John Joseph

Vice President, Product Marketing

I saw an interesting discussion topic on the MDS Lavastorm Analytics LinkedIn group on our ability to predict whether a customer on a service plan will or won’t pay their bill. A subsequent blog post outlined some of the criteria that lead to failure to pay.  Interestingly, the list of factors included factors based on usage (including usage or related, but different products), payment patterns, product selection, and interactions with the customer through various customer contact channels.  For example, the list of common predictors  included:

• A customer lowers or limits their service plan
• The amount the customer is expected to pay changes significantly
• Unusually high service consumption in the middle of a billing cycle
• A pattern of non-payment

When we improve customer and billing processes with the Lavastorm Analytics Platform at major service companies, we also find that root cause analysis of the order-to-bill process and, specifically, the cause of credits and bill adjustments, also indicates whether payment delays should be expected.   When looking at these processes, the following cases are important:

• Errors in the point of sale process – Many issues arise when a person purchases a service, but they receive an invoice that doesn’t seem to match what they ordered.  Sometimes everything is correct and the customer just cannot understand the bill, but in other cases, the bill may be incorrectly calculated or the product may not have been sold properly.
• Unexpected billing miscalculations – If billing miscalculations reach the invoice and the customer, payment delays go up.  Catching these errors before the invoice is calculated not only eliminates payment delays, but also eliminates calls to customer service representatives for clarification/adjustments.
• Known billing miscalculations for new services – A company striving to shorten time to market for a new service may introduce the service before the billing system has been modified to correctly calculate the bill.  In this case, high bill amounts may be misleading because an adjustment has been expected all along to correct the bill.

Aside from what you should monitor, it is also important to consider how you should monitor failure-to-pay indicators.  First, it should be obvious from these lists that predicting bill payment behavior will require you to consider data from multiple sources, including usage systems, billing systems, and customer support systems.  All of this needs to be unified and evaluated for you to get an accurate view of customer behavior and likelihood to pay.  Second, monitoring some indicators, including usage, requires observations between billing period and, ideally, on a continuous, or real-time, basis so that you can get an early warning of how current behavior compares to past behavior or to business rules, such as the maximum plan minutes.

What else is needed to predict failure to pay?  I look forward to your comments.

John Joseph

Vice President, Product Marketing

As analytics play a larger role in many organizations, the analytics profession itself is also changing.  A number of people who contributed to the MDS Lavastorm Analytics Community on LinkedIn expect there to be a number of major changes in store for business analysts and data analysts in 2012.  The group thought the major trends and changes on the horizon are:

• A shortage of analytic professionals (business analysts, data analysts, data scientists, BI analysts, etc.) will become evident. Aside – there is a great definitions of analytic professional roles on modernanalyst.com.
• More focus on the “analytic profession” within an organization. Those with a base set of technical skills (excel, SQL, etc), a strong business / process knowledge, and most importantly, a curiosity / motivation about data & analytics will be in the driver’s seat and will thrive.
• Empowered by easy to use and visual interfaces, non-PhD analysts will use software to apply sophisticated modeling and algorithmic techniques to large and small data sets.
• A requirement for more classes and training at companies and at universities.

With a shortage clearly upon us, organizations need to address what to do in the short term.  In my experience, the dominant model seems to make information available in interfaces that are visual and that a normal business users can learn and use without much trouble and to have more-technical folks within the business units take on a role as data integrator and publisher.  This way the business can still do the heavy lifting if IT doesn’t have the bandwidth to respond to the business needs, but the information is made broadly available to decision makers regardless of their technical skill so that the information can have the greatest impact on the business.

John Joseph

Vice President, Product Marketing

Over the past few weeks, one of the hottest discussions on the MDS Lavastorm Analytics Community on LinkedIn has been the top predictions for 2012.  In fact, it was probably one of the hottest topics posted for all of 2011.  The sheer number and variety of the predictions indicates that the business analytics (a.k.a. business intelligence/BI) world is alive with innovation, new technologies, and investment.

We recently published our own view on the major changes or trends in 2012 on IT Business Edge.  They were:

1. A Shift in Analytical Power – IT and business groups will work more collaboratively as the business insists on more analytical power and ownership. Self-service BI/analytics options will continue to grow in numbers.
2. A Focus on Trust – To address compliance and auditing requirements organizations will put more emphasis on processes and controls, such as visualizations for data forensics, that build trust in the data among IT, the executive team, and business managers.
3. A New Wave of Discovery – increased awareness and acceptance of visual query tools will make the concepts of data exploration and discovery a much bigger part of an organization’s BI portfolio.
4. Real-Time Analytics, Real-Time Action – As BI and analytics get pushed to more business users, companies will strive to shorten the time from an insight to a business process change.
5. Big Data Moves from Science to Reality – Instead of Big Data “science projects”, we’ll start to see organizations integrate Big Data analytics into their standard BI organizations/processes.

