Basel III and IT Implementation Overview

The aim of this blog is to provide a brief overview of Basel accords which provides financial supervisory controls at broader level in the global financial market and brief IT Implementation steps to accomplish for BCBS 239 regulatory requirements. I am relying on my financial & accounting academic background and learnings & experience with the financial clients in my consulting world, while I profess my career as an IT professional.

Basel

Basel Committee on Banking Supervision (BCBS) based in Switzerland was created in 1974 to establish standards on regulation and supervision for SIB banks. The first major accord Basel-1 in 1988 was published to provide supervisory and regulatory controls for banks in G-10 countries after several International Banks faced heavy losses on account of closure of German Bank Herstatt and Franklin National Bank of New York whose foreign exchange exposure was more than 3 times that of their capital and found this issue more as a symptomatic pattern among other major international banks.

Over the period, there were major and minor accords created by BCBS & Financial Stability Board (FSB) to provide for fair play, regulatory requirements based on firms risk exposure, management and their appetite. Among various accords Basel-III so far is a complex package that supersedes its earlier versions including Basel –I and Basel-II. The growing economies of Asia and its influence on the financial and economic activities has also prompted them to expand the landscape from G-10 to G-20 countries and today more banks from 140 countries follow the regulatory requirements.

Basel accord is not just a recommendation but a package of regulatory controls aimed at Systemically Important Financial Institutions (SIFI) of both local and global organizations. In normal parlance, common banking activities like lending, investments involves risk exposure, and the willingness or the appetite for risk depends upon its infrastructure reach and capital strength, to drive its core and secondary commercial activities.

These activities results in the creation of different types of risk (Operational Risk, Credit Risk, Interest Risk, Liquidity Risk, Market Risk and other risks).  Strong and solid Governance & Controls provide stability to their operations to understand both inherent and residual risks.These risks can be originated internally and externally by different pillars of the heterogeneous economies and organizations have to take appropriate risk mediation steps to overcome these potential risks and its survivability while limiting its collateral damages.

Basel accord emphasizes in creating liquidity, capital adequacy, operations leverage in the global economy with host of other measures aimed at providing stability to avoid another financial meltdown.

Blame Game and Cause for Financial meltdown

There were many fingers that pointed out by eminent people for the cause of this meltdown right from accusing few CEO’s greed to lack of knowledge or even understand to the basic question in the bank wide transactions as simple as “who is who”, “who owns whom” and “who owns what” with clarity.

There were some who have indicated that lack of corporate governance structure and absence of precise and intuitive corporate management language which failed them to understand, monitor and control the fancy and complex products that were put in the market abetting the financial collapse. There are others who argue that letting down  Lehman "a too big to fail" institute caused and exacerbated the collapse with severe collateral damages. Rating companies attesting better rankings to a "Junk" instruments based on the incorrect assessments of financial statements also played a role in the crisis.

BASEL-I, 1988

This was the first major accord where BCBS provided definitions on the classification of Bank’s Capital and set certain minimum requirement standards. The Tier-1 and Tier-2 Capital for all International Banks emphasized the banks to maintain a minimum of 8% of its Risk Weighted Assets (RWA) to avoid financial failures on account of closures of German and American bank due to their overexposure on foreign exchange in relation to their capital adequacy.

BASEL-II 2004

Superseded BASEL-I in the risk and capital management requirements by further emphasizing on the adequacy requirements to the exposure of risk in their businesses of lending, investment and trading. Some of the key takeaways from this accord are as follows:

• Regulatory compliance should not become a sore point among the international banks on their competitiveness to operate with big banks
•  Capital adequacy was considered as a risk sensitive function with greater the risk, more capital needs to be held by the banks to maintain its solvency
• Emphasis was made on Credit Risk, but left to individual banks to manage other major risks like Operational Risk, Market Risk on their own
•  Emphasis on greater disclosure requirements twice a year, so regulatory bodies can monitor the various adequacy requirements and also enable assessments by analysts, investors, international financial bodies and other banks to showcase the effective corporate governance of individual banks among other details on
• Details on Risk Exposure & Risk Assessment Process
•  Capital Adequacy requirements and their validations

BASEL-III 2010

Accord was revisited after the financial meltdown in 2007-2008 that revealed additional financial regulations needed to be in place towards Capital Adequacy Requirements (CAR), Stress Testing, Funding Stability and Market Liquidity Risks, Liquidity Coverage Ratio (LCR) to effectively and Banks Leverage ratios.

