Banking: Using enterprise data for business decisions at the right-time

With their extensive volumes of customer and transaction information, banks in Australia and New Zealand are leveraging their data assets to transition to more customer-centric organisations. They are focusing on the best customer experience and positioning themselves as relevant and valued providers of financial services. In doing so, Australian and New Zealand banks are leading the charge to become fact-based decision makers driven by big and small data.

Even though opportunities around customer engagement are plentiful, regulatory change and new prudential standards and guidelines are requiring increased agility to accommodate new data management, credit reporting and risk aggregation obligations.  Increased focus on addressing and responding to fraud and cybercrime in more challenging economic conditions is also top of mind for the industry.

Data on its own is not valuable. Value is only realised when organisations employ genuine and sustainable approaches to analytics and insight to generate business outcomes.  I thought it would be worth considering what SAS has seen in some recent customer use cases.

Customer data – doing good and right things
We all want to do what is good and right. There are two interesting use cases where customer data is being used to derive actionable insight to deliver valued business outcomes for SAS customers and their customers. Westpac’s KnowMe project is using customer data to better understand how to serve and interact with its customers and deliver to them, offers which are relevant appropriate and have higher levels of potential acceptance based on preferences and behaviour.  Not only are customers rating Westpac 10% higher for their Net Promoter Score but in knowing and understanding their specific needs, Westpac has attained 37% improvement in new business acceptance in branches and 60% improvement in call centre interactions. With such impressive early gains and ROI at more than double initial targets, you cannot challenge the age-old saying that knowledge is power!  Power to the customer and bank alike for good outcomes.

Commonwealth Bank is leveraging customer data for a considerably different purpose. Understanding customer behaviour from the insights gained from extensive customer transaction data can also be used for good in responding to a need to both detect and prevent unexpected and adverse customer activity due to fraud or cybercrime.

If security is not maintained, trust is the first casualty and reputational damage and regulatory intervention is likely.  Commonwealth Bank has used real-time analytics and SAS’ proprietary hybrid technology for right-time fraud prevention and detection. With rules, predictive models and neural learning brought together, they assess growing transaction volumes in both real-time and right-time at speeds exceeding 250 transactions per second and an average response time per transaction assessed of 40 milliseconds. This approach not only optimises coverage but actively assesses unexpected activity using a risk-based model with higher levels of overall coverage and lower dollar values for fraud.

Against a backdrop of exponential increases in customer transaction activity and revenue, the ROI and value to both customers and CBA – as a trusted and reliable bank from real-time detection and prevention based on actionable insight and scoring – gives Commonwealth Bank knowledge and power to meet the expectations to protect depositers and shareholders.  Knowing what is normal and what is abnormal proves the value of rich customer information.

Risk-reward remains a key focus for CROs
We all know that pricing risk should be in the DNA for all banks, particularly in today’s environment with subdued demand and lower growth rates for retail lending. Lenders must remain focused on risk-reward trade-offs and writing business which is priced right and reflects the quality and capacity for borrowers to repay. There are continuing demands from both global and domestic regulators to implement and comply with new capital adequacy standards such as Basel III. Meaning that the sourcing and sustainable allocation of funding requires increasingly sophisticated and transparent capabilities in advanced analytics to better support and manage credit and financial risks.  Optimising available capital and funds for lending purposes and attracting and retaining customer profitability over the life of the banking relationship means that risk-reward optimisation is the main game for CROs.

Seeing the right story in complex data
Making better business decisions earlier and at lower costs is what financial services executives continue to ask for as both time and funds remain scarce and markets change quickly.  Having the right information at the right time is important but to derive actionable insights which are capable of being understood is more important. New capabilities for business intelligence, reporting and data visualisation enables all available data – internal and external - to be analysed and presented clearly, accurately and reliably  for real-time insights to support decisions and create meaningful conversations.  Making complex information simple and meaningful means the time to value is reduced and opportunity for competitive advantage improved.

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Taking the big data dive with Hadoop

Demand for analytics is at an all-time high. Monster.com has rated SAS as the number one skill to have to increase your salary and Harvard Business Review continues to highlight why the data scientist is the sexiest job of the 21st century.  It is clear that if you want to be sexy and rich we are in the right profession! Jokes aside I have spent the past five weeks travelling around Australia, Singapore and New Zealand discussing the need to modernise analytical platforms to help meet the sharp increase in demand for analytics to support better business and social outcomes.

While there are many aspects to modernisation, the most prolific discussion during the roadshow was around Hadoop. About 20% of the 150 plus companies were already up and running with their Hadoop play pen. Questions had moved beyond “What is Hadoop?” to “How do I leverage Hadoop as part of my analytical process?”. Within the region we have live customers using Hadoop in various ways:

  • Exploring new text based data sets like customer surveys and feedback.
  • Replicating core transaction system data to perform adhoc queries faster. Removing the need to grab extra data not currently supported in the EDW.
  • The establishment of an analytical sandpit to explore relationships that can have an impact on marketing, risk, fraud and operations by looking at new data sets and combining them with traditional data sets.

