Myles Suer

Myles Suer
Mr. Suer is a senior manager of solutions marketing at Informatica Corporation. Much of Mr. Suer’s experience has been as a BI practitioner. At HP and Peregrine, Mr. Suer led the product management team applying BI and Scorecard technology to these company’s IT management products. Prior to HP, Mr. Suer led new product initiatives at start-ups and large companies. This included doing a restart of a Business Activity Monitoring Company. Mr. Suer has, also, been a software industry analyst. Mr. Suer holds a Master of Science degree from UC Irvine and a 2nd Masters in Business Administration in Strategic Planning from the University of Southern California.

It is All About the “I”

Six ideas for CIOs in 2015 to put the innovation back in CIO

CIOFor most, the “I” in CIO stands for Information. But what about that other “I”, Innovation? For many IT organizations, 60-80% of IT spending continues to be tied up in keeping the IT lights on. But innovation matters more than ever to the business bottom line. According Geoffrey Moore, “without innovation, offerings become more and more like each other. They commoditize.” (“Dealing with Darwin”, Geoffrey Moore, page 1). Geoffrey goes on to say later in “Dealing with Darwin” that commoditization will over time drop business returns to “the cost of capital”. So clearly, this is a place that no CIO would want their enterprises to consciously go.

Given this, what is the role of the CIO in driving enterprise innovation? I believe that it is a significant one. Without question, technology investment has been a major driver of enterprise productivity gains. At the same time, IT investment has had a major role in improving business capabilities and the business value chains. And more recently, IT is even carving out a role in products themselves as part of the IoT. So how can CIOs help drive business innovation?

1) Get closer to your business customers. CIOs have said to me that their number one priority is connecting what the IT is doing to what the business is doing. Given this, CIOs should make it a real priority for their teams to get closer to the business this year. According to Kamalini Ramdas’ Article in Harvard Business Review, “to succeed at innovation, you need to have a culture in which everyone in the company is constantly scanning for ideas”.

2) Develop internal design partners. When I have started new businesses, I have always created a set of design partners to ensure that I built the right products. I tell my design partners to beat me up now rather than after I build the product. You need, as Kamalini Ramdas suggests, to harvest the best ideas of your corporate team just like I did with startups. You can start by focusing your attention upon the areas of distinctive capability—the places that give your firm its right to win.

3) Enabling your IT leaders and individual contributors to innovate. For many businesses, speed to market or speed of business processes can represent a competitive advantage. Foundationally to this are IT capabilities including up time, system performance, speed of project delivery, and the list goes on. Encouraging everyone on your team to drive superior operational capabilities can enable business competitive advantage. And one more thing, make sure to work with your business leaders to pass a portion of the business impact for improvements into a bonus for the entire enabling IT team. At Lincoln Electric, they used bonuses by team to continuously improve their products. This arch welding company shares the money saved from each process improvement with the entire team. They end up getting the best team and highest team longevity as teams work improves product quality and increases cost take out. According Kamalini, “in truly innovative culture, leaders need to imbue every employee with a clear vision and a sense of empowerment that helps them identify synergistic ideas and run with them” (“Build a Company Where Everyone’s Looking for New Ideas”, Harvard Business Review, page 1).

4) Architect for Innovation. As the velocity of change increases, businesses need IT organizations to be able to move more quickly. This requires an enterprise architecture built for agility. According to Jeanne Ross, the more agile companies have a high percentage of their core business processes digitized and they have as well standardized their technology architecture (Enterprise Architecture as Strategy, Jeanne Ross, page 12).

5) Look for disruptive innovations. I remember a professor of mine suggesting that we cannot predict the future when discussing futures research. But I believe that you can instead get closer to your customers than anyone else. CIOs should dedicate a non-trival portion of IT spend to germinating potentially disruptive ideas. They should use their design partners to select what gets early stage funding. Everyone here should act like a seed stage venture capitalist. You need to let people experiment. At the same time, design partners should set reasonable goals and actively measure performance toward goals.

6) Use analytics. Look at business analytics for areas of that could use IT’s help. Open up discussions with design partners for areas needing capability improvement. This is a great place to start. Look as well for where there are gaps in business delivery that could be drive better performance from further or improved digitization/automation. And once an innovation is initiated, analytics should actively ensure the management of  the innovation’s delivery.