It also defined Common Equity requirements as a Well Capitalized, Adequate Capitalized, Inadequate Capitalized under different Tiers (CET-1, CET-2, and CET-3) and High Quality Liquid Assets (HQLA) at different levels (Level 1, 2A, and 2B). 

Another major component of this accord defined was to maintain a net stable funding profile in relation to their on-and off- balance sheet activities to reduce the funding disruptions and its impact to liquidity. Finally, the focus is also able to identify KRI Key Risk Indicators (KRI) and build Risk and Control Self-Assessment (RCSA) methods to identify inherent and residual risk exposures.

Basel Summary

In Summary, Basel attempted to create a harmonized set of quality, consistent policy accords that aids in the better management of financial operations of SIFI’s complex products by increasing reserves based on key ratios and slew of measures. It created new Counterparty Credit Risk (CCR) ratios, Liquidity Risk Ratios like Liquidity Coverage Ratios (LCR), NSFR (Net Stable Funding Ratio) and Collateral risk ratios for Quality coverage such as Initial Margin (IM), Variation Margin (VM) among others.

It also created additional buffer requirements like Capital conservation buffers to be infused in during normal period and to be utilized during stress periods. Some other key components like Stressed VaR (SVaR), Trading book positions and changes to general, and specific Market Risk Models with respective to changes in parameter values were also highlighted during stress and normal periods.

Basel regulatory compliance works hand in glove with other controlling agencies like Federal Reserve Bank, Financial Stability Board (FSB), Security Exchange Commission (SEC), International Organization of Securities Commissions (IOSCO), Regulatory Oversight Committee (ROC), Federal Deposit Insurance Corporation (FDIC) and many other International Regulatory bodies and Reserve Banks of native countries to build a customized version of requirements, ratios and timelines by which these accords needs can be implemented.

Business, IT and other professional folks are still working towards assessing the changes warranted to implement this complex package of rules and regulatory requirements. One may identify and group these requirements into 4 buckets:

1.       New Capital definitions and its adequacy requirements impacting Operational & Functional aspects of the Organization

2.       Creation of additional Buffers and its operations during normal and stress time windows

3.       Building and maintaining Leverage & Liquidity Ratios and its changes to the Operational and Functional system of the Organization

4.       Implementing CCR changes across US, EU and Asia for Global companies. This one I believe is bit more complex to implement as it transcends many areas of the institutions business model and geographies.

Some of the reasons for the financial meltdown were attributed to lack of comprehensive risk reporting and its aggregation abilities that fell short on its accuracy, reliability and timeliness. To address these and more, Basel also created a BCBS 239 document to be implemented by the SIFI’s with eye on creating a stable all-encompassing Risk Data Aggregation Reporting (RDAR) repository.

BCBS 239, Jan 2013 a regulatory document on “Principles for effective Risk Data Aggregation and Risk Reporting” was created by BASEL and FSB to provide guidance to enhance the bank’s ability to identify and manage bank wide risks. It consists of 14 principles to guide the banks to develop and build process and methods for a Risk MIS that provide Qualitative and Quantitative measures and reporting mechanism. These broad principles can be summarized as follows:

1.       Overarching Governance & Infrastructure: Build Strong Governance over bank's risk data aggregation capabilities, risk reporting practices and IT capabilities. It should cover design, build and maintenance of data and IT architecture to fully support its data aggregation capabilities and risk reporting at all times.