The key challenge discussed was unanimous. While Hadoop provided a low cost way to store and retrieve data, it was still a cost without an obvious business outcome. Customers were looking at how to plug Hadoop into their existing analytical processes, and quickly discovering that Hadoop comes with a complex zoo of capabilities and consequentially, skills gaps.

The SAS /Hadoop Ecosystem

The SAS /Hadoop Ecosystem

Be assured that this was and is a top priority in our research and development labs. In response to our customers' concerns, our focus has been to reduce the skills needed to integrate Hadoop into the decision-making value chain. SAS offers a set of technologies that enable users to bring the full power of business analytics functionality to Hadoop. Users can prepare and explore data, develop analytical models with the full depth and breadth of techniques, as well as execute the analytical model in Hadoop. It can be best explained using the four key areas of the data‐to‐decision lifecycle process:

  • Managing data – there are a couple of gaps to address in this area. Firstly, if you need to connect to Hadoop, read and write file data or execute a map reduce job; using Base SAS you can use the FILENAME statement to read and write file data to and from Hadoop. This can be done from your existing SAS environment. Using PROC HADOOP, users can submit HDFS commands and Pig Scripts, as well as upload and execute a map reduce tasks.
    SAS 9.4 is able to use Hadoop to store SAS data through the SAS Scalable Performance Data (SPD) Engine within Base SAS. With SAS/ACCESS to Hadoop, you can connect, read and write data to and from Hadoop as if it were any other source that SAS can connect to. From any SAS client, a connection to Hadoop can be made and users can analyse data with their favourite SAS Procedures and Data Step. SAS/ACCESS to Hadoop supports explicit Hive QL calls. This means that rather than extracting the data into SAS for processing SAS translates these procedures into the appropriate Hive‐QL which resolves the results on Hadoop and only returns the results back to SAS. SAS/ACCESS to Hadoop allows the SAS user to leverage Hadoop just like they do with an RDBMS today.
  • Exploring and visualising insight - With SAS Visual Analytics, users can quickly and easily explore and visualise large amounts of data stored in the Hadoop distributed file system based on SAS LASR Analytics server.  This is an extremely scalable, in‐memory processing engine that is optimised for interactive and iterative analytics. This engine addresses the gaps in MapReduce based analysis, by persisting data in‐memory and taking full advantage of computing resources. Multiple users can interact with data in real‐time because there is no re‐lifting data into memory for each analysis or request, there is no serial sequence of jobs, and computational resources available can be fully exploited.
  • Building modelsSAS High Performance Analytics (HPA) products (Statistics, Data Mining, Text Mining, Econometrics, Forecasting and Optimisation) provide a highly scalable in‐memory infrastructure that supports Hadoop. Enabling you to apply domain‐specific analytics to large data on Hadoop, it effectively eliminates the data movement between the SAS server and Hadoop. SAS provides a set of procedures that enable users to manipulate, transform, explore, model and score data all within Hadoop. In addition, SAS In‐Memory Statistics for Hadoop is an interactive programing environment for data preparation, exploration, modelling and deployment in Hadoop with an extremely fast, multi‐user environment leveraging SAS Enterprise Guide to connect and interact with LASR or take advantage of SAS’ new modern web‐editor, SAS Studio.
  • Deploying and executing models - conventional model scoring requires the transfer of data from one system to SAS where it is scored and then written back. In Hadoop the movement of data from the cluster to SAS can be prohibitively expensive. Instead, you want to keep data in place and integrate SAS Scoring processes on Hadoop. The SAS Scoring Accelerator for Hadoop enables analytic models created with Enterprise Miner or with core SAS/STAT procedures to be processed in Hadoop via MapReduce. This requires no data movement and is performed on the cluster in parallel, just like SAS does with other in‐database accelerators.

To be ahead of competitors we need to act now to leverage the power of Hadoop. SAS has embraced Hadoop and provided a flexible architecture to support deployment with other data warehouse technologies.  SAS now enables you to analyse large, diverse and complex data sets in Hadoop within a single environment – instead of using a mix of languages and products from different vendors.

 Click here to find out how SAS can help you innovate with Hadoop.

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SAS users bask at SUNZ

SAS users at the SUNZ conference in Wellington

SAS users at the SUNZ conference in Wellington

With a record-high 309 in attendance at SUNZ 2014, seems every SAS user in New Zealand was at Te Papa Museum in Wellington last month for the flagship user conference. If you were unable to attend, you missed a great presentation by me and lots of good ones by everyone else.

But in all seriousness, the conference was a success, and we were honored to have a distinguished lineup of speakers from both the public and private sectors.

The day opened with Minister for Social Development Paula Bennett discussing her department’s use of SAS to protect vulnerable children. Bennett told how predictive risk modeling is being used by the state to summarize information about children quickly so frontline workers can better protect those in need.

“We found it’s possible to pinpoint which children are most at risk before harm is done,” said Bennett. For more on this story, watch SAS Analytics helps the Ministry of Social Development in New Zealand. You can also watch Bennett's SUNZ speech or read the transcript.