Final remarks

There is always more that you can do to innovate. The key thing is to get innovation front and center on the IT agenda. Actively sponsor it and most importantly empower the team to do remarkable things. And when this happens, reward the teams that made it happen.

IT Is All About Data!
The Secret To Being A Successful CIO
Driving IT Business Alignment: One CIOs Journey
How Is The CIO Role Starting To Change?
The CIO Challenged

Twitter: @MylesSuer

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Are The Banks Going to Make Retailers Pay for Their Poor Governance?

 

Retail and Data Governance

Retail and Data Governance

A couple months ago, I reached out to a set of CIOs on the importance of good governance and security. All of them agreed that both were incredibly important. However, one CIO retorted a very pointed remark by saying that “the IT leadership at these breached companies wasn’t stupid.” He continued by saying that when selling the rest of the C-Suite, the discussion needs to be about business outcomes and business benefits.  For this reason, he said that CIOs have struggled at selling the value of investments in governance and security investment. Now I have suggested previously that security pays because of the impact on “brand promise”.  And, I still believe this.

However, this week the ante was raised even higher. A district judge ruled that a group of banks can proceed to sue a retailer for negligence in their data governance and security. The decision could clearly lead to significant changes in the way the cost of fraud is distributed among parties within the credit card ecosystem. Where once banks and merchant acquirers would have shouldered the burden of fraud, this decision paves the way for more card-issuing banks to sue merchants for not adequately protecting their POS systems.

Accidents waste priceless time

Accidents waste priceless time

The judge’s ruling said that “although the third-party hackers’ activities caused harm, merchant played a key role in allowing the harm to occur.” The judge also determined that the bank suit against merchants was valid because the plaintiffs adequately showed that the retailer failed “to disclose that its data security systems were deficient.” This is interesting because it says that security systems should be sufficient and if not, retailers need to inform potentially affected stakeholders of their deficient systems. And while taking this step could avoid a lawsuit, it would likely increase the cost of interchange for more risky merchants. This would effectively create a risk premium for retailers that do not adequately govern and protect their IT environments.

There are broad implications for all companies who end up harming customer, partners, or other stakeholders by not keeping their security systems up to snuff. The question is, will this make good governance have enough of a business outcome and benefit that businesses will actually want to pay it forward — i.e. invest in good governance and security? What do you think? I would love to hear from you.

Related links

Solutions:

Enterprise Level Data Security

Hacking: How Ready Is Your Enterprise?

Gambling With Your Customer’s Financial Data

The State of Data Centric Security

Twitter: @MylesSuer

 

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Relating the IoT to Enterprise Business Strategy

Business StrategyRecently, I got to speak to a CIO at a Global 500 Company about the challenges of running his IT organization. He said that one of his biggest challenges is getting business leaders to understand technology better. “I want my business leaders to be asking for digital services that support and build upon their product and service offerings”. I think that his perspective provides real insight to how businesses should be thinking about the so called Internet of Things (IoT), but let me get you there first.

What is the IoT?

According to Frank Burkitt of @Strategy, by 2029, an estimated 50 billion devices around the globe will be connected to the Internet. Perhaps a third will be computers, smartphones, tablets, and TVs. The remaining two-thirds will be “things”–sensors, actuators, and intelligent devices that monitor, control, analyze, and optimize our world. Frank goes on to say if your company wants to stake a claim in the IoT, you first need to develop a distinctive “way to play”—a clear value proposition that you can offer customers. This should be consistent with your enterprise’s overall capabilities system: the things you do best when you go to market.

While what Frank suggests make great sense, they do not in my opinion provide the strategic underpinning that business leaders need to link the IoT to their business strategy. Last week an article in Harvard Business Review by Michael Porter and James E. Heppelmann shared what business leaders need to do to apply the IoT to their businesses. According to Porter and Hepplemann, historical, enterprises have defined their businesses by the physical attributes of the products and services they produce. And while products have been mostly composed of mechanical and electrical parts, they are increasingly becoming complex systems that combine hardware, sensors, data storage, microprocessors, software, and data connectivity.