2.       Risk Data Aggregation Capabilities: Build adequate system controls in the generation of risk data with capability to quickly adapt to changes in the key risk identification and decision making arrangements and regulatory and compliance requirements.

3.       Risk Reporting Practices: System should be able to provide forward looking accurate, reliable, timely & useful risk distribution reports and assessments on risk with build in procedures to monitor and control.

Link to BCBS Principles Guidelines

www.bis.org/publ/bcbs239.pdf

Common IT Challenges among SIB’s.

1.       There are many silos of data in heterogeneous platforms with different aging and reporting capabilities

2.       Lack or Limited Master & Reference Data across different domains (Operational Risk, Market Risk, Liquidity Risk, and Credit Risks) leaves big hole to validate it as single source of truth

3.       Minimum or lack of Governance bank wide to build a cohesive audit controls and corrective measures

4.       Lack of Data Quality inhibits reporting accuracy and many don’t see data as an asset and uncorrected data flows into other systems thus cascading the imperfection

5.       Different grains levels of data processed and stored for analysis and thus creates compatibility issues on its usage and reporting

6.       Many risk modeling are done outside the integrated systems with no loop back mechanism and often are out of synch and difficult to consolidate

7.       Latency issues in gathering and reporting across multiple channels thus missing on many windows of opportunity to address and fix the issues

8.       Many of the measures & metrics are created on assessments rather than being measured thus are not a good candidates for aggregation

9.       Lack of coordination & understanding of business needs between IT and Business and vice versa resulting in creation of many inefficiencies on productivity of resources leading to  time & cost overruns

10.   Lack of Matured Interactive Reporting Platform with Dashboards, Scorecards, Slicing/Dicing capabilities across many constructs or dimensions

The implementation of BCBS 239 should not be viewed just as a Data Management project but coordinated between Technology, Data Management & Governance and Risk Management Business teams with clear ownership and responsibilities among the stakeholders.

Implementation Steps in Building a Robust BCBS 239 Compliant System

I have read several times the principles and each time, I could make bit more meaningful sense on each reading. So here are some suggestions for both IT, Business and other stake holders.

• Understand clearly each of the BCBS 239 principles in totality with one principle at a time
• Create a game plan by organizing the task of the requirements with a bottom-up approach
•  Create an Information Governance Catalog of Labels and identify the stewards for each of those information
• Identify Risk Metrics and its related terms, Custom terms and its evolution with history to identify the changes and record them appropriately for compliance
• Create Business lineage of source, targets and reporting assets across different domains
• Create Data lineage of column level flow activity of source to targets across different data silos, transformation of expressions, flow activity trace, abstractions, derivations, STP, Data movement process like FTP and any touch points
• Profiling data both history and intermittent from time to time, updating the Information Governance Catalog for regulatory compliance
• Flatten the hierarchical risk metrics views with relationships across different constructs/dimensions as a Blue print for better understanding and grasp of its complexity
•  Create Metadata tables for expressions and its terms along with showing calculations precedence and expected intermediary and expected results
• Document models usage and its various algorithms

Options in Building RDAR (Data Virtualization)

As I have indicated earlier one of the reasons for the financial meltdown was inability in providing a single bank wide view of risks in timely fashions and providing consolidation of individual risk practices into an enterprise wide one. This has also made it difficult to monitor and identify systemic risk and provide for regulatory transparency.

Data Virtualization is one solution that is creating traction with many company’s which has 100’s of silos of data stores and multitude of heterogeneous database platforms with dynamic rules changes to be compliant.

Financial institutions can built single view of institution wide risks to better manage Market, Credit, Liquidity and Operational risks with data being pulled from multitude of sources like trading, portfolio applications, account systems and others in real-time for timely assessment. In addition many financial companies employ several financial analytical and research applications and these can also be combined for identifying trading opportunities and also address any regulatory compliance requirements.

