Category Archives: Governance, Risk and Compliance
The Rising CFO is Increasingly Business Oriented
At the CFO Rising West Conference on October 30th and 31st, there were sessions on managing capital expenditures, completing an IPO, and even managing margin and cash flow. However, the keynote presenters did not spend much of time on these topics. Instead, they focused on how CFOs need to help their firms execute better. Here is a quick summary of the suggestions made from CFOs in broadcasting, consumer goods, retail, healthcare, and medical devices.
The Modern CFO is Strategic
The Broadcasting CFO started his talk by saying he was not at the conference to share why CFOs need to move from being “bean counters to strategic advisors”. He said “let’s face it the modern CFO is a strategic CFO”. Agreeing with this viewpoint, the Consumer Goods CFO said that finance organizations have a major role to play in business transformation. He said that finance after all is the place to drive corporate improvement as well as business productivity and business efficiency.
CFOs Talked About Their Business’ Issues
The Retailer CFO talked like he was a marketing person. He said retail today is all about driving a multichannel customer experience. To do this, finance increasingly needs to provide real business value. He said, therefore, that data is critical to the retailer’s ability to serve customers better. He claimed that customers are changing how they buy, what they want to buy, and when they want to buy. We are being disrupted and it is better to understand and respond to these trends. We are trying, therefore, to build a better model of ecommerce.
Meanwhile, the Medical Devices CFO said that as a supplier to medical device vendors “what we do is compete with our customers engineering staffs”. And the Consumer Goods CFO added the importance of finance driving sustained business transformation.
CFOs Want To Improve Their Business’ Ability To Execute
The Medical Devices CFO said CFOs need to look for “earlier execution points”. They need to look for the drivers of behavior change. As a key element of this, he suggested that CFOs need to develop “early warning indicators”. He said CFOs need to actively look at the ability to achieve objectives. With sales, we need to ask what deals do we have in the pipe? At what size are these deals? And at what success rate will these deals be closed? Only with this information, can the CFO derive an expected company growth rate. He then asked CFOs in the room to identify themselves. With their hands in the air, he asked them are they helping to create a company that executes or not. He laid down the gauntlet for the CFOs in the room by then asserting that if you are not creating a company that executes then are going to be looking at cutting costs sooner rather than later.
The retailer CFO agreed with this CFO. He said today we need to focus on how to win a market. We need to be asking business questions including:
- How should we deploy resources to deliver against our firm’s value proposition?
- How do we know when we win?
CFOs Claim Ownership For Enterprise Performance Measurement
The Retail CFO said that finance needs to own “the facts for the organization”—the metrics and KPIs. This is how he claims CFOs will earn their seat at the CEOs table. He said in the past the CFO have tended to be stoic, but this now needs to change.
The Medical Devices CFO agreed and said enterprises shouldn’t be tracking 150 things—they need to pare it down to 12-15 things. They need to answer with what you measure—who, what, and when. He said in an execution culture people need to know the targets. They need measurable goals. And he asserted that business metrics are needed over financial metrics. The Consumer Goods CFO agreed by saying financial measures alone would find that “a house is on fire after half the house had already burned down”. The Healthcare CFO picked up on this idea and talked about the importance of finance driving value scorecards and monthly benchmarks of performance improvement. The broadcaster CFO went further and suggested the CFO’s role is one of a value optimizer.
CFOs Own The Data and Drive a Fact-based, Strategic Company Culture
The Retail CFOs discussed the need to drive a culture of insight. This means that data absolutely matters to the CFO. Now, he honestly admits that finance organizations have not used data well enough but he claims finance needs to make the time to truly become data centric. He said I do not consider myself a data expert, but finance needs to own “enterprise data and the integrity of this data”. He said as well that finance needs to ensure there are no data silos. He summarized by saying finance needs to use data to make sure that resources are focused on the right things; decisions are based on facts; and metrics are simple and understandable. “In finance, we need use data to increasingly drive business outcomes”.
