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Using Analytics and Creating Intelligence in “The Cloud”

Wednesday, August 19th, 2009

Part three of a continuing series on the changing analytical ecosystems

By Mark P. Dangelo

www.Innovative-Relevance.com

With any new “miracle” idea or innovation, history and experience has taught us to approach it with a fair amount of skepticism. Foundationally, we often retort, “So what and who cares?” However, when highly respected media icons such as the Financial Times, start to consistently publish objective articles on a topic, skepticism for many turns into potentially creating competitive differentiation (see Cloud Computing Sidebar).

Our Heads are Firmly in “The Clouds”

The terminology and capabilities of cloud computing or “The Cloud,” has exploded in the last three years. For some, the expectations will far exceed reality. However, driven by continual technical advances innovatively supported by people and processes, “The Cloud” approaches have found harmonization with profit starved investors and forward thinking strategists.

Equally, the widespread euphoria has morphed into fragmented realities for corporate decision makers seeking robust operating functionality supported by rapid implementation cycles. That is, they have found quick successes, but their larger future is still unclear. In general, the principles of cloud computing are no longer buried in trade journals, presented in an obscure standards brief, or merely debated by technologists over beers.

As a matter of fact, cloud computing, underpinned by new measurements and data integration demands, is increasingly appearing in corporate agendas with an estimated annual spend in the billions and growing at an annual compounded rate of 25% and 40%.

At a time when organizations are questioning everything and dealing with iterative cost cutting programs, these articles and growing implementation successes are beginning to establish a foundation for lasting action.

Yet, we need to ask some very fundamental questions before we redefine the 2010 budgets and open the checkbook. For example, what is the roadmap, and more importantly what does “The Cloud” pragmatically offer? How can quality, “decision intelligence” be developed? What analytical measurements, driven by cloud technology, are now important?

You see, “The Cloud” is as important operationally as it is strategically if we adopt more than a “one-off” line of attack.

A Changing Reality for Decision Making

Analogous to the aftermath of the Great San Francisco Earthquake of 1906, we can foresee lasting corporate and social strife as a result of the prior supply chain practices and decisions encompassing origination, servicing, and securitization processes.

The permanent solutions and regulatory changes will be years in the making. Nonetheless, what is becoming apparent is the fundamental root causes. Our current public flaws architecturally resided with the flawed reasoning models used to confirm co-dependent mortgage decisions.

Yet, with finance and mortgage groups (FMG’s) spending over $14 billion (out of $80 billion globally) on decision driven business intelligence, dashboards, scorecards, planning, infrastructure, and applications, what will the new costs and benefits be when using cloud computing solutions? Sometimes, when dealing with highly complex challenges, historical references can teach us how to avoid a reoccurring fate of excessive spending.

In reviewing a 2007 report by the Economist Intelligence Unit (EIU, “In Search of Clarity, Unraveling the Complexities of Executive Decision Making”), we are able to witness a time capsule of priorities, methods, and challenges internalized prior to the most severe recession in nearly 80 years.

In hindsight, there are several understated findings, within the EIU assessment, which stand out:

1) “Poor data leads to poor decisions,”

2) “Challenges only increase as companies grow,”

3) “Too much art, not enough science?,” and

4) “Decision support tools need to be easier to use.”

Fast-forward two plus years, and we now see how the lack of relevant quantitative criteria fostered one of the greatest wealth destabilizations in three generations. The indicators were all “green,” but the decisioning results wound up to be very, very ”red.”

Layering and Leveraging KPI’s

It was a myopic focus on granular key performance indicators (KPI’s,) without a holistic examination of interrelationships and efficacy, which produced “false positives.” Or stated differently, the use of inelastic, static measurements and monitoring methods to predict future performance was just a disaster waiting to happen. Future decisioning cannot be defined merely by projecting forward historical indicators (i.e., backward focused gauges as a measure of future performance and consumer behaviors). It is akin to driving 65 mph while constantly being focused on the actions in the rearview mirror.

As we know, this was the preferred BAU for analytical predictions before the escalation of cloud computing, and the multi-faceted integration demands implied with the deployment of these new, virtual data sources. Moreover, we now are confronted with challenges of cascading economics and public policies that result in the demand for a series of risk adjusted analytics needed for decision making, compliance, and operational performance. So, what now?

“The Cloud” adoption, coupled with the crystal clear failures of the past, represents a waterfall opportunity to redefine and rebuild how decision making for the next decade should be done. The opportunity is with not just technology, but the integration and compartmentalization of multi-polar sources into intelligent and self correcting decision approaches.