Next came a complimentary keynote from James Mansell, Director of Innovation and Strategy at the Ministry of Social Development. Mansell added that analytics is essential in the public sector – however, data must be shared for benefits to be fully realized. “Until we can join up data across the various organizations looking after citizens, we cannot act as effectively and deliver better outcomes,” said Mansell.

He was followed by Kiwibank Senior Economist Donna Purdue, who energized the room with news of New Zealand’s bright economic future, noting 2014 is shaping up to be a bumper year.

With the morning sessions in the bag, the group enjoyed some tea before splitting off into the various business, technology and SAS update streams. One I’ll mention was by Loyalty New Zealand Analytics Manager Vince Morder, who described his company’s use of SAS® Customer Intelligence to understand shopping patterns and increase partner involvement with its popular Fly Buys program. Another was by Carl Rajendram, National Manager of Commercial Pricing and Analytics with NZI Insurance. Rajendram delivered a passionate testimony of his company’s use of SAS® Data Quality to evaluate risk and optimize insurance pricing.

Select presentations are available on the SUNZ website.

Much like the braided streams that converge into the Pacific, attendees convened once again in the Soundings Theatre for Ken Quarrie’s locknote presentation, “The Game is Changing.” Quarrie is Senior Scientist for New Zealand Rugby, and he held the room in rapture as he showed old footage, remarking how analytics has been instrumental in helping the All Blacks prevent injury, improve player performance and lead to an overall exceptional win ratio.

And finally, it wouldn’t be a SUNZ conference without cold beers to end it – a fitting conclusion for a family of SAS users who form a close community of bright, passionate professionals – all working to make New Zealand a smarter and safer place.

***

For press coverage of SUNZ 2014, see the links below.

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Opportunity… Share, Present, Win!

Bob Whitehead (left) with Bankwest SAS Account Manager, Scott Goodsell (right)

Bob Whitehead (left) with Bankwest SAS Account Manager, Scott Goodsell (right)

The New Year brings fresh opportunities and 2014 is an exciting year for SAS users in the Australia New Zealand (ANZ) region to form connections, share ideas and get inspired! At the start of 2013, Hanlie Myburgh, SAS Customer Advocacy Manager for ANZ, announced a new incentive to encourage SAS users to present at their local SAS user group: the Best Presentation Award. This award is given to the presenter with the best presentation content determined by attendee feedback in the evaluation form/online survey. The winner receives an Apple iPod and the chance to win the MAIN PRIZE – a trip to SAS Global Forum 2014 in March, with flights, accommodation and registration expenses all covered by SAS Institute Australia. In 2013 there were 15 best presentation winners who were placed in the random draw for the MAIN PRIZE and on Friday 17th January 2014 Bob Whitehead was awarded the trip to SAS Global Forum 2014. Bob shares his experience in being a presenter at WASUP as follows:

“I have always enjoyed presenting new topics at these events. The opportunity to learn something new and impart that knowledge to other SAS customers is a great experience. The unexpected surprise of winning a trip to the SAS Global Forum in Washington DC this year is obviously fantastic.  After almost 30 years of being involved with SAS, I have yet to attend a SAS Global Forum.”

Bob would also like to “Thank SAS Institute Australia for supporting the various user community groups around Australia and providing such a great incentive for people who choose to present papers.”

Keep an eye out for Bob’s presentation on his experience at SAS Global Forum 2014 at the Q2 2014 WASUP meeting in June.

What about you?  Have you considered being a SAS user group presenter? There are many discussions and blogs on the personal and professional benefits of presenting at a local, regional or global user group. Some benefits mentioned over the past year are:

  • Presenting helps to strengthen presentation and public speaking skills
  • It allows us to share information with, and to get advice from, our peers
  • It is an opportunity to stimulate ideas through collaboration
  • It provides inspiration to others by sharing knowledge
  • It allows the presenter to seek guidance and direction in their own SAS knowledge and learning
  • It gives back to the community

These comments come from SAS users across the entire ANZ region at all levels of knowledge and experience. I am sure you will agree that presenting at a user group can be encouraging and valuable for all SAS users and students in our left-of-the-date-line community.

With the SUNZ conference in Wellington, New Zealand on the 18th February, and plans underway for the 1st quarter Australia SAS user group meetings, now is your opportunity to share the work that you have done, be recognized by your peers, and be rewarded personally and professionally for achieving your goals. And don’t forget the MAIN PRIZE, a chance to win a trip to SAS Global Forum 2015! If you are interested in presenting at a SAS user group meeting this year, let your SAS ANZ user group committee know before the presenter slots are filled!

If you are unsure about presenting and would like to discuss further with SAS ANZ user group committee members and users, feel free to start a discussion on SANZOC, our online community to complement the local SAS user group meetings within the Australia and New Zealand region through online collaboration, networking and sharing. We look forward in seeing you there…

Join SANZOC now!

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Analytics all the way!

Lights, Camera, Analytics! These three words best describe the unique experience which we had in India recently. Five days packed with customer interviews, recording insights on how they are leveraging analytics and data management to drive business outcomes, curb fraud, increase efficiencies and create a better future. Technical and business users, from organisations across Indian industries such as automobile, utilities, banking, government, education, etc., shared their views on SAS Solutions and also underlined the creativity with which they are using analytics to drive business impact.  It is clear that analytics is gaining acceptance as a key enabler of competitive advantage. Are you getting the most out of analytics?