CFOs Need to Drive a Culture That Executes for Today and the Future
Honestly, I never thought that I would hear this from a group of CFOs. The Retail CFO said we need to ensure that the big ideas do not get lost. We need to speed-up the prosecuting of business activities. We need to drive more exponential things (this means we need to position our assets and resources) and we need, at the same time, to drive the linear things which can drive a 1% improvement in execution or a 1% reduction in cost. Meanwhile, our Medical Device CFO discussed the present value, for example, of a liability for rework, lawsuits, and warranty costs. He said that finance leaders need to ensure things are done right today so the business doesn’t have problems a year from today. “If you give doing it right the first time a priority, you can reduce warranty reserve and this can directly impact corporate operating income”.
CFOs need to lead on ethics and compliance
The Medical Devices CFO said that CFOs, also, need to have high ethics and drive compliance. The Retail CFO discussed how finance needs to make the business transparent. Finance needs to be transparent about what is working and what is not working. The role of the CFO, at the same time, needs to ensure the integrity of the organization. The Broadcaster CFO asserted the same thing by saying that CFOs need to take a stakeholder approach to how they do business.
In whole, CFOs at CFO Rising are showing the way forward for the modern CFOs. This CFO is all about the data to drive present and future performance, ethics and compliance, and business transparency. This is a big change from the historical controller approach and mentality. I once asked a boss about what I needed to be promoted to a Vice President; my boss said that I needed to move from a technical specialist to a business person. Today’s CFOs clearly show that they are a business person first.
Solution Brief: The Intelligent Data Platform
CFOs Move to Chief Profitability Officer
CFOs Discuss Their Technology Priorities
The CFO Viewpoint upon Data
How CFOs can change the conversation with their CIO?
New type of CFO represents a potent CIO ally
Competing on Analytics
The Business Case for Better Data Connectivity
Every fall Informatica sales leadership puts together its strategy for the following year. The revenue target is typically a function of the number of sellers, the addressable market size and key accounts in a given territory, average spend and conversion rate given prior years’ experience, etc. This straight forward math has not changed in probably decades, but it assumes that the underlying data are 100% correct. This data includes:
- Number of accounts with a decision-making location in a territory
- Related IT spend and prioritization
- Organizational characteristics like legal ownership, industry code, credit score, annual report figures, etc.
- Key contacts, roles and sentiment
- Prior interaction (campaign response, etc.) and transaction (quotes, orders, payments, products, etc.) history with the firm
Every organization, no matter if it is a life insurer, a pharmaceutical manufacturer, a fashion retailer or a construction company knows this math and plans on getting somewhere above 85% achievement of the resulting target. Office locations, support infrastructure spend, compensation and hiring plans are based on this and communicated.
So why is it that when it is an open secret that the underlying data is far from perfect (accurate, current and useful) and corrupts outcomes, too few believe that fixing it has any revenue impact? After all, we are not projecting the climate for the next hundred years here with a thousand plus variables.
If corporate hierarchies are incorrect, your spend projections based on incorrect territory targets, credit terms and discount strategy will be off. If every client touch point does not have a complete picture of cross-departmental purchases and campaign responses, your customer acquisition cost will be too high as you will contact the wrong prospects with irrelevant offers. If billing, tax or product codes are incorrect, your billing will be off. This is a classic telecommunication example worth millions every month. If your equipment location and configuration is wrong, maintenance schedules will be incorrect and every hour of production interruption will cost an industrial manufacturer of wood pellets or oil millions.
Also, if industry leaders enjoy an upsell ratio of 17%, and you experience 3%, data (assuming you have no formal upsell policy as it violates your independent middleman relationship) data will have a lot to do with it.
The challenge is not the fact that data can create revenue improvements but how much given the other factors: people and process.
Every industry laggard can identify a few FTEs who spend 25% of their time putting one-off data repositories together for some compliance, M&A customer or marketing analytics. Organic revenue growth from net-new or previously unrealized revenue is what the focus of any data management initiative should be. Don’t get me wrong; purposeful recruitment (people), comp plans and training (processes) are important as well. Few people doubt that people and process drives revenue growth. However, few believe data being fed into these processes has an impact.