The IoT is really about creating a system of systems

Business StrategyPorter and Hepplemann share in their article how connectivity allows companies to evolve from making point solutions, to making more complex, higher-value “systems of systems”. According to Russell Ackoff, a system’s orientation views customer problems “as a whole and not on their parts taken separate” (Ackoff’s Best, Russell Ackoff, John Wiley and Sons, page 47). This change means that market winners will tend to view business opportunities from a larger versus a smaller perspective. It reminds me a lot of what Xerox did when it transformed itself from commoditized copiers to high priced software based document management where the printer represent an input device to a larger system. Porter and Hepplemann’s give the example of a company that sells tractors. Once a tractor is smart and connected, it becomes part of a highly interconnected agricultural management solution.

According to Porter and Hepplemann, the key element of “smart, connected products” is they take advantage of ubiquitous wireless connectivity to unleash an era where competition is increasingly about the size of the business problem solved. Porter and Hepplemann claim that as smart, connected products take hold, the idea of industries being defined by physical products or services alone will cease to have meaning. What sense does it make to talk about a “tractor industry” when tractors represent just a piece of an integrated system of products, services, software, and data designed to help farmers increase their crop yield?

Porter and Hepplemann claim, therefore, the phrase “Internet of Things” is not very helpful in understanding the phenomenon or even its implications. They say after all what makes smart, connected products fundamentally different is not the Internet, it is a redefinition of what is a product and the capabilities smart, connected products provide and the data they generate. Companies, therefore, need to look at how the IoT will transform the competition within their specific industries.

Like a business slogan, the IoT is about putting IT inside

Business StrategyIT leaders have a role to play in the IoT. They need to move IT from just assisting business management drive improvements to the company value chain to organizations  that as well embed IT in what become system oriented products. How perceptive, therefore, was my CIO friend.

Porter and Hepplemann claim connectivity serves two purposes. First, it allows information to be exchanged between a product and its operating environment, its maker, its users, and other products and systems. Second, connectivity enables some functions of the product to exist outside the physical device. Porter and Hepplemann give the example of Schindler’s PORT Technology that reduces elevator wait times by as much as 50% by predicting elevator demand patterns, calculating the fastest time to destination, and assigning the appropriate elevator to move passengers quickly. Porter and Hepplemann see as well intelligence and connectivity enabling an entirely new set of product functions and capabilities, which can be grouped into four categories: monitor, control, optimize, and autonomy. To be clear, a systems product can potentially incorporate all four.

  • Monitored products alert users to changes in circumstances or performance. They can provide a product’s operating characteristics and history. A company must choose the set customer value and define its competitive positioning. This has implications design, marketing, service, and warranty.
  • Controlled products can receive remote commands or have algorithms that are built into the device or reside in the product’s cloud. For example, “if pressure gets too high, shut off the valve” or “when traffic in a parking garage reaches a certain level, turn the overhead lighting on or off”.
  • Optimized products apply algorithms and analytics to in-use or historical data to improve output, utilization, and efficiency. Real-time monitoring data on product condition and product control capability enables firms to optimize service.
  • Autonomous product like are able to learn about their environment, self-diagnose their own service needs, and adapt to users’ preferences.

Smart, connected products expand opportunities for product differentiation

Geoffrey MooreIn a world where Geoffrey Moore sees differentiated products constantly being commoditized; smart, connected products dramatically expand opportunities for product differentiation and move the competition away from price alone. Knowing how customers actually use your products enhances a company’s ability to segment customers, customize products, set prices to better capture value, and extend value-added services. Smart, connected products, at the same time, create opportunities to broaden the value proposition beyond products per se, to include valuable data and enhanced service offerings. Broadening product definitions can raise barriers to entrants even higher. The powerful capabilities of smart, connected products not only reshape competition within an industry, but they can expand the very definition of the industry itself. For example, integrating smart, connected farm equipment—such as tractors, tillers, and planters—can enable better overall equipment performance.

Smart, connected products will not only reshape competition within an industry, but they can expand the very definition of the industry itself. Here Porter and Hepplemann are talking here about the competitive boundaries of an industry widen to encompass a set of related products that together meet a broader underlying need. The function of one product is optimized with other related products.

Porter and Hepplemann believe that smart, connected products allow as well companies to form new kinds of relationships with their customers. In many cases, this may require market participants to develop new marketing practices and skill sets. As companies accumulate and analyze product usage data, they will as well gain new insights into how products create value for customers, allowing better positioning of offerings and more effective communication of product value to customers. Using data analytics tools, firms will be able segment their markets in more-sophisticated ways, tailor product and service bundles that deliver greater value to each segment, and price those bundles to capture more of that value.

