the payback can’t be substantiated. The temptation is to invest a little—but this is hugely dangerous. You can trash your brand in 20 minutes by not responding to a Tweet or Facebook post. Keep in mind that this is an on-going effort: you are never done. If you needed $10 million to build your capabilities, you’ll need $5 million to keep up with rapidly changing markets and customers.
  2. Clearly Communicate Objectives, Roadmap, And Results. This is a team effort, not only within the organization, but also with agency and technology partners. You need to constantly review the game plan with the team to answer these questions: where are we, where are we going right now, and are we still on track?
  3. Rely on Partners. Partners have the knowledge and tools to accelerate your progress. You won’t have the resources in house, and it is too hard to find the talent. Partners will bring the talent to cross-pollinate your team.

How Malaysia AirlineS’ Marketing Coped with two Back-to-Back Disasters

[Editor’s Note: This more recent section of our case study is largely in Dean Dacko’s own words, quoted from the mUmBRELLA interview referenced below[1]]:

Flight 370 Disappears

In March 2015, Robin Hicks, the Editor of Mumbrella Asia, caught up with Dean Dacko at the Media Asia industry event. Robin asked:

“Tell us about the time when you first heard the news of the missing MH370 jet and how you briefed your agencies [Ogilvy & Mather is MAS’ creative agency, IPG Mediabrands handles media and Rally does social media]:”

“What happened on 8 March was one of the most widely publicised, dramatic, confusing, mysterious events in recent history. One of the words often used to describe it in the media is ‘unprecedented’. And it was.

Never before had a modern aircraft, a Boeing 777, completely and utterly disappeared. The search that followed was also unprecedented in the scale and length of the operation; 26 different countries using 100 different ships and aircraft. So was the level of public fascination. Almost every day we are in the news, with different conspiracy theories emerging about what happened. Never before has any brand or story captured so many people’s imagination.

We were made aware that flight MH370 had gone missing at 5.30am on a Saturday. By 9am, I’d given the direction to take down every Malaysia Airlines media property worldwide.”

Dean Dacko, CMO, Malaysia Airlines from Robin Hicks’ Interview

How Marketing Reacted to the 370 Disaster

Dean Dacko describes the initial steps taken by his marketing organization and their marketing partners, immediately after the July 8th Flight 370 disappearance:

 “On Monday at 9am, I convened a meeting of all our agency partners and all my team with the objective of how we would rebuild the brand.

Taking everything down was easy. Building it back up was going to be much harder. But we had no choice. When flight cancellations happen and advertising is taken off air, the financial impact is devastating for an airline.

Our job was to restart the commercial engine and find a way to make money – otherwise the company would have collapsed. There was no other way. We had to do it. We had to be successful.

One of the nice things about the process was that, from the first minute, there was universal sense of partnership. As much as it was a blow for us, it was also felt by our partners.

In the meeting, I said to the 50 people in the room: ‘What we do from here and how we manage the recovery from this will measure us and define us as a brand and as individuals. In your career you’ll never see anything like this. But how you deal with this will define you and us for many years to come.’….

Everything happened in an era when people can share information, ask questions and challenge a brand in an instant. As a marketing and communications challenge, it was huge. It was like a mushroom cloud of attention – a bright white like was shone upon us. We were totally exposed. And it did not help that the media was reporting anything, regardless of source or no matter how crazy, just because they had to report something.

“When that sort of thing happens, brands tend to freeze. Whichever way you move, you’ll be criticised; it’s paralysing. But the worst thing you can do is not move.

We used some of the tools we had created in the months prior. One was our web platforms. Before the beginning of 2014, we had one English language website. But we had created 22 different country sites, each with their own currency and own content. This gave us the ability to engage with people, supported by agency teams around the world, in local languages and with content relevant to them.

We took the 22 different sites and colour coded them – red, yellow and green – as part of a process we called “analyse and adjust”. We looked at the comments that were coming through in real time, and gauged what we should do based on that sentiment. If the colour was red, it meant stop all marketing. If it was yellow, we’d slow things down and continue with caution. If it was green, we’d keep going as normal.

We also had a business continuity plan for marketing in four different phases – from blackout to recovery. In the blackout phase, we stopped doing anything commercially linked. In the recovery phase, we had returned to normal.”

Dean Dacko, CMO, Malaysia Airlines from Robin Hicks’ Interview

Lessons Learned from Responding to the Flight 370 Disaster

What did Dean Dacko, his marketing team, and partners learn from coping with the aftermath of the Flight 370 disappearance?