This is a head scratcher for me. An IT manager at a US upstream oil firm once told me that it would be ludicrous to think data has a revenue impact. They just fixed data because it is important so his consumers would know where all the wells are and which ones made a good profit. Isn’t that assuming data drives production revenue? (Rhetorical question)
A CFO at a smaller retail bank said during a call that his account managers know their clients’ needs and history. There is nothing more good data can add in terms of value. And this happened after twenty other folks at his bank including his own team delivered more than ten use cases, of which three were based on revenue.
Hard cost (materials and FTE) reduction is easy, cost avoidance a leap of faith to a degree but revenue is not any less concrete; otherwise, why not just throw the dice and see how the revenue will look like next year without a central customer database? Let every department have each account executive get their own data, structure it the way they want and put it on paper and make hard copies for distribution to HQ. This is not about paper versus electronic but the inability to reconcile data from many sources on paper, which is a step above electronic.
Have you ever heard of any organization move back to the Fifties and compete today? That would be a fun exercise. Thoughts, suggestions – I would be glad to hear them?
Do We Really Need Another Information Framework?
The EIM Consortium is a group of nine companies that formed this year with the mission to:
“Promote the adoption of Enterprise Information Management as a business function by establishing an open industry reference architecture in order to protect and optimize the business value derived from data assets.”
That sounds nice, but we do really need another framework for EIM or Data Governance? Yes we do, and here’s why. (more…)
Gartner’s official definition of Information Governance is “…the specification of decision rights and an accountability framework to encourage desirable behavior in the valuation, creation, storage, use, archival and deletion of information. It includes the processes, roles, standards, and metrics that ensure the effective and efficient use of information in enabling a business to achieve its goals.” It therefore looks to address important considerations that key stakeholders within an enterprise face.
A CIO of a large European bank once asked me – “How long do we need to keep information?”
Keeping Information Governance relevant
This bank had to govern, index, search, and provide content to auditors to show it is managing data appropriately to meet Dodd-Frank regulation. In the past, this information was retrieved from a database or email. Now, however, the bank was required to produce voice recordings from phone conversations with customers, show the Reuters feeds coming in that are relevant, and document all appropriate IMs and social media interactions between employees.
All these were systems the business had never considered before. These environments continued to capture and create data and with it complex challenges. These islands of information that seemingly do not have anything to do with each other, yet impact how that bank governs itself and how it saves any of the records associated with trading or financial information.
Coping with the sheer growth is one issue; what to keep and what to delete is another. There is also the issue of what to do with all the data once you have it. The data is potentially a gold mine for the business, but most businesses just store it and forget about it.
Legislation, in tandem, is becoming more rigorous and there are potentially thousands of pieces of regulation relevant to multinational companies. Businesses operating in the EU, in particular, are affected by increasing regulation. There are a number of different regulations, including Solvency II, Dodd-Frank, HIPAA, Gramm-Leach-Bliley Act (GLBA), Basel III and new tax laws. In addition, companies face the expansion of state-regulated privacy initiatives and new rules relating to disaster recovery, transportation security, value chain transparency, consumer privacy, money laundering, and information security.
Regardless, an enterprise should consider the following 3 core elements before developing and implementing a policy framework.
Whatever your size or type of business, there are several key processes you must undertake in order to create an effective information governance program. As a Business Transformation Architect, I can see 3 foundation stones of an effective Information Governance Program:
Assess Your Business Maturity
Understand the full scope of requirements on your business is a heavy task. Assess whether your business is mature enough to embrace information governance. Many businesses in EMEA do not have an information governance team already in place, but instead have key stakeholders with responsibility for information assets spread across their legal, security, and IT teams.
Undertake a Regulatory Compliance Review
Understand the legal obligations to your business are critical in shaping an information governance program. Every business is subject to numerous compliance regimes managed by multiple regulatory agencies, which can differ across markets. Many compliance requirements are dependent upon the numbers of employees and/or turnover reaching certain limits. For example, certain records may need to be stored for 6 years in Poland, yet the same records may need to be stored for 3 years in France.