On the horizon Financial Transaction Barcodes (LEI, UPI, UTI)

Just as a 9 digit routing number of bank can participate in a financial transaction like ACH and Wire transfer, global banks are working towards building a Legal Entity Identifier (LEI) that can be used in their financial transactions. The objective of BCBS regulators is to observe the buildup of enterprise risk and understand the capital adequacy across silos of business by aggregation within each financial institutions and identify systemic risk across global financial system.

This initiative has been tasked by Financial Stability Board (FSB) and is getting tested with complex derivative product like Swaps with billions of transactions both in US and EU. However the coding scheme used is still not up to mark as per the researchers and academicians to meet the BSBS regulators objective of aggregation. The mapping services for LEI still has gaps in parent/control/ownership hierarchies and its linkages to the issuer, obligor, counterparties and guarantee relationships.

Regulators are hoping this initiative would be able to create global identification system with Unique Product Identifier (UPI), Unique Transaction Identifier (UTI) along with LEI to reduce risk, lower cost and improve efficiencies in the middle office infrastructure by enabling the industry as a whole into digital age.

Conclusion:

I am excited at the outlook and the opportunities that this new Global Financial System brings to its stakeholders as they move cautiously and surely into digital world after a major crisis.

"We cannot solve our problems with the same thinking we used when we created them.”

Albert Einstein 

Supply Chain and its Strategies

Supply Chain is a vast and dynamic subject with many domain areas each intertwined with hierarchical relationships and is difficult to monitor, control and predict its inter and intra relationships and its influence on business objectives and goals. The Goal of Supply Chain Manager is to overcome these challenges and build a smooth and seamless operational business model.

I would like to use A.G. Lafley CEO of Procter & Gamble simple way of expressing the objective line for Supply Chain. Supply Chain’s objective should be able to provide a customer what they want, when they want at a competitive price while seamlessly managing the complex backend and frontend integration process encompasses the various domain areas of Buy, Make, Store, Deliver and Sell.

When you buy coffee or even on other end a tire or any clothing’s, the end product has already gone thru a series of steps right from procurement of raw materials à manufacturing process & schedulingàwarehouse inventory management & forecasting and risk management àtransport & route optimizationà retail shelf and finally into your hands. Feel free to add the Product Return process for additional complexity to the supply chain in reverse order.

This E2E process of managing the process of goods and services is reflected in Supply Chain Management involving some critical domain areas like Supply Chain Planning, Inventory & Order Management, Logistics and Risk & Mitigation steps for any disruptions.

Supply Chain Management objective goals in any given enterprise has been to plan, monitor and control efficiently the lowest order/purchase order cost; lowest landed cost; total cost of ownership and demand driven supply management.

Supply Chain Industry trends

My brief analysis on the 200+ number of Expo exhibit participants in this year’s 2015 Council of Supply Chain Management Professionals (CSCM) shows that 75% of them provide services in Supply Chain Solutions, Forecasts and Transportation & Distribution areas while 13% in Manufacturing, Planning & Sourcing and another 12% in Talent and Career. The reading and observation that I was trying to make is to indicate the significant and dominant focus areas the industry is seeking help in the Supply Chain.

Also most executives would be looking forward from these exhibitors besides cost savings is how they would be able to deliver value and improves their business outcomes in areas such as Supplier Relationship Management, Performance Management, Risk Management, Sourcing & Procurement and Planning and building Master Data Management with Supplier Segmentation.

In this blog, I would like to elucidate some solutions and strategies employed by practitioners and supply chain leaders based on my experience, readings and understanding of Supply Chain.

Supply Chain Integration (SCI) Strategies:

Here are some potential solution areas that many Supply Chain leaders and practitioners have been employing strategically with their clients. Japanese industrial practices lead the way in todays matured SCI strategies and they have professed that lot of wastage (“muda” in Japanese) is mainly caused due to fragmented supply chain configurations both within and among intra parties. The Value Based Management (VBM) framework further accentuated the need to improve the bottom line and thus SCI became an integral part of the corporate strategies.