The future of analytics begins to mirror a federated model of interconnected KPI’s that not only assesses past performance, but provides adaptability of forward-looking indicators that are properly vetted and cross-matched against multi-polar requirements. After all, analytics is more than data – it must deliver intelligence.

Sound impossible? Too Complex? Too futuristic? Think again. What I’m representing in this thumbnail began in earnest back in 2007-2008 with their seeds planted nearly a decade prior.

Analyzing and Anticipating Tomorrow

As the siloed technology discussions of SaaS, SOA, virtualization, and web services converge and confront fluid business pressures, standard operating processes and decision making breaks down and becomes dysfunctional. Business leaders struggle with innovation and consumer behaviors without sufficient analytics, intelligence, and predictability on “what’s next?”

Moreover, changing market conditions have created voids in reporting and compliance systems, internal skill sets needed for adaptation and the budgets needed to implement change. There is a need for clarity to avoid layers of cascading hazards, but uncertainty and risks have created institutionalized frustrations. In essence, we need to unwind the legacy, but be mindful of the disruptions and chaos that can be introduced.

In several of my prior 2009 articles, we examined the foundational strategies of analytics. In this article, we introduced the new variable of cloud computing and touched on the benefits and challenges it creates for severely strained IT departments and business personnel. However, what is the answer? What are others doing? What are the implications of adoption or redefinition?

To assess and begin anticipating viable solutions for the use of analytics, we invite you to participate in a brief survey. The survey can be found at www.Innovative-Relevance.com/analyticsurvey/. We anticipate releasing select findings of “Using Analytics and Creating Intelligence in ‘The Cloud’” industry report, starting in October 2009 in subsequent MBA articles.

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In closing, there is a strange reader reaction that happens when a writer looks into the future and attempts to ascertain strategy – go figure, not everyone agrees on how to read the aggregated indictors for positive and profitable results. Earlier in 2009, when I holistically examined analytics and the likely impacts on operations and markets, there were many doubters. Now after another $5 plus billion in new M&A actions, perhaps those ideas don’t look so crazy after all?

But, whether you agree or disagree, we cannot deny our predicaments both domestically and globally. As printed in the Financial Times on August 13, 2009, “Foreclosure filings, which include default notices, scheduled auctions and bank repossessions, hit 360,149, an increase of 7 per cent from June and 32 per cent on the year. One in every 355 US homes received a foreclosure notice in July, according to the online marketplace for foreclosure properties.”

There is a need for change and how we responsibly and ethically define “success.” New and relevant analytics will help us determine our performance and models of operations – before others make those decisions for us.

Posted in Analytics, Architecture, Cloud Computing, Dashboards, Data, Financial Services, Measurements, Mortgage, Orchestration, Outsourcing, Strategy | No Comments »

Bankrupt Macro Ideology

Friday, May 22nd, 2009

There were some very key changes while we slept on the global stage:

 

1.        The UK “AAA” debt outlook was downgraded from stable to negative. 

2.       The Dollar and more important the U.S. ability to finance 15% negative debt to GDP (now < $13.3 trillion GDP projected for 2009 against a growing deficit) is looking more and more risky.

3.       The Canadian SWF’s (Sovereign Wealth Funds) / pensions are also apparently limiting ther buying of Sovereign “paper” from heavily indebted countries (e.g., USA).

4.       The U.S. debt auctions continue to be anemic to poor placing reoccurring pressure on the Fed to purchase its sister agency debt (now estimated to be in excess of 1.5 trillion). 

5.       The growth models that propelled the world markets for the last 25 years are done – the U.S. consumer made Asia and the Middle East SWF’s rich and flowing in trade surpluses and dollars.  The 4th version of global trade has reached its end.

 

I could go on but the potential implications are becoming clear (not facts, not yet):

 

1.       The ability of private industry to finance debt in the second half of this year may come under significant pressure – aka higher costs to borrow if it is available at all.

2.       If Sovereign debt and the ratings of EU developed nations continue to fall, so will the fragile bottoming we are seeing.  Who will buy debt backed by “hope?”

3.       The result might be new corporate costs cutting initiatives across the board regardless of industry. Question is how are they measured and are they enough? 

4.       Anyone recording profits in dollars will experience profit and currency conversion pressures.

5.       M&A’s will be “survival” driven (i.e., little if any premiums), while the credit freeze for medium to small institutions already struggling for funding will drive may to close.