To give you a feel of it, let me take you seventeen years back in time - When Arnold Schwarzenegger ventured on a mission to buy an action figure for his seven year old son, in the movie ‘Jingle all the way’. In the ensuing chase, he lands-up attaining much more than he ever thought and shares a delightful moment with his loved ones. In no ways, did I go out on a chase to procure a Christmas sell-out toy. However, the results derived out of this busy week was nothing less than a delight. While I was hoping that we get a chance to interact with 3-4 customers, we landed-up recording eight success stories. We interacted with customers from across Indian cities and industries. The week was packed with customer interviews, event, travel, interactions and loads of business insights. Right from the largest automobile manufacturer in India to an organisation that provides power to the commercial capital of the country to state government to two of the best B-schools in India to private banks, the week unfolded a new story with every passing day.

I wasn’t alone in this initiative, though. Bill Marriott, who’s the Sr. Director of Video Communications and New Media at SAS, travelled all the way from Cary, North Carolina to Mumbai. The week started with an interview with one of the largest private sector banks in India. The interaction highlighted how this growing private sector bank leverages analytics for curbing fraud and deriving insights from their goldmine of data. They shared valuable views on how the Indian banking industry has transformed over the years and explained the underlying importance of creating a delightful customer experience. After interviewing both the Chief Risk Officer and Head of Analytics at the bank, we ended the day with a great start to the week.

Day 2 was packed with three back-to-back interviews with the IT Secretary of one of the states in India and with two leading B-Schools in the country. The customers travelled down to SAS’ Mumbai office for the interviews. The first one to be interviewed was the IT Secretary of State Government. He talked about his experiences with data management and its importance in delivering citizen benefits. The importance of integrating data from multiple sources, removing duplicate entries, ensuring quality data and assigning unique identification to citizens. It was very insightful to learn how a technology like data management and data visualisation is empowering government to ensure that the needy citizens derive benefits of government schemes and fraud/leakages are plugged. By the time this interview was over, it was time for a heavy Indian lunch, especially for Bill. Later in the day, we interacted with senior associates from the B-Schools. This was a different experience altogether as the institutes shared how they are leveraging SAS’ analytical expertise to create business leaders of the future. They receive student admissions from varied cultural and professional backgrounds, with each student having a different career aspiration. They leverage SAS to impart MBA aspirants with a confluence of managerial and analytical skills.

Day 3, we were on the other side of the city for an interaction with a leading power distribution company. Electricity is something that we take for granted. Seldom do we think that if one machinery gets malfunctioned or one switch gets erroneously turned off, it can bring the entire city to a halt. Senior executives from the organisation talked about load forecasting and how it enables them in meeting the regulatory requirements and at the same time distribute power efficiently and save costs. They also showed us their distribution, operations and monitoring facilities. It was truly a great learning experience.

Day 4 and we were off from Mumbai to another beautiful city – Kochi. Here we interviewed the IT Head from a leading bank. He shared his views on how SAS has helped them in creation and allocation of unique customer identifications to customers and removing duplicates from customer database. This helps them meet regulatory requirements, gain a unique view of their customers, create a customer family view, optimise marketing campaigns and empower the branch manager/staff. The day not only ended with insights but also ended with an extra-large plate of South-Indian food, besides the pool.

Day 5 was a tricky one, as I had to head back to Mumbai for attending an event which we were conducting in association with InformationWeek and Bill had to fly down to Delhi to interview a leading automobile company in India. On one hand the event saw good turnout despite the bank holiday. Bill, on the other hand, conducted a successful interview with the customer. Their IT Head shared insights on how they are using SAS Solutions in order to optimise production, reduce delivery times, improve marketing ROI and derive customer intelligence.  Back in Mumbai, the event was the perfect conclusion to my action-packed week. The event saw participation from industries such as insurance, consumer goods, manufacturing, banking, telecom, oil & gas, etc. CIOs, IT heads and senior analytics professionals presented their views on upcoming trends in analytics, usage of analytics in their organisation, importance of business intelligence, data management in the age of big data, road to an analytical enterprise, and so on. To me, this was the perfect summary of the week.

Five days… multiple experiences. Experiences that reflected how organisations across different parts of the country and different industries are creatively using SAS’ expertise in analytics, business intelligence & data management to drive business objectives. Each organisation has a different set of goals and different game-plan to achieve the desired growth. Each one leverages technology for a different purpose altogether. They view technology not just as an enabler but as a secret sauce, that can be mixed with the overall business recipe to create a competitive edge. My moment of delight was not when the week ended. But, it was hidden within every interaction – especially when customers talked about the value which they derived from SAS solutions and how SAS helped them in driving business impact.

Stay tuned for a host of Customer Success Videos coming-up soon.

Click here to view a host of existing Customer Success Stories.