SCI has seen many improvements and innovations over the years like TPS (Toyota Production System), JIT (Just In Time), EOQ (Economic Order Quantity), MRP (Manufacturing Resource Planning), Continuous Replenishment that led to VMI (Vendor Managed Inventory) and host others. However each company depending upon their business model adopt either semi integrated or fully integrated approaches with levels of integration from tight to being intensive within selected domain areas.

Relationship Management

Supplier Relationship Management has moved on from being a mere transactional based relationship to more collaborative arrangement to increase business value, reduce demand supply complexities and importantly shift from lowest price to TCO (Total Cost of Ownership). A relationship is always a continuously evolving one and many companies constantly update their own profile with the suppliers who also may be going changes either thru vertical or horizontal integration with mergers and acquisitions and assigning newer prioritizations and preferences.

Supplier Stratification & Integration Strategies

The global merchandise trade (imports/exports) since 1990 has jumped from a mere 2.3 trillion dollars in 1990 to 18.3 trillion dollars in 2014. Global sourcing is a key focus area today for many organizations big or small and thus making SCM to constantly reshape its relationship and realign its strategies.

The growth in trade led many companies in the Supply Chain to build a strong relationship among its suppliers, stratified and prioritized on a collaborative basis rather than merely on transactional basis. In this relationship the capabilities of the supplier is to be developed on a continuous basis to meet the proactive needs of its customers.

This has also lead many companies to focus on their core strengths and that also gave way to “Outsourcing” paradigm both in products from “Make” to “Buy” and Services to increase market share and create formidable global footprint while being competitive.

This major alignment led to the creation of Maturity Model of 3^rd Party Service Providers (3PSP’s) and OEM’s based on their capabilities. However there were some major concerns that were expressed on this alignment mainly on disruption of supplies and its associated risks. To addresses this risk, companies are approaching in a phased manner rather than as a big bang approach.

• Internal Cross Functional Integration
• Backward Integration with first tier Suppliers
• Forward Integration with valued first tier Customers
• Complete forward and backward integration from suppliers to customers

 Building Logical Sharing Community for Logistics

SCM leaders have also built LSC (Logical Sharing Community) with 3/4/5PL (Third party Logistics Providers) to integrate and provide for logistical services. These collaborative arrangement range from sharing of network infrastructure services, production platforms, shared warehouse & distribution centers, shared transportation agreements, vendor managed inventory (VMI) to building consortiums to provide for better triangulation of the ecosystem and keep in abeyance the Organizational inertia and keep the industry’s clock-speed ticking.

Logistics is a critical discipline in the supply chain and covers various functions including procuring, warehousing and distribution of products effectively utilizing appropriate channels to its end customers.

3/4/5 PL parties are defined from the perspective of degree of responsibilities that they perform with their core competencies in managing, controlling and utilization of their own or contracted assets for a smooth flow of products across different functions of logistics.

Reverse logistics is also another growing area that relates to the functions required to address the Goods Returns, Repairs, Recycle or dispose of products in effective way.

There are defined goals in Logistics like Response time, Inventory expenses, Shipment consolidation with continuous improvement for which strategies are built and often times as coordinated planning efforts with suppliers & customers in the integrated supply chain systems.

One of the key strategies professed by implementers is to build near real-time information sharing system with improved collaboration to track the movement of products with RFID (Radio Frequency Identification) and GPS. This is to helps meet its objectives of lower cost, lower inventory, reducing stock outs, reducing pooling risks and providing consistent ordered deliveries to its customers.

Performance Management

Performance metrics which were focused on financial perspective has moved more towards understanding in totality as business model called SCM. Practitioners have created Metric Maturity models utilizing standardized frameworks like SCOR™ with its 550 metrics that are hierarchical, controllable and coherent in nature and that can be integrated with different SCM domains to meet the Corporate goals and objectives.