You can read a bit more on these trends here: Top Five Business Intelligence Predictions for 2012.

In addition to those trends some other predictions that showed up in the MDS Lavastorm Analytics group see the following changes to how analytics are created and consumed:

• Organizations will create Big Data sets that bring together data typically disconnected from the IT-governed data processes, including CRM, social media and web analytics data.
• Greater use of predictive analytics.  For example, predictive analytics will be combined with new data sources, such as social network analytics, to detect and reduce fraud in health care and other industries.
• A greater convergence of emerging technologies, such as predictive analytics available in the cloud and consumed anytime anywhere on mobile devices.

With changes and trends of this magnitude, it begs the question, “What isn’t changing?”  One thing is clear.  There is a growing passion that data is critical to decisions and that analytics can help businesses respond better to changes including the changing needs of their customers and partners.  As MDS Lavastorm Analytics looks to 2012 and beyond, our mission remains on course to help leading companies analyze, optimize and control business processes to drive greater business performance through discovery-driven business and data analytics.  We are planning our investments accordingly to keep the Lavastorm Analytics Platform on the cutting edge of business analytics that give business users visibility to diverse, siloed data and across fractured business processes.

John Joseph

Vice President, Product Marketing

Earlier this week I spent a day with a telecommunications service provider that is also a thought leader in revenue assurance.  We discussed how they got to the point where they had generated many millions of dollars in cost savings and additional revenue.  Out of that discussion came a number of best practices for getting your revenue assurance initiative on track.

If you aren’t familiar with revenue assurance, it is the process of analyzing bills against services rendered to ensure that the bill isn’t leaving money on the table – either in the case where you are paying your suppliers too much money or you aren’t billing your customers enough.  This is a big deal in telecom, but the same principles can be applied to any business where bills are issued against service plans, such as bills for healthcare, cable and internet, streaming radio services, etc.  During the discussion we identified five keys to revenue assurance success:

1. Make it a Business Priority –Probably every  telecom company does some level of revenue assurance, but it’s clear that not all apply the same rigor, and, therefore, their results can vary significantly. For example, some companies that grow through acquisitions may not integrate their systems or apply their best revenue assurance processes across the newly-formed entity. On the other hand, focused programs with a tenacious staff, clear business goals, and the power to implement changes in other departments yield the best results.
2. Acquire the Proper Tools – To wring every dollar from a revenue assurance plan, teams need to cast a wide net and that means analyzing different data sets from many different angles.  Tools that give great analytic freedom and the flexibility to integrate diverse data sources are essential.
3. Ensure that Your Team has the Skills to Use the Tools – The number one criteria for evaluating analytics tools for revenue assurance should be whether the team has the skills to make use of them at all.  High-level, visual tools, such as the Lavastorm Analytics Platform,  allow more users to analyze the data than low-level programming tools.  If your team has limited skills, you can make the most out of the skills you have in house by using the skilled analysts as information creators/publishers who create analytic applications that the less-skilled analysts use.
4. Select a Team with Deep Knowledge of the Data – Understanding the data is more than half the battle in revenue assurance.  Knowledge of the data gives you insight on where to look next for additional revenue opportunities and it allows you to create the required business logic and that can sometimes get messy.
5. Select a Team With a Good Imagination – As you ramp up a revenue assurance initiative, there are low hanging fruit that can yield significant revenue.   After you have cleaned that up, the wins are still plentiful, but they get tougher to find.  Your staff needs to have a bull-dog attitude and the creativity to look at data in different ways to
   uncover additional value.

Please comment with your ideas on these and other revenue assurance best practices.

Matt Hooper

Chief Marketing Officer, MDS

This post has been inspired, in some small amount, by IBM’s suggestion that businesses are unable to analyze over 90% of their data.

Jeff Jonas, IBM chief scientist for the entity and analytics group, has suggested that “as computers are getting faster, organizations are getting dumber – they are now lucky to fully understand seven percent of their data and this is steadily getting worse.” The data analytics equivalent to the age old question, “What comes first, the chicken or the egg?” is “What comes first, the analytic solution or the business requirements.

For a long time the conventional wisdom in telecoms circles has been that we need to know the questions the communication services providers (CSPs) want to answer before we turn them loose to analyze the data.  That’s all changed.  If we look back over just the past year and assess the plethora of attention being directed at big data and business analytics, we’ll find that a large part of the effort is about getting the data in front of the users faster and reducing the requirement gathering, data modelling, report building, and other steps that normally would take place before the business user ever saw the data she needed.  For CSPs, in particular, discovering the insight hidden in plain sight, as it were, could make all the difference in minimising revenue leakage from a notoriously fickle customer base.