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The Art of Eight in Analytics

Analytics is not just about algorithms and numbers. Every analytics practitioner will tell you that there is an “art” to it – when to combine variables to extend data in the data warehouse, what options to set in the algorithm to get the best balance of accuracy and interpretability, how to define an outcome when it’s never been measured before. Although being “analytical” is a left brain concept, analytics practitioners regularly tap into the right brain for the creativity to answer these everyday questions.

But just as there is an art to doing analytics, there must be an art to explaining it, as well, particularly to those who do not have the same love of algorithms and numbers. This is Context, without which there is a disconnect between those that do the analytics and those that decide whether to action on the analytics.

Here are eight methods I’ve come across in my journeys as an analytics practitioner that anyone can mix and match to supplement the numbers.

1. Pictures
They really do tell a thousand words. If your audience is new to a concept, using a picture that can be understood without a lot of explanation (25 words or less as a guide) is an easy way to describe concepts. Google Images or your own photo albums are a great resource for this.

2. Videos
In this day and age of do more in less time, social media and easy-to-use recording software, the moving picture will always be effective in capturing the attention of an audience. Videos of less than a minute are great for demonstrating specific functionality. Longer videos can be used to tie into a story or limbic (see points 6 & 7). Have you seen the latest SAS YouTube videos?

3. Graphics
Graphics unlike pictures have standard formats e.g. arrows, processes, hierarchies. Whether using default graphics such as Smart Graphics in MS Powerpoint, Word Clouds or graphics found on the internet, the high-definition format of graphics and well defined colour palettes provide an eye-catching focus point that audiences can follow.

4. Visualisation
Tables and lists may be informative but they are rarely easy to interpret. Creating bar and line charts, plotting dimensions geospatially and using traffic lighting to differentiate severities will take less effort to explain and keep your audience’s attention longer. The interactive and attractive nature of SAS Visual Analytics is a great way of presenting complex analytical results.

5. Parameterised Reports
For presentations which need to be repeated regularly either as data is updated or for differently focused audiences, pre-defining levers which can be pulled in reports such as filters, hierarchy dimensions and cut-offs can save you a lot of time in recalculating metrics. The interactivity of parameterised reports also gives audiences more opportunity to be engaged in the presentation.

6. Stories
Why do we all remember the plot to Forrest Gump? Because it was a story most of us could relate to in some form, and though full of adventures, it had a simple “boy loves girl” plot. Using a story that your audience can identify with will clearly contextualise the analytics. For example, receiving an irrelevant offer from an organisation you have been a loyal customer for ten years, how you felt on the matter and your subsequent behaviour. If you want to tell a story visually on a single page, there is nothing better than an infographic. This visual combination of art and data can work in still or movement like in the AMEX ads on TV. Have a look at this previous SAS blog on how you can create infographics for your organisation.

The key to the success of any story though is that the storyteller (designer in the case of infographics) has a clear understanding of the objective. Without this, stories can turn out to be more confusing than informative for the audience.

7. Limbic or Themes

Having a theme run through the presentation lets an audience contextualise concepts and outcomes to the same subject. If this subject is relevant to the audience they will easily follow the presentation so either keep it specific to the interests of the stakeholder or generic to be safe. It’s important to note that themes do not work for all presentation audiences – particularly those that are only after the facts, so for these, stick with graphics, visualisation and parameterised reports.

8. Less is More
Keep the page “clean and simple”. Clean: don’t overload the screen with pictures and graphics or embed too many different attempts to explain a topic. Simple: don’t mix too many analogies lest you confuse the audience and use stories and themes that can be easily explained afterwards.

Just as the brain is made up of both left and right sides, Analytics and the ability to be creative in both its application and its presentation make up a complete equation. For an analytical viewpoint on different techniques to describe your data check out the Harvard Business Review whitepaper Visualizing Data.

These holidays, remember that Analytics can be fun… when treated with a little Art!

PS: Eight is made up of 2 zeros joined together, is an infinity when knocked sideways and is perfectly symmetric. What a beautiful number!

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Marketers must put the ‘R’ back in CRM

Let’s talk about Customer Relationship Management (CRM), but first, let’s go back to basics for a moment. Let’s ask, “How does an individual initiate a long-term, mutually rewarding relationship with another individual?”

One of the key requirements is obviously to make an effort to understand the actual and potential nature of the relationship. To do this we need to find out as much as we can about the other person’s background, and when we engage with them we must be clear about why we are doing so – what is the context of the meeting and what are the other person’s attitudes and aspirations? These are just basic principles, after all, and part of human nature.

Over the years, literally hundreds of millions of dollars have been invested in CRM systems, and all with the best of intentions. In keeping with those basic principles, organisations of all types and sizes have implemented CRM systems that promised to empower the building of relationships with thousands of customers. Interestingly, however, any number of major studies have revealed that customer satisfaction hasn’t, in fact, improved to the extent that justified the expense, disruption and effort. Moreover, we find that the consumer’s trust in the corporation’s ability to communicate effectively has actually been going backwards for many years now and often dramatically so.

Why is this? My take is that organisations have overlooked focusing on the R in their CRM vision. While marketers have invested heavily in gathering and storing customer information, together with all manner of other information to support the vision – and while they’ve also invested equally heavily in channel execution – they have so often failed to improve their understanding of relationships beyond very basic levels.