Some parting thoughts

So summarizing their position, Porter and Hepplemann believe the IoT is really about taking smart things and building solutions that solve bigger problems because one can architect the piece parts into a solution of solutions. This will impact marketplace dynamics and create competitive differentiators in a world of increasing product commodization. For me this is a roadmap forward especially for those at the later stages of product lifecycle curve.

Related links

Related Blogs

Analytics Stories: A Banking Case Study
Analytics Stories: A Financial Services Case Study
Analytics Stories: A Healthcare Case Study
Who Owns Enterprise Analytics and Data?
Competing on Analytics: A Follow Up to Thomas H. Davenport’s Post in HBR
Thomas Davenport Book “Competing On Analytics”

Solution Brief: The Intelligent Data Platform

Author Twitter: @MylesSuer

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Analytics Stories: An Educational Case Study

AnalyticsAs I have shared within other posts within this series, businesses are using analytics to improve their internal and external facing business processes and to strengthen their “right to win” within the markets that they operate. At first glance, you might not think of universities needing to worry much about their right to win, but universities today are facing increasing competition for students as well as the need to increase efficiency, decrease dependence upon state funding, create new and less expensive delivery models, and drive better accountability.

George Washington University Perceives The Analytic Opportunity

AnalyticsGeorge Washington University (GWU) is no different. And for this reason their leadership determined that they needed to gain the business insight to compete for the best students, meet student diversity needs, and provide accountability to internal and external stakeholders. All of these issues turned out to have a direct impact upon GWU’s business processes—from student recruitment to financial management. At the same time university leadership determined the complexity of these challenges requires continual improvement in the University’s operational strategies and most importantly, accurate, timely, and consistent data.

Making It A Reality

processing dataGWU determined that getting after these issues required a flexible system that could provide analytics and key academic performance indicators and metrics on demand, whenever they needed them. They, also, determined that the analytics and underlying data needed to enable accurate, balanced decisions needed to be performed more quickly and more effectively than in the past.

Unfortunately, GWU’s data was buried in disparate data sources that were largely focused on supporting transactional, day-to-day business processes. This data was difficult to extract and even more difficult to integrate into a single format, owing to inherent system inconsistencies and the ownership issues surrounding them — a classic problem for collegial environments. Moreover, the university’s transaction applications did not store data in models that supported on-demand and ad hoc aggregations that GWU business users required.

To solve these issues, GWU created a data integration and business intelligence implementation dubbed the Student Data Mart (SDM). The SDM integrates raw structured and unstructured data into a unified data model to support key academic metrics.

“The SDM represents a life record of the students,” says Wolf, GWU’s Director of Business Intelligence. “It contains 10 years of recruitment, admissions, enrollment, registration, and grade-point average information for all students across all campuses”. It supports a wide-range of academic metrics around campus enrollment counts, admissions selectivity, course enrollment, student achievement, and program metrics.

These metrics are directly and systematically aligned with the academic goals for each department and with GWU’s overall overarching business goals. Wolf says, “The SDM system provides direct access to key measures of academic performance”. “By integrating data into a clean repository and disseminating information over their intranet, the SDM has given university executivesdirect access to key academic metrics. Based on these metrics, users are able to make decisions in a timely manner and with more precision than before.”

Their integration technology supports a student account system, which supplies more than 400 staff with a shared, unified view of the financial performance of students. It connects data from a series of diverse, fragmented internal sources and third-party data from employers, sponsors, and collection agencies. The goal is to answer business questions about whether students paid their fees or how much they paid for each university course.

Continual Quality Improvement

AnalyticsDuring its implementation, GWU’s data integration process exposed a number of data quality issues that were the natural outcome of a distributed data ownership. Without an enterprise approach to data and analytics, it would have been difficult to investigate the nature and extent of data quality issues from its historical fragmented business intelligence system. Taking an enterprise approach has, as well, enabled GWU to improve data quality standards and procedures.

Wolf explains, “Data quality is an inevitable problem in any higher education establishment, because you have so many different people—lecturers, students, and administration staff—all entering data. With our system, we can find hidden data problems, wherever they are, and analyze the anomalies across all data sources. This helps build our trust and confidence in the data. It also speeds up the design phase because it overcomes the need to hand query the data to see what the quality is like.”