It raises the question of what CSPs should be looking for in their business data.  Most people would reflexively say they should get answers.

I would propose, however, that CSPs should view data analytics more as a way to find out what the questions should be; letting the data guide business decisions rather than simply answering predetermined and recurring questions. For example, rather than assuming revenue leakage necessarily stems from traditional sources – such as billing inaccuracies or rising commission costs – and seeking to find data that matches the assumption, CSPs should let the data provide the lead for what the problem might be, before defining the solution. This intuition and discovery-driven approach to data analytics can be tightly intertwined with a specific business process,  often leading to near real-time insights and insights that are easier to understand and act on to modify performance.

Even more importantly, however, with a discovery-driven approach, CSPs will find new areas where data analytics can improve performance, including areas of the business, such as those dealing with fraud or customer management, where new questions arise every day that go beyond pre-modeled and predetermined business logic.

So a discovery-driven approach, where analytic solutions are created before the full business requirements are known, can guide you to what you should be asking, give you the answers to these previously unknown questions and lead to more actionable insights that those provided by traditional reporting and data management processes.

Vice President, Product Marketing

TM Forum’s Management World Americas just wrapped up a very productive event in sunny Orlando.  This year’s theme was The Innovation Race, Fueling New Revenue.  As always, the event was a great opportunity to catch up on the current issues circulating in the telecommunications industry.  As a proponent of information-based decision making, I was thrilled to see the level to which analytics is now dominating the conversation in the telecom industry.  In both one on one conversations with service providers and in the conference presentations put on by industry visionaries and vendors, the need to use information to improve the business was by far THE most dominant theme.

There were two aspects to this theme:

1. Greater data variety and volume – The expressed need to handle a greater variety of data and greater volume of data started with a baseline of integrating operations support systems (OSS) and business support systems (BSS), but also extended to new frontiers, such as machine-generated data (or machine to machine/M2M) data sources.    This general need for analytics that cover a broader data footprint is in line with business intelligence trends and the wave of activity around Big Data that I’ve experienced in other industries, such as manufacturing and retail.
2. Tie analytics to business processes to enable action – A unique aspect coming through loud and clear in this telecom-focused event was the need to tie the analytics to a specific business process so that the analytics can be used to make both strategic and daily improvements.  I won’t go so far as to say “embedded” analytics because sometimes people think if they embed a dashboard in a standard software product, such as a CRM system, they have that one covered.  No, this idea is about strongly connecting the analytic to a process – both in terms of data (i.e. near real-time data about the process) and the people (i.e., giving the people who can affect the process he analytic knowledge to make the change).  Let’s call this “in-flow analytics”. Examples where this close tie between the business process and the analytics were highlighted numerous times, including the Catalyst project where products like the MDS Lavastorm Analytics Platform were used to create dashboards showing current
   status of critical business operations, such as customer service queues, the order-to-bill process, the service delivery process.

Both of these aspects were on display in a discussion I had with a major service provider who related to me that their organization uses an analytics dashboard to track the customer contact center on essentially an hourly basis.   When they see the wait queue go “off the rails” they intervene to change the human behavior and get things moving again.  That’s in-flow analytics because the analytic application is running alongside the process and is used in a continuous or at least a continual basis to improve the process.  Plus the analytic was taking into account a greater variety of information than ever before.  Not just billing information and CRM data, but also data from the interactive voice response (IVR) system itself.  The most significant part about that story though is that the analytics are driving process changes throughout the day as conditions change.  It’s interesting to note that the changes that were implemented based on the analytic were often changes to human-driven processes and dictated human behavior throughout the contact center.  That’s a great example of the responsiveness that can be achieved when analytics are used “in flow” to modify an ongoing business processes.

These concepts are not new. In fact, they have been discussed in influential writings such as “Analytics at Work: Smarter Decisions, Better Results” by Thomas Davenport, Jeanne Harris and Robert Morison.  But it’s clear from this year’s Management World Americas that analytics are being used in a multitude of ways to drive
process innovations throughout the telecom industry.

Matt Hooper

Chief Marketing Officer, MDS

For those of you that have seen the movie ‘Big Wednesday’ you will know that it is an iconic 70’s coming of age movie centred on change and surfing large waves. Big Wednesday is the day when the biggest waves or sets come in.  For some time now there has been a growing swell around the area of analytics in the communications market and we are now seeing a wave of both vendor and service provider activity, as well as in the TM Forum, that is creating considerable excitement. So why is this?