Utilizing BI (Business Intelligence) tools, enables the business users to build these holistic and integrated metrics as dashboards and scorecards with drill down capabilities to its sub metric levels and also get a view point across various constructs or dimensions to its lowest grain. Companies utilize these insights to identify bottlenecks and opportunities to put forward strategies for growth and competitiveness.

Supply Chain Risk Management

The 2011 Tsunami and the unfortunate nuclear leak event happened at Fukushima Daiichi, in Japan and the shutdown of several manufacturing plants within its 20km area as non-inhabitant area, had destructive consequences on the supply chain for thousands of global companies. For months the global shortages for many industries for components produced in these affected regions led to severe shortages of end products to B2B and B2C customers leading to loss of billions of dollars on sales and lost opportunities.

Many of the Supply chain Managers re-emphasized on three aspects of disruptions management.

·        Controlling, Managing disruptions and prevent the reoccurrences

·         Monitoring disruptions and predicting before they occur

·         Action plan for any major and minor disruptions  

Some of the mitigation steps that were advanced by implementers was to relocate from high risk zones to safer ones, analyzing the disruptions and modeling them for reducing the disruptions impact, creating extra capacity in the system and flexibility in the supply chain with interchangeability of the products.

A new set of data metrics were created called KRI (Key Risk Indicators) to identify and monitor trends and predictions for any disruptions and take necessary mitigation steps. There is lot of research that is currently being undertaken by many academicians and industry to identify and understand the relationships on major events and model them, so they would be able to predict the events even before they occur, so the impacts of potential disruptions are mitigated.

Forecasting

Forecasting in Supply Chain is an important tool that is used by Supply Chain integrators to predict and manage the vagaries of uncertainties that are often systemic in nature in different domain areas such as sourcing risk, production costs and customer demand. 

These forecasting tools with specialized software enables the customers to build Qualitative, Time Series, Causation and Simulated scenarios to help and evaluate different options. Indicators help in the study of forecasts and its influence on planning aspects in supply chain by establishing and building performance and error measures.

The quality and accuracy of these forecasts has greater dependencies on its depth and width of historical data used in many of its Time Series, Causation and Simulated scenarios. Inaccurate forecasting is a crushed success, because when production level and supply levels are not in line with customer demands in a given time window, companies get crushed with higher inventory carrying costs and obsolescence or lost opportunities.

Analytics

Supply Chain Managers have to wrestle with many global economic challenges of instabilities, uncertainties besides unpredictable customer demand volatility. The shorter product life cycles, supply chain disruptions, and limited visibilities to real time metrics add to their woes in today’s Operational environment. It becomes very imperative that Business Analytics with performance metrics utilizing their ERP systems with different modules like Inventory, Order Management, Warehouse, Finance, Procurement, Manufacturing, Logistics, Supply Chain Planning, Marketing and Sales needs to be deployed in near real time to provide the required information for planning, forecasting and execution.

It is also observed from various research and surveys that companies which have built Analytics are 3 times more likely to outperform the companies who have just adopted analytics and 5 times more with companies who rely on intuitions and business processes alone.

Integrators emphasize that Analytics needs to be employed across different domain groups not necessarily all at one go, but with a clear roadmap to deliver real business results and value rather than as mere technology platform or set of tools.  Some integrators may just focus primarily on S&OP (Sales & Operation Planning) an integrated business management process area and mature it before moving into other areas but again it depends upon individual company’s maturity levels in the analytics space.

A road map for Business Analytics should built to identify and mature along the line from being just a Descriptive Analytics (Insights to show how are we doing) to Diagnostic Analytics (Why are we doing, what we are doing), Predictive Analytics (What is likely to happen) and finally Prescriptive Analytics (What should we be doing) as a step ladder across time lines and value proposition axis.

Conclusion:

Today’s data driven Supply Chain companies with their nimble Integrated Suppliers are more likely to  overshoot the older giants if they are slow in adopting and adapting these newer frontiers in an orchestrated manner.

A Prudent Business Analytic platform

Analytics today are vital to triumph in any business functions and it’s no wonder acquiring or building Business Analytics platform seems to be today’s mantra for many Enterprises. 