 “The first lesson from MH370 was that, in the digital world, the expectation of the audience is immediacy. They want to know now. In real time.

In traditional crisis management, the opposite is what is desired. Most of the way these plans are articulated is driven by lawyers – what you should say, who would say it and how often is a communications protocol meant to mitigate against civil liability. The overall direction was to say as little as possible as infrequently as possible. The idea was to let time go on, and say at little as possible, so they could not hold you liable for anything you have said during the crisis.”

“But, in a world that wants immediate answers, we realised that was absolutely the wrong thing to do. So we established the capability, after consulting with our legal team, to be able to comment immediately where appropriate. If something was known to be true, could be validated 100 per cent or was already in the public domain, then we could comment on it. Within that context, if someone was expecting an answer from us, we could respond immediately.

We were able to demonstrate that if we managed the situation by being engaged, our ability to manage the story and the brand became so much easier. And it worked.”

Dean Dacko, CMO, Malaysia Airlines from Robin Hicks’ Interview

The Flight 17 Disaster

How did the experience of dealing with the disappearance of Malaysian Airlines’ flight 370 affect the marketing department’s ability to deal with the second tragedy: the shooting down of Flight 17 over the Ukraine four months later? Dean Dacko explained to interviewer, Robin Hicks:

“With MH370, to go from [marketing] blackout to recovery took seven weeks.

With MH17, it took seven days.

This was driven by the fact that those two events were completely different. But also because we had learned so much more about how to deal with a situation of such magnitude the second time around.”

Dean Dacko, CMO, Malaysia Airlines from Robin Hicks’ Interview

Biggest Mistake

What was the biggest mistake that Malaysian Airlines’ marketing team made during that double crisis period? Dean Dacko admits that Malaysia Airlines’ now infamous “Bucket List” promotion was in very bad taste.

“It’s not an excuse. But the reality was that, any word we published would be reacted to in some way.

The bucket list was a promo designed months before MH370 and MH17 and was never meant to be advertised that way. We did not get a single customer who said it was a problem. It was the media that suggested it was an issue.

It’s never the case that everything will go 100 per cent how you expect it to. What is critical is how you deal with it. That’s what I believe we’re measured against. Within minutes of recognising that we made a mistake with the bucket list promotion, we reacted in the best way we could [the promo was removed from MAS’ website]. We were under a global spotlight. Should we have been scrutinised any closer as a brand? Probably. But at same time, it’s pretty hard to be perfect.”

Dean Dacko, CMO, Malaysia Airlines from Robin Hicks’ Interview

Rebuilding Trust in the Brand?

The most common question Malaysian Airlines received after the double-whammy was “how can you survive as a company?,” according to Dean Dacko. He responded this way:

“When MH17 was shot down, the feeling within Malaysia Airlines was universal shock. It was like taking a punch in the stomach. We were completely winded; 20,000 people suffered a big blow.

So, from a marketing perspective, we decided to send a message to ourselves internally – that was #StayStrong. It was intended for our own people, but it went viral.”

“People were posting back to us, saying yes, Malaysia Airlines, stay strong, you didn’t deserve this.

We took that and we moved on to ‘Fly high’ and ‘Keep flying’. It has shaped our new direction. We recognised that it was the vehicle to get our message out, and to do so in an authentic, truthful way that leveraged a shared sense of grief and loss, together with a determination to carry on.

We felt that our customers were saying, I’m still with you, I still trust you. And we said, from a commercial standpoint, we’re going to honour that sentiment and we’re going to offer pricing and promotions to reflect that commitment, with the same Malaysian hospitality that we’re known for.”

Dean Dacko, CMO, Malaysia Airlines from Robin Hicks’ Interview

Or Rebranding?

Dean Dacko’s contract as SVP of marketing is nearing its conclusion, but he feels he still has a big job to do. The company has a new CEO. Since January 2015, Christoph Mueller, who is credited with turning around Aer Lingus has taken over the reins of this government-owned airline. As of the time of his March, 2015 interview with Robin Hicks, Dacko had not yet had a discussion with the new CEO about the need for rebranding and the future marketing direction. When Robin Hicks asked Dean about rebranding, he replied:

“There are two elements to this. First is the awareness of the Malaysia Airlines brand. Prior to MH370, globally Malaysia Airlines’ brand awareness was in the low single digits. But after MH370 and MH17 it is 86 per cent worldwide. The name is now in the range of Coke and Pepsi. That kind of awareness takes decades and billions of dollars in investment to build. To abandon that, from a commercial marketing perspective, would be a tragically bad mistake to make.