6.       The lack of analytical discipline and rigor will lead many to make uninformed decisions and experience “unintended” consequences

7.       We could be in for a “third” shockwave starting in Q3 2009.

8.       Those dependent on high volume U.S. markets (e.g., outsourcers, manufacturing, B2C, …) will have to radically change their arbitrage business model and strategy or watch others take over their position of dominance.

9.       If unemployment passes 12% (forget the 10% upper control limit), then government intervention may reach a disequilibrium – for globally interconnected economies at these levels we do not have any models or experience with this circumstance (this is beyond the localization of the Great Depression).

10.   Whilst economists want governments and consumers to “spend money” they don’t have there is only so much reality within this tattered dogma. 

 

Much more could be said…if there is such a thing as an “offensive defense” then this should be the approach for many leaders.  Non-conventional revenue growth may be a key to future success.

Posted in Analytics, Business Model, Industry, Measurements, Outsourcing, Strategy, U.S. Treaury | No Comments »

After near Industry Extinction, Analytics are Questioning Everything

Monday, May 18th, 2009

Accelerating Returns of Mortgage Operations Utilizing Multi-Faceted Indicators and Analytics

By Mark P. Dangelo

 www.Innovative-Relevance.com

For decades, managers and their teams have sought the “holy grail” of decisive and discrete performance indicators that would assess and predict corporate profitability.  As we now know, their inability to cohesively link strategy, operations, risks, and rewards have resulted in permanent industry realignments – M&A’s, failures, oversight, fiduciary breeches, and consumer alienation.  However, the industry’s past predicaments were not just contained within individual products or exotic solutions, but with the downstream implications of their adoption.  Straightforwardly stated, analytical causality across the enterprise was grotesquely misinterpreted.

Additionally, complacency and arcane systems of beliefs led many to rely on irrelevant indicators, practices, processes, and technologies.  Even after billions were spent on SOX, Basel and other regulatory compliance efforts, the recent economic crisis clearly indicates that the global public, not just domestic ones are no better protected than they were in the “Age of Enron.” 

So, with all the theories, vendors, and prior pundits being replaced, we have to ask, “What is next?”  What are the informational governance and regulatory approaches that have efficacy today and tomorrow?  How can agile and adaptable analytics be achieved across the breath of our partners and data sources, including our servicers linked to the programs targeting consumer “workouts?” 

Whereas, proactive business analytics and governance were once the domains of larger lenders and originators, innovative business and technology advances have leveled the playing field regardless of organizational size and budgets.  The questions are many – the answers are evolving.  However, let’s take a “walk on the wild side,” and see what our future holds beyond the anti-climatic stress tests.

Conducting a Diagnostic Assessment

For many organizations, a holistic and critical examination of analytical usage (i.e., business intelligence, dashboards and scorecards, analytical applications, MDM, warehouses, et al) is a time consuming process tainted with internal biases and prejudices.  Often times, analytical evaluation and projections are done across the enterprise using fragmented ROI point-solutions — not the least of which are ignoring the hundreds of siloed “management” spreadsheets lacking little referential integrity or understanding of how they interconnect or influence each other. 

The result of the ensuing analytical chaos are diverse “versions” of operational performance, ROI, risks, regulatory compliance, and worse yet, a false sense of security – until as illustrated recently, the bottom falls out of markets.  Moreover and with great frequency, organizations latch onto “analytical answers” and quickly proceed with allocating resources all in a desperate effort to secure success. 

Yet, is the most convenient analytical answer correct?  As many enterprises discovered during the recent global financial and economic meltdown, it wasn’t the answers that were difficult to achieve — it was the fact that the wrong questions were being asked.  Without the relevant questions and proper alignment with required strategy, managers were ill-prepared to deal with pervasive calamities.  It was as one industry observer said, “Driving with your eyes closed.”

It is this hidden cost of disjointed analytical architectures, spread among the business units and IT, which led AMR in 2008 to estimate that global enterprise expenditures exceeded $57 billion USD.  What is more, according to December 2008 Accenture report[i], only 60% of organizational decisions were supported by analytical insights.  The rest of those tens of billions of dollars worth of corporate investments, well, were not. 

With an average organizational analytical investment consuming between $250,000 and $1 million, depending upon market sub-segment, decision makers have to be wondering, what all this technology was really worth — as budgets are cut, consumer scrimp, and the two year recession lingers into 2010.  This begs the question for many decision makers, “What are the 3-year returns and operating costs for analytical investments in 2010-2012?  Can we afford to sustain what we have and invest in the future?  For every dollar of capital spent, are we looking at another$ 5 to $7 spread over the next 3 years?”