Establish an Information Governance Team
It is important that a core team be assigned responsibility for the implementation and success of the information governance program. This steering group and a nominated information governance lead can then drive forward operational and practical issues, including; Agreeing and developing a work program, Developing policy and strategy, and Communication and awareness planning.
Recently, I had the opportunity to talk to a number of CFOs about their technology priorities. These discussions represent an opportunity for CIOs to hear what their most critical stakeholder considers important. The CFOs did not hesitate or need to think much about this question. They said three things make their priority list. They are better financial system reliability, better application integration, and better data security and governance. The top two match well with a recent KPMG study which found the biggest improvement finance executives want to see—cited by 91% of survey respondents—is in the quality of financial and performance insight obtained from the data they produce, followed closely by the finance and accounting organization’s ability to proactively analyze that information before it is stale or out of date”
CFOs want to know that their systems work and are reliable. They want the data collected from their systems to be analyzed in a timely fashion. Importantly, CFOs say they are worried not only about the timeliness of accounting and financial data. This is because they increasingly need to manage upward with information. For this reason, they want timely, accurate information produced for financial and business decision makers. Their goal is to drive out better enterprise decision making.
In manufacturing, for example, CFOs say they want data to span from the manufacturing systems to the distribution system. They want to be able to push a button and get a report. These CFOs complain today about the need to manually massage and integrate data from system after system before they get what they and their business decision makers want and need.
CFOs really feel the pain of systems not talking to each other. CFOs know firsthand that they have “disparate systems” and that too much manual integration is going on. For them, they see firsthand the difficulties in connecting data from the frontend to backend systems. They personally feel the large number of manual steps required to pull data. They want their consolidation of account information to be less manual and to be more timely. One CFO said that “he wants the integration of the right systems to provide the right information to be done so they have the right information to manage and make decisions at the right time”.
Data Security and Governance
CFOs, at the same time, say they have become more worried about data security and governance. Even though CFOs believe that security is the job of the CIO and their CISO, they have an important role to play in data governance. CFOs say they are really worried about getting hacked. One CFO told me that he needs to know that systems are always working properly. Security of data matters today to CFOs for two reasons. First, data has a clear material impact. Just take a look at the out of pocket and revenue losses coming from the breach at Target. Second, CFOs, which were already being audited for technology and system compliance, feel that their audit firms will be obligated to extend what they were doing in security and governance and go as a part of regular compliance audits. One CFO put it this way. “This is a whole new direction for us. Target scared a lot of folks and will be to many respects a watershed event for CFOs”.
So the message here is that CFOs prioritize three technology objectives for their CIOs– better IT reliability, better application integration, and improved data security and governance. Each of these represents an opportunity to make the CFOs life easier but more important to enable them to take on a more strategic role. The CFOs, that we talked to, want to become one of the top three decision makers in the enterprise. Fixing these things for CFOs will enable CIOs to build a closer CFO and business relationships.
Solution Brief: The Intelligent Data Platform
Solution Brief: Secure at Source
Last time I talked about how benchmark data can be used in IT and business use cases to illustrate the financial value of data management technologies. This time, let’s look at additional use cases, and at how to philosophically interpret the findings.
So here are some additional areas of investigation for justifying a data quality based data management initiative:
- Compliance or any audits data and report preparation and rebuttal (FTE cost as above)
- Excess insurance premiums on incorrect asset or party information
- Excess tax payments due to incorrect asset configuration or location
- Excess travel or idle time between jobs due to incorrect location information
- Excess equipment downtime (not revenue generating) or MTTR due to incorrect asset profile or misaligned reference data not triggering timely repairs
- Equipment location or ownership data incorrect splitting service cost or revenues incorrectly
- Party relationship data not tied together creating duplicate contacts or less relevant offers and lower response rates
- Lower than industry average cross-sell conversion ratio due to inability to match and link departmental customer records and underlying transactions and expose them to all POS channels
- Lower than industry average customer retention rate due to lack of full client transactional profile across channels or product lines to improve service experience or apply discounts
- Low annual supplier discounts due to incorrect or missing alternate product data or aggregated channel purchase data
I could go on forever, but allow me to touch on a sensitive topic – fines. Fines, or performance penalties by private or government entities, only make sense to bake into your analysis if they happen repeatedly in fairly predictable intervals and are “relatively” small per incidence. They should be treated like M&A activity. Nobody will buy into cost savings in the gazillions if a transaction only happens once every ten years. That’s like building a business case for a lottery win or a life insurance payout with a sample size of a family. Sure, if it happens you just made the case but will it happen…soon?