Secondly, millions rallied around the brand and embraced the notion of Fly High and Stay Strong. So much so, that if we were to rebrand, we would not be honouring that message, and we would not be leveraging that as a springboard.

And if we rebranded, what would that say about the company? Malaysia Airlines has always been recognised as a premium full-service carrier and a national icon. The prime minister has said that this is something that needs to be preserved, as it is part of the fabric of Malaysian culture and society. What makes us good, what is engrained in our character and our culture, is Malaysian hospitality. It’s one of the only things that makes us genuinely different as an airline. It’s what makes us who we are. And we wouldn’t want to disrupt that promise.”

Dean Dacko, CMO, Malaysia Airlines from Robin Hicks’ Interview

However, in the press release announcing Mueller’s appointment, Malaysian Airlines talks about the creation of “NewCo” by July, 2015. And, in an internal memo in early May, Mueller informed the employees of Malaysia Airlines that he would be cutting the staff by 6,000 (from 20,000). “Sometimes you have to retreat and regroup before growing again. And that is the ultimate target. We want to grow again in the last phase of restructuring,” he said. He also said that Malaysia Airlines is “suffering badly from a heavily damaged brand reputation” in key markets with many people avoiding the carrier because “they are frightened.” This was born out on May 11th, 2015, when an unruly, intoxicated and very large passenger caused such a disturbance on Malaysian Airlines Flight 179 from KL to Columbo that the flight circled and eventually returned to the Kuala Lumpur airport, unable to continue its planned flight. This incident caused a large uproar on Twitter, with tweets like this one from Ayien@nurulazreen: “Let us all take a minute to pray for #MH179. Please give us good news this time. Hope everyone is safe. Land safely.”

Digital Transformation Leader: Suncorp Group

Leaders communicate the path; followers must interpret. 

Leaders in digital transformation foster a culture of experimentation, customer experience management supported by mature optimization programs, and measurements relevant to their goals. They demonstrate how an integrated platform, skilled people, and mature optimization capabilities are the keys to success.

One such leader is Murray Howe, Executive Manager of Digital Strategy & Innovation at Suncorp Group. Recognizing the need to adapt to changing customer needs and expectations, and the vital importance of digital transformation to achieve the desired results, he identified five necessary cultural changes necessary:

  • Integrated platforms
  • Customer knowledge
  • Using data assets
  • Consistent customer experience
  • Continuous improvement

Suncorp Group’s efforts has yielded impressive results: the group’s sales in the personal insurance business now start online 70 percent of the time and uptake of the mobile banking app exceeded 20 percent of customers within 6 months.

Note from the editor: Sue Aldrich’s case study on Suncorp Group is reprinted here (with minor updates) with permission from research commissioned by Adobe Systems, Inc.

Suncorp group’s digital transformation

Evolving Customer Expectations

Suncorp Group is a conglomerate of 15 insurance and banking brands in Australia and New Zealand with nine million customers. It is structured so that each business’s results are transparent to investors. Senior management has been focused on operations, solving business problems, and executing business and operations plans, but in recent years has recognized that the customer must be central to focus, strategies, and plans. Suncorp can control changes to its own business operations, but it must react to changes to customer needs and expectations. The organization realized it needed to become agile and adaptable in order to meet evolving customer expectations, and that digital transformation is the heart of this evolution.

Digital Strategy Goals

Suncorp’s digital transformation, just four years along, has made great strides in establishing a unified digital platforms used by all businesses; streamlining some customer experiences resulting in a dramatic increase in sales; and shifting focus from operations to customer needs.

The digital strategy leads this transformation. Murray Howe, Executive Manager of Digital Strategy & Innovation, describes five broad cultural changes necessary to support Suncorp’s digital transformation:

  • Integrated Platforms. The lines of business need to adopt common platforms and become proficient with them. At Suncorp, there is one technology business serving all companies, and a single digital team supporting three dozen or so web front ends.
  • Customer Knowledge. Each core business must embrace the shift from optimizing channels to understanding customers. This effort has been underway for about three years, and capabilities are not yet mature.
  • Using Data Assets. The organization must also learn to unlock the value of data, which means shifting its focus from transaction data to interaction insights. In FY2013 there was broad recognition that data is a strategic asset that can be managed and valued better.
  • Consistent Customer Experience. Each business needs to design and deliver continuous or consistent customer conversations. Remembering a conversation across channels and sessions should influence future conversations. Since the various Suncorp businesses share customers, new practices for leveraging the customer asset across organizations are evolving. Rather than think in terms of success in advertising and attracting, marketing teams are starting to think in terms of service, sales, and customer experiences. In one of Suncorp’s markets, improved customer experience has contributed to quadrupling of online sales, and an additional 70 percent of sales now start online.
  • Continuous Improvement. Continual improvement and experimentation need to be embedded in the culture, capabilities, and practices of every business. Conversion rates in one of the businesses have improved between 10-20 percent, year-over-year (YOY).