However to build analytics platform one has to truly understand and answer the broader questions like  a) how do we accomplish the analysis, b) how decisions should be made and c) how technologies should be evaluated and implemented to avoid half baked solutions with its negative side effects.

These side effects can be minimized if enterprises were to initiate an assessment to understand their current platform maturity levels. One way is to view how much of their current operations is supported by different types of analytics namely Descriptive (What happened), Diagnostic(Why happened), Predictive (What will happen) and Prescriptive (How to prevent). These can be categorized further from value add perspective as providing Hindsight (Observation), Insight (Comprehension) and Foresight (Prudence) in the order of magnitude of complexities as well as steps towards higher maturity progression.

My aim in this blog is to emphasize that enterprises have to take a holistic approach in building or extending Analytics for their Data Warehouses or Native Repositories first and create Data Management Solutions for Analytics that utilizes both internal and external data.

There are many technologies both in hardware and software that implementer's can choose from with various degrees of mixes to provide an  enterprise level analytics platform. Some companies prefer to align with single vendor to obtain BOB (Best of Breed) products across their entire stack thus avoiding the fear of difficulties of having to bring and maintain different skills sets while others prefer to go with a different approach of getting the Best of BOB in the market from across vendors to integrate these products and technologies and build seamless platform.

Both these extreme positions or any varied combinations have to still overcome many integration issues with their enterprise data while providing plumbing activities (ETL/ELT) for data movements before it can be build as a cohesive and a high performance dominant platform. We also hear that many platforms sooner than later, plunge both on storage capacity as well as on performance with storage capacities overshooting their estimates and missing SLA's (Service Level Agreements), benchmarks on business users usage demand and requests.

On the horizon towards a Solution

Today we hear implementer's are vying with a concept what Gartner calls it as “Best Fit Engineering” (BFE). In this mix, the minimum required technology for each function is considered for an appropriate purpose and is therefore much more likely to exhibit a lower cost and still retain good performance.  Some of the areas that I believe are major areas where implementer's are considering are as follows:

Data Virtualization layer (DVL)

Implementing Data Virtualization layer over data stack creates a LDW (Logical Data Warehouse). This LDW would minimize the most expensive data movements (ETL/ELT) and expose the data requirements from different silos large and small by creating a repository of metadata layer to meet the data demands in format, scope across different channels.

Big Data Platform

Big Data platform is no more a buzz word or a hype nor an aspiration but a certainly a catalyst in providing many beneficial use cases for data analytics in performing exploration by utilizing it as ‘sandboxes’ for offloaded history from warehouses and external data.

Data Lakes

Data lakes can be deployed, managed and scaled for its computing needs and storage by building in public or private clouds for both external and internal data. Data lakes provides the much needed agility in terms of responsiveness and flexibility to deliver faster insights. The other big advantage in Data lakes is it does not restrict to pre-definition of schemas and can be propagated from different silos in their original formats. Organizations can utilize the BI Self-Serve tools much more effectively to prepare data for analysis in Data lakes while aligning to business needs and provide evidence based data discovery to support decision making.

Data Sciences

Build Data Sciences as a discipline within Organizations and nurture data scientists who can play pivotal role in sharing data science discoveries while processing operational applications data in the enterprise planning efforts and its executions. Nurturing and supporting this step could lead in creating building blocks for Graph databases that could also abridge gap for its usage between commonly used BI solutions by less skilled personnel.

Observation

There were many disruptive technologies we have seen in past and at each juncture it helped the IT folks to build faster, modular yet powerful and flexible platform and applications, however in the BI space the shift of balance of power is moving from IT to Business folks with ambitious Self Serve Service platform offerings.

Building Blocks for Metrics and KPI's

Create Metrics to Drive Your Business Smoothly

There are many Companies and Enterprises that have isolated metrics providing a narrow view of what is happening on the ground and some have complex hierarchical ones that are mapped to provide lineage to the root cause analysis and far few have capabilities to slice and dice the metrics across different constructs or dimensions.