I suggest the likely reason for this failed understanding and lack of insight on the part of marketers is that it has simply been too tempting to deploy mass communication programs in one-to-one channels even though their investments in CRM should have steered them towards more tailored approaches. Perhaps that’s understandable, you might say, given that a large number of case studies have shown that those kind of communication programs are very efficient when it comes to driving short term revenue objectives.

The other reason is that understanding the relationships between the organisation and its hundreds of thousands of customers isn’t all that easy. Competition for customers has become tougher in most businesses and this, together with intensified digital communications, has had the effect of eroding face-to-face contact. This communications–intensity has actually empowered the customer with an advanced filter against one-size-fits-all types of marketing messages. In effect, today’s customers have been able to hijack the marketer’s ownership of the R in CRM. This means that developing a broad and deep contextual understanding of customer relationships is now mission-critical.

Marketers need to refocus and further invest in understanding the customer journey – essentially to concern themselves with the specific needs of the individual in order to develop valuable long-term relationships instead of concentrating on the familiar short-term Return on Marketing Investment (ROMI). I believe the organisational courage to develop advanced customer intelligence is a key ingredient that will enable organisations with large customer bases to re-inject that much needed human touch into the communication between the brand and the masses of its sought-after buyers.

If organisations rise to that challenge, my promise is that they will be able to start improving consumer trust and eventually create a sustainable competitive edge against other organisations that are too content with the status quo or too slow to see the importance of putting the R back in CRM.

First published on marketingmag.com.au

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The 4 keys to creating a successful analytics team

“Numbers have an important story to tell. They rely on you to give them a voice.”
Stephen Few

In today’s economy, the importance of this message is increasingly significant. The big data phenomenon is driving countless innovation and creating a buzz across industry. Business Analytics is becoming all the rage. Data science is the new “sexy” job.

Convincing the organization to take notice and change remains a challenge.

This Christmas, to ensure data analytics, our “true love”, is allowed to shine its red nose and safely lead the way in 2014, consider the following fourtools to give the story a voice by building a trusted analytical capability in your organization:

  1. Define the required core competencies for your analytics team
  2. Communicate a vision and delivery roadmap for analytic capability
  3. Define your team structure
  4. Invest in your team and their ability to execute

1. Define the required core competencies for your analytics team

Focus allows us to deliver spectacular results. Ironically, focus requires focus in order to deliver meaningful business results. Sounds like common sense right? Now think about how many teams you have been part of that have been allowed to grow organically without clear purpose?

In order to get the right focus for your business, you must have clearly defined core competencies for your analytics team. For example, if your business strategy is to compete on “cost leadership” the core competencies of your team may focus on driving efficiency in business processes to remove cost by controlling production costs or providing decision making tools for outsourcing decisions. If your business strategy is to compete on “innovation leadership” then the core competency of your analytics team may focus on providing a test and learn capability to allow your business to quantify the value of new products or offerings before having to invest too much.

A great example of how the definition of the core competence of an organisation’s analytics capability drove the focus is at Loyalty New Zealand, the leading loyalty coalition in New Zealand, with over 75% household penetration. Loyalty defined their core analytics competency as having the ability "to use the data we have to deliver better, faster and more sophisticated statistical analysis."

As a result, Loyalty New Zealand are now able to create analytical models in under 30 minutes! These models drive campaigns that are now created and executed in less than a day, down from more than 20 days previously.

To be able to get to this point, Loyalty New Zealand had a vision and a plan.

2. Communicate a vision and delivery roadmap for analytic capability

It is well known that communication is critical for an analytics capability in an organization if the information is to be trusted. To be trusted, analytical capability needs to be communicated to the business in their terms. It is only then that the business will want to engage with you. They understand what you are saying and can assess the potential value you might be able to add to their goals. A critical tool to assist with earning the trust of the business is to communicate (and document) a vision for the analytical capability.

An organisation’s analytical capability is unique in that it is often responsible for the execution of other business divisions' strategy. For example, creating response models and campaigns for the marketing team. For this reason, it is extremely important to have a delivery roadmap that shows how organizational assets such as the analytics technology is increasingly integrated with campaign and other operational technology, and how these capabilities impact the organisation’s business strategy.

My colleague Evan Stubbs in his book Delivering Business Analytics, Practical Guidelines for Best Practice, defines this process as:

  • Define the vision
  • Understand the current state
  • Move to target state
  • Measure and refine

Critical to this process is to align the vision and delivery roadmap to that of your internal customers. Strong engagement with key stakeholders is required to achieve this. Making the change sustainable requires ongoing stakeholder engagement, and, importantly, strength and courage to keep those stakeholders accountable. Too often, analytics leaders bend to the will of their business counterparts due to business priorities. Often times these are unstructured reactions to competitive activity or noise that arises from someone who shouts the loudest.

Use your vision and delivery roadmap continuously to ensure the analytics team is consistently delivering value, but also to challenge your internal customers on the relevance and priority of a change in direction.

3. Define your team structure

Determining the team structure is critical as it communicates the “how” of the delivery roadmap. Consistency is once again important, both in the structure you implement as well as the processes that you enforce.