Unified Platforms and Data

During the first three years of this digital transformation, Suncorp established a common, unified platform for marketing and customer experience, as well as building skills and practices. Suncorp lines of business each have marketing organizations supported by a shared IT services division. In the past, lines of business invested to achieve their own goals without considering the impact on the rest of the Group. It is not surprising that there were multiple independent platforms and databases that must be merged and replaced. Today, the marketing organizations recognize that only common platforms can deliver the scale and agility they will need to be successful, and to make best use of skills and investment.

Maturity Model

Howe believes they have achieved the first stage of maturity, according to a model he has developed, and are now focused on the second. He sees a big risk in underestimating the difficulty of reaching the next level of maturity. The environments for marketing, business information and customer interaction need to merge, and merge across lines of business. How do you replace technology and develop new skills and practices, without bruising your business? Who leads deployment of new capabilities—marketing organizations or IT?

Howe’s maturity model for being able to deliver the right interaction, for the right customer, at the right time, on any channel has these four stages:

  1. Tracking and measuring. Click and campaign tracking; standard metrics
  2. Benchmarking, analytics, optimization; segmentation, retargeting, path analysis, automated reporting
  3. Advanced segmentation and integration. Personalized content, integration with channels and across devices; cross-channel path analysis and targeting
  4. Machine learning; single customer view with third party data enhancement; outbound predictive targeting

There are 21 capabilities in Howe’s model, and each business has competency scores for each capability. Business initiatives are mapped against the model to assess maturity required vs. maturity currently achieved, and roadmaps are developed accordingly.

Howe’s aim is a pyramid of technology and capabilities. “If the foundation blocks are weak in capability, the next layer will be weak. The common denominator is data accuracy, data integration, and data knowledge.” Integration and simplicity are more important than best of breed tools, because the market changes rapidly and the unknowns are both internal and external.

Making the technology core as simple and adaptable as possible, with widely used tools and integrated platforms, will make Suncorp more agile. Suncorp chooses partners who have a similar vision, even if their products don’t yet provide all the required features.

One such partner is Adobe. With Adobe Target, Adobe Analytics and Adobe Media Optimizer already deployed, Suncorp is investigating Adobe Marketing Cloud to provide a common core for marketing. For such a broad set of capabilities, Howe envisions implementing for a single brand, and then rolling out to others in baby steps as business demands.

Skills and Practices

As Suncorp invests in unlocking the value of data, and in digital marketing, skills are the key. These skills are sourced internally in part because of the scarcity of experienced applicants, and in part because business knowledge is so important. In Howe’s view, the overarching requirement for staff development is learned rather than bought capability.

Experimentation

Experimentation and innovation are crucial to the future health of a company. But it is hard for an organization that is operationally focused—and accomplished—to learn how to incubate. You need to carve out time, money, and staff to experiment and learn and fail. Howe cites the 70/20/10 model of learning and development as a useful tool for helping to focus effort and resources on capability change. In this model 70 percent of resources are dedicated to core business activities; 20 percent is focused on bringing new capabilities to scale, and 10 percent is focused on experimentation.

Experimentation and innovation are crucial to the future health of a company. But it is hard for an organization that is operationally focused—and accomplished—to learn how to incubate. You need to carve out time, money, and staff to experiment and learn and fail. Howe cites the 70/20/10 model of learning and development as a useful tool for helping to focus effort and resources on capability change. In this model 70 percent of resources are dedicated to core business activities; 20 percent is focused on bringing new capabilities to scale, and 10 percent is focused on experimentation.

Wisdom

Howe relies on his maturity model to formulate his investment plans. “You need to have a maturity model and a roadmap, and understand where you are. This tells you the two things you need to know: what initiative should be next, and how are you enabled with the capabilities to do it.”

“We move forward with repeated quick, small wins, with eyes on a grander plan,” says Howe. While he is gun-shy about huge projects, he is also careful not to compromise the integrity of his platform by accepting the wrong quick wins. A cheap, simple tool that satisfies one need for one line of business will in the long run cause great expense and complexity, and impede the organization’s agility.

“One of best ways to experiment and learn is to be organic. You don’t need the CEO’s permission to start.”

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