The communications industry has evolved and transformed at a great pace in the last 10 years and while network infrastructure, OSS and to some extent BSS has undergone and continues to go through transformation, the industry not only has a growing volume of enterprise data, but also more business processes which stretch across functions, business units and entire enterprises. Increasingly often relationships between the data and these business processes gets broken so it can be very difficult to visualise business performance across these processes and more importantly drive performance improvement strategy.

The analytics opportunity across these business processes is to be able to visualise and trace performance across the entire process for a business function, for example, order accuracy for an SMB segment, using analytics to highlight where performance improvements are needed and at what stage of the business process. By understanding where the issues are and not just that there are issues, they can be resolved and clear strategies can be designed and measured from a business KPI perspective to drive customer experience enhancements such as reduce fraud, improve revenue and profitability, improve billing and order accuracy, reduce churn and provide the basis for launching new offerings based on predictive data patterns.

This is a prize worth having and does not require costly and time consuming transformation. The key topic at this year’s Tele Management World was ‘Customer Experience Management’ and enhancing the service that customers get in order to differentiate and grow. The key to this is the power of knowledge, knowledge of how business processes perform and how they can be improved by achieving visualisation across the whole business process and then taking persistent action to build a high performance, new generation communications business. The opportunity is there for CSP’s to get on the front of the wave and ride it!
Find out more at: http://www.mda-data.com/solutions

Senior Product Manager, MDS

Matt Hooper

Chief Marketing Officer, MDS

Currently, CSPs face a problem as they are constrained by high numbers of legacy systems in their back office. This leads to high volumes of product, service and functional silos, meaning that there is no ‘single view’ of customers or services (a concept talked about in the industry for several years), and as a result, this creates increased customer experience complexity for the CSPs.

As the evolution of the communications services industry continues towards connectivity solutions and an explosion of virtual service provision, new business models will need to be supported by a greatly enhanced BSS layer that sits between the customer experience and back-office O/BSS in the CSPs IT estate.

For the CSPs who are looking to adopt  a far reaching transformation model, the investment required can result in long-term demands across their business, including costs that can reach into the high millions, sometimes years of investment, ever-increasing complexity, and, ultimately, the risk that the programme may fail to deliver, as many others have done.  For the CSP that has already committed to billing transformation it is even more critical to adopt BSS enhancements that introduce benefits in the short to medium term, helping to drive down costs and respond more efficiently to variable customer demands and new market opportunities such as VNO/E.

In order to address these issues, CSP decision makers need to evaluate alternative options that can overlay and coordinate existing systems quickly while leaving existing IT assets in place; otherwise they risk being left behind in a continually evolving marketplace. It is here where we will see the emergence of new generation BSS models as a driving force for rapid customer experience enhancement over the next few years.

New generation BSS will provide CSPs with a layer that sits over existing systems and, also with a provision for new services which will in turn provide a single view of each individual customer’s products and services, empower customers to manage their services on their terms. A unified layer keeps an existing O/BSS asset base in place while unifying the back end data sources and business processes. It’s all about providing a single, unified platform that offers a single view of the customer and enhances the customer experience in a way that drives up customer satisfaction. This will enable customers to have a whole view of business comms expenditure, and monitor where rogue spending may be taking place.

In the future, this flexibility will become more prevalent as new services are introduced that existing system assets will have to integrate with. In the next few years alone we can begin to see suppliers and partners emerging in cloud, healthcare, utilities, as well as the continuing and fragmented rise of digital content provision. New generation BSS is about making services and networks more unified and selling into market segments, such as business, with pace and agility.

Read more about MDS BSS Solutions.

62 per cent of businesses are increasing their telecoms spend year on year.  However, 65 per cent are under increasing pressure to justify that spend to budget holders.  Four in ten telecoms managers said that they are looking to reduce the number of communications suppliers they use, with a desire among nearly all companies to introduce unified communications.

For telecoms managers in businesses there is a recognised need to make savings by looking in greater detail at their bills with a higher degree of analytic capability.  Coupled with a desire to reduce the number of suppliers and introduce unified communications, the market has become fraught with challenges for service providers looking to cement ongoing profitability from business customer bases.

In an increasingly complex telecoms environment there is pressure to justify spend and rationalise suppliers to budget holders like never before.  The reality for many telecoms managers is a lack of insight into telecoms usage across their business.  Service providers must increase control and value through analytics and insight if they are to secure long-term revenues and growth in this highly profitable customer base.  Ultimately they must provide assurance that the end customer experience is unified and operating as intended, to the highest standard, or risk losing out in an increasingly competitive and crowded market.

A copy of the Connecting with Business Customers Report is available for download at: http://www.martindawessystems.com/connecting-with-business-customers.php