Use benchmarks and ranges wisely but don’t over-think the exercise either. It will become paralysis by analysis. If you want to make it super-scientific, hire an expensive consulting firm for a 3 month $250,000 to $500,000 engagement and have every staffer spend a few days with them away from their day job to make you feel 10% better about the numbers. Was that worth half a million dollars just in 3rd party cost? You be the judge.
In the end, you are trying to find out and position if a technology will fix a $50,000, $5 million or $50 million problem. You are also trying to gauge where key areas of improvement are in terms of value and correlate the associated cost (higher value normally equals higher cost due to higher complexity) and risk. After all, who wants to stand before a budget committee, prophesy massive savings in one area and then fail because it would have been smarter to start with something simpler and quicker win to build upon?
The secret sauce to avoiding this consulting expense and risk is a natural curiosity, willingness to do the legwork of finding industry benchmark data, knowing what goes into them (process versus data improvement capabilities) to avoid inappropriate extrapolation and using sensitivity analysis to hedge your bets. Moreover, trust an (internal?) expert to indicate wider implications and trade-offs. Most importantly, you have to be a communicator willing to talk to many folks on the business side and have criminal interrogation qualities, not unlike in your run-of-the-mill crime show. Some folks just don’t want to talk, often because they have ulterior motives (protecting their legacy investment or process) or hiding skeletons in the closet (recent bad performance). In this case, find more amenable people to quiz or pry the information out of these tough nuts, if you can.
Lastly; if you find ROI numbers, which appear astronomical at first, remember that leverage is a key factor. If a technical capability touches one application (credit risk scoring engine), one process (quotation), one type of transaction (talent management self-service), a limited set of people (procurement), the ROI will be lower than a technology touching multiple of each of the aforementioned. If your business model drives thousands of high-value (thousands of dollars) transactions versus ten twenty-million dollar ones or twenty-million one-dollar ones, your ROI will be higher. After all, consider this; retail e-mail marketing campaigns average an ROI of 578% (softwareprojects.com) and this with really bad data. Imagine what improved data can do just on that front.
I found massive differences between what improved asset data can deliver in a petrochemical or utility company versus product data in a fashion retailer or customer (loyalty) data in a hospitality chain. The assertion of cum hoc ergo propter hoc is a key assumption how technology delivers financial value. As long as the business folks agree or can fence in the relationship, you are on the right path.
What’s your best and worst job to justify someone giving you money to invest? Share that story.
According to the Financial Executives Institute, CFOs say their second highest priority this year is to harness business intelligence and big data. Their highest priority is to improve cash flow and working capital efficiency and effectiveness. This means CFOs highest two priorities are centered around data. At roughly the same time, KPMG has found in their survey of CFOs that 91% want to improve the quality of their financial and performance insight obtained from the data that they produce. Even more amazing 51% of CFO admitted that “collecting, storing, and retrieving financial and performance data at their company is primarily accomplished through a manual and/or spreadsheet-based exercise”. From our interviews of CFOs, we believe this number is much higher.
Your question at this point—if you are not a CFO—should be how can this be the case? After all strategy consultants like Booz and Company, actively measure the degree of digitization and automation taking place in businesses by industry and these numbers year after year have shown a strong upward bias. How can the finance organization be digitized for data collection but still largely manual in its processes for putting together the figures that management and the market needs?
CFOs do not trust their data
In our interviews of CFOs, one CFO answered this question bluntly by saying “If the systems suck, then you cannot trust the numbers when you get them.” And this reality truly limits CFOs in how they respond to their top priorities. Things like management of the P&L, Expense Management, Compliance, and Regulatory all are impacted by the CFOs data problem. Instead of doing a better job at these issues, CFOs and their teams remain largely focused on “getting the numbers right”. And even worse, the answering of business questions like how much revenue is this customer providing or how profitable this customer is, involves manual pulls of data today from more than one system. And yes, similar data issues exist in financial services organizations which close the books nightly.