Connecting The Dots

Dots_gameplayWolf and his team have not stopped here. As data emanating from social media has grown, they have designed their system so social data can be integrated just as easily as their traditional data sources including Oracle Financials, SunGard, SAP, and flat file data. Wolf says the SDM platform doesn’t turn its back on any type of data. By allowing the university to integrate any type of data, including social media, Wolf has been able to support key measures of academic performance, improving standards, and reducing costs. Ultimately, this is helping GWU maintain its business position as well as the University’s position especially as a magnet for the best students around the world.

In sum, the GWU analytics solution has helped it achieve the following business goals:

  • Attract the best students
  • Provide trusted reliable data for decision makers
  • Enable more timely business decisions
  • Increase achievement of academic and administrative goals
  • Deliver new business insight by combining social media with existing data sources

Related links

Related Blogs

Analytics Stories: A Banking Case Study
Analytics Stories: A Financial Services Case Study
Analytics Stories: A Healthcare Case Study
Who Owns Enterprise Analytics and Data?
Competing on Analytics: A Follow Up to Thomas H. Davenport’s Post in HBR
Thomas Davenport Book “Competing On Analytics”

Solution Brief: The Intelligent Data Platform

Author Twitter: @MylesSuer

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CFO Checklist to Owning Enterprise Analytics

Frank-FriedmanLast month, the CEO of Deloitte said that CFOs are “the logical choice to own analytics and put them to work to serve the organization’s needs”. In my discussions with CFOs, they have expressed similar opinions.  Given this, the question becomes what does a CFO need to do to be effective leader of their company’s analytics agenda? To answer this, I took a look at what Tom Davenport suggests in his book “Analytics at Work”. In this book, Tom suggests that an analytical leader need to do the following twelve things to be effective:

12 Ways to Be an Effective Analytics Leader

1)      Develop their people skills. This is not just about managing analytical people which has its own challenges. It is, also, about CFOs establishing the “the credibility and trust needed when analytics produce insights that effectively debunk currently accepted wisdom”.
2)      Push for fact based decision making. You need to, as a former boss of mine like to say, become the lightening rod and in this case, set the expectation that people will make decisions based upon data and analysis.
3)      Hire and retain smart people. You need to provide a stimulating and supportive work environment for analysts and give them credit when they do something great.
4)      Be the analytical example. You need to lead by example. This means you need to use data and analysis in making your own decisions
5)      Signup for improved results. You need to commit to driving improvements in a select group of business processes by using analytics. Pick something meaningful ike reducing the cost of customer acquisition or optimizing your company’s supply chain management.
6)      Teach the organization how to use analytic methods. Guide employees and other stakeholders into using more rigorous thinking and decision making.
7)      Set strategies and performance expectations. Analytics and fact-based decisions cannot happen in a vacuum. They need strategies and goals that analytics help achieve.
8)      Look for leverage points. Look for the business problems where analytics can make a real difference. Look for places where a small improvement in a process driven by analytics can make a big difference.
9)      Demonstrate persistence. Work doggedly and persistently to apply analytics to decision making, business processes, culture, and business strategy.
10)   Build an analytics ecosystem with your CIO. Build an ecosystem consisting of other business leaders, employees, external analytics suppliers, and business partners. Use them to help you institutionalize analytics at your company.
11)    Apply analytics on more than one front. No single initiative will make the company more successful—no single analytics initiative will do so either.
12)   Know the limits to analytics. Know when it is appropriate to use intuition instead of analytics. As a professor of mine once said not all elements of business strategy can be solved by using statistics or analytics. You should know where and when analytics are appropriate.

Data AnalyticsFollowing these twelve items will help strategic oriented CFOs lead the analytics agenda at their companies. As I indicated in “Who Owns the Analytics Agenda?”, CFOs already typically act as data validators at their firms, but taking this next step matters to their enterprise because “if we want to make better decisions and take the right actions, we have use analytics” (Analytics at Work, Tom Davenport, Harvard Business Review Press, page 1). Given this, CFOs really need to get analytics right. The CFOs that I have talked to say they already “rely on data and analytics and they need them to be timely and accurate”.

One CFO, in fact, said that data is potentially the only competitive advantage left for his firm”. And while implementing the data side of this depends on the CIO. It is clear from the CFOs that I have talked to that they believe a strong business relationship with their CIO is critical to the success of their business.