To gain a handle on the use of enterprise analytics (EA) and the “questioning of everything” previously deployed within the entity, organizations have begun conducting independent diagnostic assessments to establish an objective baseline and an iterative roadmap for the future.  Organizations are no longer just examining impacts within lines of businesses, but the forward and backward value chains spanning multiple operational segments.  Representative diagnostic categories include:

·         Financial Impact / Financial Integrity

·         Monitoring Methods, Rigor, Techniques

·         Operational and Business Intelligence

·         Visualization, Views, and Meta Data

·         Technology and Infrastructure

·         Performance Management, Reporting

·         Data Warehouses / Marts

·         Security, Privacy, Information Governance

·         Dashboards and Scorecards

·         Regulatory Compliance and Delivery

Underpinning a base of solid financial and performance data, organizations have embarked on their own “analytical stress tests” in an effort to define what and how to frame their indicators – and the methods and sources needed for their accurate delivery.  Even though we hate to admit it, the regulators just may have been on to something.  When examining the data, process, and indicators contained within the stress tests themselves, before the results were subject to change, there are substantial self correcting and regulating diagnostic guidance buried in their approaches. 

In a Financial Times article by Russell Walker on January 30, 2009, he stated, “JPMorgan’s success came from identifying novel data and realizing that it challenged conventional thinking.”  Isn’t that really what analytics and the investments they represent are all about?

Integrating Strategy, Demands, and Success

Analytics taken out of context can yield “false positives” – aka erroneous decisions.  Without proactive linkages to strategy, operational demands, and performance results, analytics are merely bits and bytes spinning on a metallic coated platter.  By making the most of the entire spectrum of corporate analytics and their implications, what led to an industry’s dishonor can be used as its foundation for future growth.

For executives seeking to move forward and identify profitable new markets, what strategies for growth should be defined, deployed, and sustained in the prospective face of onerous government oversight?  What has worked in the past and where should organizations concentrate their resources in the future facing new consumer behaviors?  Finally, how can technology and policy be exploited to create a robust business case for reducing costs, growing profits, and capitalizing on market trends, especially within the rebirthed secondary markets?

Many quantitative organizational analytical approaches are starting over.  After huge CAPEX investments coupled with significant budget increases, the value of insight and governance produced by “intelligence and analytical” tools have yielded a false sense of purpose and security. 

The long held ideas, practices, and techniques of assessing and projecting have proven inadequate for current operating demands.  With historical 20/20 hindsight, what is now apparent is that the conceptual and piecemeal methods deployed were too remedial and the business solutions too abstract.  A new way forward must be developed.

Using the aforementioned diagnostic assessment, progressive organizations are integrating strategy, demands and success into an iterative go-forward roadmap (illustrative list below):

·         Consumer profiles, market usage, and competitor capabilities

·         Orchestrated solution sets built on componentization of best-in-class

·         Advanced multi-dimensional data segments (e.g., OLAP)

·         Predefined and configured software components

·         Forward and reverse “supply chains” across micro and macro sources

·         Auditability, repeatability, adaptability to promote consistency and accuracy

·         Interoperability of decisioning networks and toolsets

·         Vendor capability and product leadership within centers of excellence

·         Reusable libraries of statistical data sources and routines (e.g., ETL, marts, warehouses)

·         Visual and standardized query capabilities and reporting across functional segments (e.g., financial, operations, risks)

 

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While there is much more that needs to be written on internalization of agile and adaptable analytics (AAA) into the corporate culture of tomorrow’s finance and mortgage groups (FMG’s), the journey begins with an objective assessment and a new path forward.  For as we now realize, all too painfully, there are “ticking time bombs” still remaining within our existing operations.  They must be rooted out.

The uses of analytics were once about “personal” manipulation and insights – individual, department, or special operational interest.  The survival criteria of organizations are now focused on their end-to-end usage across the enterprise, while proactively integrating isolated components among the channels to achieve relevant macro-micro efficacy. 

A new age of Enterprise Analytics has been launched as it is now questioning everything surrounding past and future indicators.  However, are we ready to embrace new questions and non-conventional insights?  Or will we relegate the new findings to aberrations that are just too painful to accept?

 


[i] “Business Intelligence Software Time is Now,” BusinessWeek, Rachael King, March 2, 2009.

Posted in Analytics, Business Model, Dashboards, Financial Services, Measurements, Orchestration, Strategy | No Comments »

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