The CFOs, that I have talked to, admit without hesitation that data is a big issue for them. These CFOs say that they worry about data from the source and the ability to do meaningful financial or managerial analysis. They say they need to rely on data in order to report but as important they need it to help drive synergies across businesses. This matters because CFOs say they want to move from being just “bean counters” to being participants in the strategy of their enterprises.
To succeed, CFOs say that they need timely, accurate data. However, they are the first to discuss how disparate systems get in their way. CFOs believe that making their lives easier starts with the systems that support them. What they believe is needed is real integration and consolidation of data. One CFO said what is needed this way, “we need the integration of the right systems to provide the right information so we can manage and make decisions at the right time”. CFOs clearly want to know that the accounting systems are working and reliable. At the same time, CFOs want, for example, a holistic view of customer. When asked why this isn’t a marketing activity, they say this is business issue that CFOs need to help manage. “We want to understand the customer across business units. It is a finance objective because finance is responsible for business metrics and there are gaps in business metrics around customer. How much cross sell opportunities is the business as a whole pursuing?”
Chief Profitability Officers?
Jonathan Brynes at the MIT Sloan School confirms this viewpoint is becoming a larger trend when he suggests that CFOs need to take on the function of “Chief Profitability Officers”. With this hat, CFOs, in his view, need to determine which product lines, customers, segments, and channels are the most and the least profitable. Once again, this requires that CFOs tackle their data problem to have relevant, holistic information.
CIOs remain responsible for data delivery
CFOs believe that CIOs remain responsible for how data is delivered. CFOs, say that they need to lead in creating validated data and reports. Clearly, if data delivery remains a manual process, then the CFO will be severely limited in their ability to adequately support their new and strategic charter. Yet CFOs when asked if they see data as a competitive advantage say that “every CFO would view data done well as a competitive advantage”. Some CFOs even suggest that data is the last competitive advantage. This fits really well with the view of Davenport in “Competing on Analytics”. The question is how soon will CIOs and CFOs work together to get the finance organization out of its mess of manually massaging and consolidating financial and business data.
Solution Brief: The Intelligent Data Platform
Recently, my US-based job led me to a South African hotel room, where I watched Germany play Brazil in the World Cup. The global nature of the event was familiar to me. My work covers countries like Malaysia, Thailand, Singapore, South Africa and Costa Rica. And as I pondered the stunning score (Germany won, 7 to 1), my mind was drawn to emerging markets. What defines an emerging market? In particular, what are the data-related themes common to emerging markets? Because I work with global clients in the banking, oil and gas, telecommunications, and retail industries, I have learned a great deal about this. As a result, I wanted to share my top 5 observations about data in Emerging Markets.
1) Communication Infrastructure Matters
Many of the emerging markets, particularly in Africa, jumped from one or two generations of telco infrastructure directly into 3G and fiber within a decade. However, this truth only applies to large, cosmopolitan areas. International diversification of fiber connectivity is only starting to take shape. (For example, in Southern Africa, BRICS terrestrial fiber is coming online soon.) What does this mean for data management? First, global connectivity influences domestic last mile fiber deployment to households and businesses. This, in turn, will create additional adoption of new devices. This adoption will create critical mass for higher productivity services, such as eCommerce. As web based transactions take off, better data management practices will follow. Secondly, European and South American data centers become viable legal and performance options for African organizations. This could be a game changer for software vendors dealing in cloud services for BI, CRM, HCM, BPM and ETL.
