By Mark P. Dangelo
www.Innovative-Relevance.com
We seemingly measure everything. We define control limits. We assess correlations and assign statistical significance. We examine process cycle times, and we do it using robust methods (e.g., Six Sigma, scorecards, dashboards, EPM), investment frameworks and measurements (e.g., budgets, forecasting, IRR, NPV), and a host of internal and industry KPI’s (key performance indicators). We pay for third-party data sources that track mortgage products, consumers, securities, and other benchmarks similar to the sports announcers who flaunt encyclopedic baseball statistics.
Our pervasive technological platforms are able to create and track infinitesimal quantitative artifacts within broad categories including; borrower contact, document management, workflows, workouts, and default management demands. During this time of crisis, we are justifiably obsessing over performance, and our ability to do it better than our competitor. It also appears that our market providers never fail to remind us of this age-old competitive axiom at every event – all underpinned by a decade of very significant corporate spending on BI (business intelligence), reporting, and aggregation toolsets.
Most recently, objective analytical assessments have been brought to center stage by an angry public, opportunistic politicians, and “late-to-the-party” regulators (e.g., Stress Testing). Analytics represent a horizontal collection framework for understanding our vertical “As-Is” states and iterating ourselves to the “To-Be” operating and strategic goals – that is determining not just measurements for the sake of siloed measuring, but interconnected department causalities (e.g., EPM).
Yet, what call to action is provided within and across these hundreds of data points routinely gathered and aggregated? Who has primary or implication accountability? Who is directly and indirectly responsible for what is measured? What does it all mean within an industry or organization struggling to survive? Who within our operations are trained and educated to unlock the hidden “secrets,” while understanding the “checks and balances” within the frameworks?
In reality, the volume of disconnected atomic-level analytics gathered within some organizations exceeds 8,000 distinct metrics. With a new obsession for measurements not seen since Edward Deming’s statistical control disciplines were finally accepted in the 1990’s, analytics in all its emerging forms are fast becoming a “great reawakening” for FMG (finance and mortgage group) decision makers as they struggle to link outcomes, accountabilities, and responsibilities.
By Design, a Confusion of Subtleties?
The next decade of FMG leaders will be enthralled with the definition and usage of analytics. Why would they not? Every week, new press releases tout new-fangled features and acronyms all in an effort to gain “enterprise performance,” “top investment,” “better decision making,” and of course, “electronic, resilient, and reliable data sources.” All laudable goals on the surface albeit somewhat cliché and increasingly ubiquitous.
However, the extensive public relations for analytics has a potential to derail its lasting benefits, as vendors advertise solutions and product repositioning over the need of changing industry usefulness. A current Twitter search finds dozens of analytics, BI, data mining, and dashboard vendors all trying to gain 140 character “leadership” in a rapidly growing seller marketplace.
Whereas, tools and their visually predictive capabilities are wonderful additions to an arsenal of corporate software, there are some prerequisites which must be addressed before those first RFI’s hit the street. To properly frame the challenges and confusions within the markets, an informal outreach to decision makers produced the following snappish reactions:
- How does the inclusion of analytical frameworks and measures improve the performance of high-value / high return processes and those personnel within these operations? What about delegated decision making and due diligence or discovery? Can it help with the hidden risks and changing credit skills that demand knowledge – not just tools?
- If our organization utilizes innumerable spreadsheets for decision making, does the adoption and adaptation of an enterprise solution require a cultural shift (e.g., the prohibition of “dueling” spreadsheets and / or localized data marts)?
- If we are already using scorecards, BI tools, dashboards, reporting, mining tools, databases, and content consultants, how does the adoption of a “new analytical framework” make this any simpler – or cost effective? Is this yet another net add to the base budget?
- How can a strategy of programs and underlying project actions be really tied to results and profits driven by the aggregation of “new fangled” analytics? What is the measurable bottom line impact?
- How can we permanently change the underlying processes using adaptable analytical solutions? Don’t we first have to reengineer our enterprise using PPT (people, process, and technology) in that order?
- What keeps me awake are our disparate solutions, the ability to state with 100% confidence the integrity of the results, the STP of informational sources, various “systems of record,” regulatory confidence, and the auditability of ever changing analytical aggregating teams. How is that for a start? Will another layer really help me gain the confidence and overcome the internal political challenges?
- Is there really anyone who has a better answer or real world centers of excellence that help deal with my problems today – loss mitigation, REO, foreclosures, workouts, government oversight, and more as I try to make a profit? Will analytics really help? How and when?
Indeed the aforementioned, paraphrased reservations may be daunting for those who are passionate about the future of analytics. Regarding the decision makers, they have historically heard business and technological boasts over the years, and for now, analytics merely represent a new chapter in a familiar book. Whereas, the on-going 26 month global financial crisis has left many of corporate competitors in declining decay, there are FMG visionaries who truly believe analytics may provide a conduit for rapid redefinition or elimination of antiquated SOP’s. They are thinking big – but starting small.
Iterate, While You Orchestrate
As a senior finance person recently stated, “I don’t have time to build an ’end-all’ analytical roadmap. We have operational actions that are far more important to our financial health and delivery performance. We can’t spend months building a comprehensive and detailed design or architecture that is supplanted within the next 45 days.”
It should be noted that the finance person was very positive on the use of analytics to help assess and improve their current priorities – customer retention, product satisfaction, M&A post-deal integration, BPO / KPO enterprise initiatives, and yes, financial reporting and soundness. It is just that the tolerance for another intellectually stimulating plan was beyond their ability to support its traditional academic creation (potentially resulting in large binders of expensive approaches), if it could offer no pragmatic and direct assistance for today’s complex realities.
As a result, an oxymoronic situation is created where you have to measure to improve, but you don’t have time to overtly determine what to measure. So frequently organizations measure everything and trust the answer will fall out from the atomic elements. Sound familiar? Will consistent organizational results be established with disjointed approaches and products?
The solution? The answer fundamentally resides with the repurposing of existing business planning methods, leveraging of predefined industry analytical profiles, and the detailed techniques contained within agile software frameworks – aka leverage what works and augment. The keystone of success is how all the segments are assembled to meet the needs of the organization, and the requirements dictated to any analytical roadmap developed. Like the conductor of an orchestra, it will be up to the organization to determine the “who, why, where, what, and how.”
This new leader, a Chief Analytics Officer (CAO), will have to balance theory and vendor promises with their organizations’ (i.e., orchestra) ability to produce measurement results. Simply stated, if the orchestra cannot do scales, then it will be unable to perform Beethoven’s Symphony No. 5 with any skill regardless of how new and shinny their instruments may be.
The CAO embodies a new role within the enterprise transcending the traditional IT functions, while representing an unwavering responsibility to meet tactical and strategic operational mandates. As a conductor, the CAO role involves strategy, financial understanding, market and competitive prowess, and technical abilities to manage the often competing internal groups and external vendors.
More will be written about the CAO in future articles. But rest assured that a new leadership role and “musical score” is being carved out of the traditional FMG corporate granite. It is a role that will have a lasting and rising impact on the industry for the next decade. The CAO is the only one that can bring trust to the enterprise and validation to a growing set of constituencies all seeking to influence business models and industry behaviors. The industry skepticism will be driven out with success and a cost-effective approach that meets the constantly changing enterprise needs.