Let’s look at our two examples from the first point. A cost leadership strategy requires efficiencies. Analytics teams working in this environment should be functionally focused on product or very specific processes. They will become specialists in these subject domains and be able to turn work products over much quicker in time.

An innovation leadership strategy requires the team to push boundaries, make quicker decisions and challenge the status quo. A cross-functional team structure best facilitates this ideation process.

4. Invest in your team and your ability to execute

This starts with you first and foremost! Make sure you are devoting enough of your time to set the right examples, coaching your business engagement managers and living the values you would like your team to exhibit.

Partner with your internal customer(s) to arrange three month job rotation programs early in the analyst's career. The experience and understanding a data analyst will gain spending three months building campaigns for marketing provides invaluable context when building a response model for the next campaign. They will know why marketing mandates going with the 100,000 leads for a campaign rather than the 30,000 the model recommends. They will also know how best to work the process to try and get a better outcome.

Use the roadmap to focus the training and change program for your team.

The final step of this investment is to provide your team and the broader business with the tools to put insight into action. At the heart of this is funding. Investing in the right analytic tools is an important part of capability to execute, however more importantly is the need to obtain enough funds to cover the span of the delivery roadmap. Analytics projects are more than technology. They are more about change management, particularly as the output are becoming more embedded into business processes. The change management aspect of the project is where the story becomes reality. If done properly (i.e. funded) this is where our “true love” is found. If done properly, our true love will lead the way through the storm and Santa will successfully deliver all our presents.

 

Happy Christmas. May all your analytics projects be well funded in the New Year!

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Campaign management as we know it is disappearing

Listening to the drumbeats of leading customer-centric organisations around the world, it’s obvious we need to rethink the way we do campaign management. Say goodbye to the days of planning large 1:1 blasts and welcome a world where inbound is the real battleground for marketers.

I recently worked with a large financial institution in Scandinavia, on a transformational program to take them to what they described as the next level of relationship banking. They chose to implement real-time next best action capabilities in their inbound/outbound call centre and web channels before implementing traditional campaign management capabilities in their direct marketing operations. We have been talking about managing the customer experience in the inbound channel for some time but to me this represented a disruptive shift in the priorities when setting out to bring customer centricity to the forefront.

When I was later on a call with one of SAS’ largest customer intelligence clients in the U.S. about a week later, that client said they would be taking a dramatic shift away from their traditional campaign management software and directing that investment to inbound channels. These are only two out of a number of instances that lead me to believe we are at the edge of significant change in marketing.

This change is real and feels like part of a natural of development in which technology will allow more and more organisations to deliver on their customer-centric promises. I am not arguing that the first wave of campaign management was wrong; analysing customer data and customer responses to deliver better targeted e-mail, direct mail and calls has certainly improved the efficiency of marketing operations compared with previous practices. But with the obvious rise of the empowered consumer and thanks to the technology now available to marketing, campaign management must evolve in order to drive the next level of customer centricity; and not only in marketing but across organisations in general.

Studies have shown 30 to 40% response rates amongst innovative organisations that have been experimenting with delivering analytically driven, real-time offers to customers in the call/service centre and throughout their digital presence. And it makes sense. Thinking of myself as a potential customer turning up in a channel – I’m highly involved, I might have been talking to a few friends or researched online and I’m on a mission. This is a moment of truth; this is when my customer experience and my brand perception are being defined, and when I’m done I will only be able to recall earlier interaction as a very vague, distant memory.

So will leading practice be to discontinue all traditional campaign management? Probably not, but I am sure the balance of power will change. We will need to get our organisations in gear to meet a new reality where the majority of the offers being made to customers will be in the inbound channels or as an outbound conversation that was triggered by inbound customer behaviour. We will stop talking about campaigns – which in its essence was never a very customer centric term anyway – and start talking about customer communication programs instead.

This will not be easy. It will require more of a change than when campaign management was introduced as the first level customer centricity. Competing on this new level requires organisations to finally let go of the product centric approach; no more brand managers and no more meetings at the beginning of the quarter deciding on which brands to campaign to which customers.

It’s understandable if marketing leadership is confused about the complexity and the capabilities and competencies they need to enable this shift. But getting it right holds the key to becoming the ‘customer-centric steward’ that the CEO and board are looking for, and having the mandate to align all other functions in the organisation according to the needs and aspirations of the customer.

First published on marketingmag.com.au

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Lessons in Statistical Forecasting from Nokia

In recent times I have had the opportunity to work on a number of customer lifetime value (CLV) initiatives. One of the enlightening aspects of working at the coalface is that it forces one to consider the practical realities of good ideas. CLV is certainly a very good idea. Which business would not want to understand the projected lifetime value of customers?

There are undoubted benefits to reliably forecasting customer value and the world would undoubtedly be a very different place were it not for the advances in statistical forecasting. Energy production planning, telecommunications capacity planning, economic forecasting and countless other critical processes rely on the work of statisticians. The modern economy could simply not function as it does without reliable statistical forecasting.