2) Competition in Telecommunication Matters
If you compare basic wireless and broadband bundle prices between the US, the UK and South Africa, for example, the lack of true competition makes further coverage upgrades, like 4G and higher broadband bandwidths, easy to digest for operators. These upgrades make telecommuting, constant social media engagement possible. Keeping prices low, like in the UK, is the flipside achieving the same result. The worst case is high prices and low bandwidth from the last mile to global nodes. This also creates low infrastructure investment and thus, fewer consumers online for fewer hours. This is often the case in geographically vast countries (Africa, Latin America) with vast rural areas. Here, data management is an afterthought for the most part. Data is intentionally kept in application silos as these are the value creators. Hand coding is pervasive to string data together to make small moves to enhance the view of a product, location, consumer or supplier.
3) A Nation’s Judicial System Matters
If you do business in nations with a long, often British judicial tradition, chances are investment will happen. If you have such a history but it is undermined by a parallel history of graft from the highest to the lowest levels because of the importance of tribal traditions, only natural resources will save your economy. Why does it matter if one of my regional markets is “linked up” but shipping logistics are burdened by this excess cost and delay? The impact on data management is a lack of use cases supporting an enterprise-wide strategy across all territories. Why invest if profits are unpredictable or too meager? This is why small Zambia or Botswana are ahead of the largest African economy, Nigeria.
4) Expertise Location Matters
Anybody can have the most advanced vision on a data-driven, event-based architecture supporting the fanciest data movement and persistence standards. Without the skill to make the case to the business it is a lost cause unless your local culture still has IT in charge of specifying requirements, running the evaluation, selecting and implementing a new technology. It is also done for if there are no leaders who have experienced how other leading firms in the same or different sector went about it (un)successfully. Lastly, if you don’t pay for skill, your project failure risk just tripled. Duh!
5) Denial is Universal
No matter if you are an Asian oil company, a regional North American bank, a Central American National Bank or an African retail conglomerate. If finance or IT invested in any technologies prior and they saw a lack of adoption, for whatever reason, they will deny data management challenges despite other departments complaining. Moreover, if system integrators or internal client staff (mis)understand data management as fixing processes (which it is not) instead of supporting transactional integrity (which it is), clients are on the wrong track. Here, data management undeservedly becomes a philosophical battleground.
This is definitely not a complete list or super-thorough analysis but I think it covers the most crucial observations from my engagements. I would love to hear about your findings in emerging markets.
Stay tuned for part 2 of this series where I will talk about the denial and embrace of corporate data challenges as it pertains to an organization’s location.
A few weeks ago, a regional US bank asked me to perform some compliance and use case analysis around fixing their data management situation. This bank prides itself on customer service and SMB focus, while using large-bank product offerings. However, they were about a decade behind the rest of most banks in modernizing their IT infrastructure to stay operationally on top of things.
This included technologies like ESB, BPM, CRM, etc. They also were a sub-optimal user of EDW and analytics capabilities. Having said all this; there was a commitment to change things up, which is always a needed first step to any recovery program.
As I conducted my interviews across various departments (list below) it became very apparent that they were not suffering from data poverty (see prior post) but from lack of accessibility and use of data.
- Vendor Management & Risk
- Commercial and Consumer Depository products
- Credit Risk
- HR & Compensation
- Private Banking
- Customer Solutions
This lack of use occurred across the board. The natural reaction was to throw more bodies and more Band-Aid marts at the problem. Users also started to operate under the assumption that it will never get better. They just resigned themselves to mediocrity. When some new players came into the organization from various systemically critical banks, they shook things up.
Here is a list of use cases they want to tackle:
- The proposition of real-time offers based on customer events as simple as investment banking products for unusually high inflow of cash into a deposit account.
- The use of all mortgage application information to understand debt/equity ratio to make relevant offers.
- The capture of true product and customer profitability across all lines of commercial and consumer products including trust, treasury management, deposits, private banking, loans, etc.
- The agile evaluation, creation, testing and deployment of new terms on existing and products under development by shortening the product development life cycle.
- The reduction of wealth management advisors’ time to research clients and prospects.
- The reduction of unclaimed use tax, insurance premiums and leases being paid on consumables, real estate and requisitions due to the incorrect status and location of the equipment. This originated from assets no longer owned, scrapped or moved to different department, etc.
- The more efficient reconciliation between transactional systems and finance, which often uses multiple party IDs per contract change in accounts receivable, while the operating division uses one based on a contract and its addendums. An example would be vendor payment consolidation, to create a true supplier-spend; and thus, taking advantage of volume discounts.