Imagine if I ask, how many of them have built-in metrics that provides an E2E perspective that are inter-related across different functional domain areas and if I harp further, what about metrics that are intertwined across their LOB (Line of Businesses).

The C level and Senior level management would love to see such metrics presented as flattened views with Dashboards, so they could check each of them periodically to crisscross and validate the overall health of their Organization’s operations and build appropriate programs, initiatives to drive their business objectives and goals and monitor.

Yes, we all want such reporting environment to have been built as of YESTERDAY.  To create such a reporting environment there is no easy tool or software from vendors or even have panacea pill that can be consumed to cure this illness.

Rather what is required is an engagement to build a user friendly Reporting Platform that can provide meaningful and insightful Reports and Analytics to support Operating Strategies of the Company with entrenched Business Processes to create consistent value of drivers on continuous basis with portfolio of metrics that drives and sustains Business Strategies and Initiatives.

I know these are lot of mouthful of words and phrases, but I will try and attempt to write in this blog some concrete understanding of basic blocks required for Metrics, KPI's and Scorecards that could be leveraged to build and efficient and effective reporting and analytical platform.

Create Building blocks of metrics using validated measures

Metrics are derived out of measures such as # of Customers, Total Sales, and Total Revenue etc. These can be simple ones or combined with other metrics to create complex metrics and also as hierarchical in nature. These are usually build around constructs or dimensions to enable Users to slice or dice them from higher to lower grain data or pivot them across different facets for insights.

Define, Create a Template Framework for Metrics

Metrics can be grouped and classified according to its domain areas such as Inventory, Supply Chain, Order Management, Sales, Health, and Progress or by context on Organization performance on Costs, Returns, Growth, Profitability, and Cycle. With litany of hundreds and thousands of measures and metrics, many Companies create Custom template frameworks for metrics or rely on some Industry Standards like SCOR™ Supply Chain Framework to group and classify and build metrics. Some major software vendors are offering OOTB (Out Of The Box) metrics as part of their Software Analytics Platform across different domains.

Organizations have many disconnected projects with metrics to validate its effectiveness and often they are singular in nature and don’t line up with specific business objectives and goals and thus cannot be related or mapped for an overall business value.

Frameworks can provide a 3D dimensional map of a complex view of metrics in a flattened structure like a blue print, so it’s easier to view and understand its inner workings and relationships.

Define KPI’s and Balanced Scorecards across Organization Functional Domain activities

Key Performance Indicators (KPI’s) are measurement indicators that supports Organizations Objectives and goals and provide key indicative performance aspects. KPI’s are generally calculated as ratios to help the business in their decision making process.  

Several key metrics are grouped into different groups as Sales KPI’s, Marketing KPI’s, Retail KPI’s, Supply Chain KPI’s, and Financial KPI’s at broader level. KPI’s are also Categorize into Strategic, Tactical and Operational as part of measurements identified by business units to align with its strategies.

Most KPI’s are siloed in nature within each functional domain areas with conflicting objectives from an E2E perspectives. Manufacturing floor would like to have Stable volumes with higher lead time while logistics would prefer low and mean volumes with less lead time while Sales and Customer domain areas would like have high availability with higher responsive cycle times. When you bring the financial domain they would like to have lower cost, higher turnover, lower inventory and higher cash to cash cycle times.

Balanced Scorecards are traditionally used to track and keep this conflicting and competing objectives in synch from different perspectives to harness the KPI’s effectively. There are no hard and fast rules however one could utilize certain thumb rules for an effective Balanced Scorecard.  

• Build a proactive cause and effective map like the Ishikawa
• Align your strategies and processes to this map
•  Identify KPI’s that are Strategic, Tactical and Operational and monitor them along the map
•  Build continuous improvement processes for an effective decision making along the map

As Peter Drucker a celebrated Management Guru said “You can’t manage what you can’t measure”.