Enterprise DataSo the question remains are you ready as a financial leader to lead on the analytics agenda? If you are and you want to learn more about setting the analytics agenda, please consider yourself invited to webinar that I am doing with the CFO of RoseRyan in January.

The Webinar is entitled “Analytics and Data for the Strategic CFO”. And by clicking this link you can register to attend. See you there.

Related Blogs

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

Twitter: @MylesSuer

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Should Analytics Be Focused on Small Questions Versus Big Questions?

AnalyticsShould the analytic resources of your company be focused upon small questions or big questions? For many, answering this question is not an easy one. Some find key managers preferring to make decisions from personal intuition or experience. When I worked for a large computer peripheral company, I remember executives making major decisions about product direction from their gut even when there was clear evidence that a major technology shift was about to happen. This company went from being a multi-billion dollar company to a $50 million dollar company in the matter of a few years.

In other cases, the entire company may not see the relationship between data and good decision making. When this happens, silos of the business collect data of value to them but there is not a coordinated, focused effort placed toward enterprise level strategic targets. This naturally leads to silos of analytical activity. Cleary answering small question may provide the value of having analytics quickly. However, answering the bigger questions will have the most value to the business as a whole. And while the big questions are often harder to answer, they can be pivotal to the go forward business. Here are just a few examples of the big questions that are worthy of being answered by most enterprises.

  • Which performance factors have the greatest impact on our future growth and profitability?
  • How can we anticipate and influence changing market conditions?
  • If customer satisfaction improves, what is the impact on profitability?
  • How should we optimize investments across our products, geographies, and market channels?

However, most businesses cannot easily answer these questions. Why then do they lack the analytical solutions to answer these questions?

Departmental BI does not yield strategic relevant data

Analytic- Business IntelligenceLet’s face it, business intelligence to data has largely been a departmental exercise. In most enterprises as we have been saying, analytics start as pockets of activity versus as an enterprise wide capability. The departmental approach leads business analysts to buy the same data or software that others in the organization have already bought. Enterprises end up with hundreds of data marts, reporting packages, forecasting tools, data management solutions, integration tools, and methodologies. According to Thomas Davenport, one firm he knows well has “275 data marts and thousand different information resources, but it couldn’t pull together a single view of the business in terms of key performance metrics and customer data” (Analytics at Work, Thomas Davenport, Harvard University Press, Page 47)

Clearly, answering the Big Questions requires leadership and a coordinated approach. Amazingly, taking this road often even reduces enterprise analytical expenditure as silos of information including data marts and spaghetti codes integrations are eliminated and replaced with a single enterprise capability. But if you want to take this approach how do you make sure that you get the right business questions answered?

Strategic Approach

Strategy Drives AnalyticsThe strategic approach starts with enterprise strategy.  In enterprise strategy,   leadership will define opportunities for business growth, innovation, differentiation, and marketplace impact. According to Derek Abell, this process should occur in a three cycle strategic planning approach. This approach has the enterprise doing business planning followed by functional planning, and lastly budgeting. Each cycle provides fodder for the stages that follow. For each stage, a set of overarching cascading objectives can be derived. From these, the businesses can define a set of critical success factors that will let it know whether or not business objectives are being met. Supporting each critical success factor are quantitative key performance indicators that in aggregate say whether the success factors are going to met. Finally, these key performance indicators derive the data that is needed to support the KPIs in terms of metrics or the supporting dimensional data for analysis. So the art and science here is defining critical success factors and KPIs that answer the big questions.

Core Capabilities

automationAs we saw above, the strategic approach is about tying questions to business strategy. In the capabilities approach, we tie questions to the capabilities that drive business competitive advantage. To determine these business capabilities, we need to start by looking at “the underling mechanism of value creation in the company (what they do best) and what the opportunities for meeting the market effectively. (“The Essential Advantage”, Paul Leinwand, Harvard Business Review Press, page 19). Typically, this determines 3-6 distinctive capabilities that impact the success of their enterprises service or product portfolio. These are the things that “enable your company to consistently outperform rivals” (“The Essential Advantage”, Paul Leinwand, Harvard Business Review Press, page 14). To optimize key business capabilities over time, and innovate and operate in ways that differentiate the businesses in the eyes and experience of customers (Analytics at Work, Thomas Davenport, Harvard University Press, Page 73). Here we want to target analytics investments at their distinctive capabilities. Here are some examples of potential target capabilities by industry:

  • Financial services: Credit scoring
  • Retail: Replenishment
  • Manufacturing: Supply Chain Optimization
  • Healthcare: Disease Management

Parting remarks

So as we have discussed, many firms are spending too much on analytic solutions that do not solve real business problems. Getting after this is not a technical issue—it is a business issue. It starts by asking the right business questions which can come from business strategy or your core business capabilities or some mix of each.