- The proactive creation of central compliance footprint (AML, 314, Suspicious Activity, CTR, etc.) allowing for quicker turnaround and fewer audit instances from MRAs (matter requiring attention).
MONEY TO BE MADE – PEOPLE TO SEE
Adding these up came to about $31 to $49 million annually in cost savings, new revenue or increased productivity for this bank with $24 billion total assets.
So now that we know there is money to be made by fixing the data of this organization, how can we realistically roll this out in an organization with many competing IT needs?
The best way to go about this is to attach any kind of data management project to a larger, business-oriented project, like CRM or EDW. Rather than wait for these to go live without good seed data, why not feed them with better data as a key work stream within their respective project plans?
To summarize my findings I want to quote three people I interviewed. A lady, who recently had to struggle through an OCC audit told me she believes that the banks, which can remain compliant at the lowest cost will ultimately win the end game. Here she meant particularly tier 2 and 3 size organizations. A gentleman from commercial banking left this statement with me, “Knowing what I know now, I would not bank with us”. The lady from earlier also said, “We engage in spreadsheet Kung Fu”, to bring data together.
Given all this, what would you suggest? Have you worked with an organization like this? Did you encounter any similar or different use cases in financial services institutions?
The interesting thing is that many of the upstarts do not even intend to take on the market leader in the segment. Christensen cites the classic example of Digital Equipment Corporation in the 1980s, which was unable to make the transition from large, expensive enterprise systems to smaller, PC-based equipment. The PC upstarts in this case did not take on Digital directly – rather they addressed unmet needs in another part of the market.
Christensen wrote and published The Innovator’s Dilemma more than 17 years ago, but his message keeps reverberating across the business world. Lately, Jill Lapore questioned some of thinking that has evolved around disruptive innovation in a recent New Yorker article. “Disruptive innovation is a theory about why businesses fail. It’s not more than that. It doesn’t explain change. It’s not a law of nature,” she writes. Christensen responded with a rebuttal to Lapore’s thesis, noting that “disruption doesn’t happen overnight,” and that “[Disruptive innovation] is not a theory about survivability.”
There is something Lapore points out that both she and Christensen can agree on: “disruption” is being oversold and misinterpreted on a wide scale these days. Every new product that rolls out is now branded as “disruptive.” As stated above, the true essence of disruption is creating new markets where the leaders would not tread.
Data itself can potentially be a source of disruption, as data analytics and information emerge as strategic business assets. While the ability to provide data analysis at real-time speeds, or make new insights possible isn’t disruption in the Christensen sense, we are seeing the rise of new business models built around data and information that could bring new leaders to the forefront. Data analytics can either play a role in supporting this movement, or data itself may be the new product or service disrupting existing markets.
We’ve already been seeing this disruption taking place within the publishing industry, for example – companies or sites providing real-time or near real-time services such as financial updates, weather forecasts and classified advertising have displaced traditional newspapers and other media as information sources.
Employing data analytics as a tool for insights never before available within an industry sector also may be part of disruptive innovation. Tesla Motors, for example, is disruptive to the automotive industry because it manufactures entirely electric cars. But the formula to its success is its employment of massive amounts of data from its array of vehicle in-devices to assure quality and efficiency.
Likewise, data-driven disruption may be occurring in places that may have been difficult to innovate. For example, it’s long been speculated that some of the digital giants, particularly Google, are poised to enter the long-staid insurance industry. If this were to happen, Google would not enter as a typical insurance company with a new web-based spin. Rather, the company would be employing new techniques of data gathering, insight and analysis to offer an entirely new model to consumers – one based on data. As Christopher Hernaes recently related in TechCrunch, Google’s ability to collect and mine data on homes, business and autos give it a unique value proposition n the industry’s value chain.
We’re in an era in which Christensen’s mode of disruptive innovation has become a way of life. Increasingly, it appears that enterprises that are adept and recognizing and acting upon the strategic potential of data may be joining the ranks of the disruptors.