Working on these CLV projects has however forced me to confront the limitations of statistical forecasting when it comes to determining the survival probability for customers. Beyond a two to three year horizon, variation rapidly takes over and forecast accuracy evaporates. There can be no denying that the concept of “lifetime” value is more nebulous over longer horizons.

Nokia

Nokia went from a position of total market dominance, being the largest smartphone vendor in 2011, to the tenth largest today with a global market share of less than 4% and struggling for survival. It happened seemingly in the blink of an eye. They failed to effectively respond to the shift in market preference from device to operating system.

If we wound back the clock five years and were discussing the use of CLV around the Nokia boardroom table, the discussion would today seem laughable. What value can there be in estimating the “lifetime” value of a Nokia customer when the very foundations on which their business model was founded was shifting beneath their feet. Nokia failed to recognize a fundamental change in the market. As a result, the business model that had delivered so much success in the past collapsed.

No doubt, Nokia had volume projections that were quite different from those that eventuated. Statistical forecasting is great, until the rules change and you are suddenly playing a different game.

Nokia is not alone in this regard. We have all observed the upheaval that technological development has wrought on traditional businesses like bookstores, video stores and newspapers. The pressure continues to this day as banks keep an eye on the development of electronic currencies and retailers grapple with online competition.

What value is statistical forecasting in a world that is subject to such flux? What value is there in aiming to project the value of a customer?

These challenges, I believe can be addressed by considering two critical factors namely; the appropriate forecast horizon for the business and developing alternate planning scenarios.

The Forecast Horizon

As soon as the market shifted from device to operating system, the lifetime for most Nokia customers collapsed from potentially years to the maximum duration of their current contract term. The only reliable forecasting would have been a declining slope of market share. A forecast horizon of three years or longer would have been pure speculation as the fundamentals driving previous forecasts were no longer valid.

Any statistician will tell you that the accuracy of a forecast diminishes as time tends to infinity. We need to reconsider the notion of “lifetime” value. It may be more useful to look at the population of current and potential customers and instead ascribe a value to them over their probable “lifecycle”.

Since we are discussing Nokia, let us look at the example of a post-pay mobile phone contract customer. How do we determine their probable lifecycle duration? Firstly we need to consider the stages of the lifecycle that a customer passes through. The traditional lifecycle of the relationship involves the following stages:

  1. Acquisition (marketing, sales and welcome)
  2. Service provision (including retention, cross-sell and upsell)
  3. Termination of the relationship

It is most useful to concern ourselves initially with the survival probability of the current relationship. As and when the relationship changes, due to changes in the contractual relationship or other factors, the horizon for that particular customer should be re-evaluated. Adopting this approach necessitates a different forecast horizon for each customer.

Factoring in the impact of win-back strategy effectiveness is too vague a notion for all but the most sophisticated customers as this extends well beyond the contract term.

Each of these stages potentially have costs and revenues that need to be forecast and the cash flows of which need to be discounted in order to determine the present value of the customer.

This may not have saved Nokia from eventual decline, but would have allowed the organization to maintain a sharp focus on the immediate horizon of the next device release cycle and may possibly have allowed the organization to maintain a healthy degree of paranoia in relation to competition.

Surviving the Drastic Change Event

Nokia almost certainly had strategy formulation teams hard at work maintaining knowledge of competitive practice. What is less certain is how seriously alternate competitive scenarios were treated. Because we cannot predict the future with certainty, a planned future can only exist as a series of potential scenarios rather than one perfect reliable plan.

In the case of drastic change in business conditions, such as those experienced by Nokia, the business would ideally have anticipated the scenario in advance and have planned a course of action that would result in the best possible outcome.

Military strategists have long known the value of scenario planning. In business, the stakes may not be quite as high as those during armed conflict but are nonetheless potentially catastrophic. There are a myriad of scenario planning techniques that can be employed. Game Theory is one approach that has proven value.

Game Theory worked well in the preventing nuclear war during the Cuban missile crisis. The blockade strategy prevented warships reaching Cuba and ultimately led to a lessening of tensions and delivered a favourable outcome in comparison with the alternative.

Nokia would have preferred to maintained total market dominance in perpetuity, but retaining a substantial market share would have been a better outcome than virtual annihilation.

Managing Turbulent or Gradual Change Scenarios

Another approach that I believe has substantial merit is the scenario modeling philosophy developed by oil industry executive Pierre Wack in the 1970’s. Using his techniques, you arrive at distinct scenarios that represent the possible conditions under which the business will be operated in the future. The techniques place reliance on both statistical forecasting and intuition. It forces the business to think seriously about scenarios rather than rely predominantly on history as a reliable guide to predict future events.

Where would Nokia be today if they had been more alert to short-term threats, planned in advance for catastrophic change and balanced statistical rigour with a healthy dose of executive scepticism?

 

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    The Asia Pacific region provides a unique set of challenges (ความท้าทาย, cabaran) and opportunities (peluang, 机会). Our diverse culture, rapid technology adoption and positive market has our region poised for great things. One thing we have in common with the rest of the world is the need to be globally competitive while staying locally relevant. On this blog, our key regional thought leaders provide an Asia Pacific perspective on doing business, using analytics to be more effective, and life left of the date line.
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