Related links

Related Blogs

Analytics Stories: A Banking Case Study
Analytics Stories: A Financial Services Case Study
Analytics Stories: A Healthcare Case Study
Who Owns Enterprise Analytics and Data?
Competing on Analytics: A Follow Up to Thomas H. Davenport’s Post in HBR
Thomas Davenport Book “Competing On Analytics”

Solution Brief: The Intelligent Data Platform

Author Twitter: @MylesSuer

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Analytics Stories: A Banking Case Study

Right to winAs I have shared within other post within this series, businesses are using analytics to improve their internal and external facing business processes and to strengthen their “right to win” within the markets that they operate. In banking, the right to win increasingly comes from improving two core sets of business capabilities—risk management and customer service.

Significant change has occurred in risk management over the last few years following theAnalytics subprime crisis and the subsequent credit crunch. These environmental changes have put increased regulatory pressure upon banks around the world. Among other things, banks need to comply with measures aimed at limiting the overvaluation of real estate assets and at preventing money laundering. A key element of handling these is to ensuring that go forward business decisions are made consistently using the most accurate business data available. It seems clear that data consistency can determine the quality of business operations especially business risk.

At the same time as banks need to strengthen their business capabilities around operations, and in particular risk management, they also need to use better data to improve the loyalty of their existing customer base.

Banco Popular launches itself into the banking vanguard

Banco Popular is an early responder regarding the need for better banking data consistency. Its leadership created a Quality of Information Office (the Office uniquely is not based within IT but instead with the Office of the President) with the mandate of delivering on two business objectives:

  1. Ensuring compliance with governmental regulations occurs
  2. Improving customer satisfaction based on accurate and up-to-date information

Part of the second objective is aimed at ensuring that each of Banco Popular’s customers was offered the ideal products for their specific circumstances. This is interesting because by its nature it assists in obtainment of the first objective. To validate it achieves both mandates, the Office started by creating an “Information Quality Index”. The Index is created using many different types of data relating to each of the bank’s six million customers–including addresses, contact details, socioeconomic data, occupation data, and banking activity data. The index is expressed in percentage terms, which reflects the quality of the information collected for each individual customer. The overarching target set for the organization is a score of 90 percent—presently, the figure sits at 75 percent. There is room to grow and improve!

Current data management systems limit obtainment of its business goals

Unfortunately, the millions of records needed by the Quality Information Office are spread across different tables in the organization’s central computing system and must be combined into one information file for each customer to be useful to business users. The problem is that they had depended on third parties to manually pull and clean up this data. This approach with the above mandates proved too slow to be executed in timely fashion. This, in turn, has impacted the quality of their business capabilities for risk and customer service. According to Banco Popular, their approach did not create the index and other analyses “with the frequency that we wanted and examining the variables of interest to us,” explains Federico Solana, an analyst at the Banco Popular Quality of Information Office.

Creating the Quality Index was just too time consuming and costly. But not improving data delivery performance had a direct impact on decision making.

Automation proves key to better business processes

TrustTo speed up delivery of its Quality Index, Banco Popular determined it needed to automate it’s creation of great data—data which is trustworthy and timely. According to Tom Davenport, “you can’t be analytical without data and you can’t be really good at analytics without really good data”. (Analytics at Work, 2010, Harvard Business Press, Page 23). Banco Popular felt that automating the tasks of analyzing and comparing variables would increase the value of data at lower cost and ensuring a faster return on data.

In addition to fixing the Quality Index, Banco Popular needed to improve its business capabilities around risk and customer service automation. This aimed at improving the analysis of mortgages while reducing the cost of data, accelerating the return on data, and boosting business and IT productivity.

Everything, however, needed to start with the Quality Index. After the Quality Index was created for individuals, Banco Popular created a Quality of Information Index for Legal Entities and is planning to extend the return on data by creating indexes for Products and Activities. For the Quality Index related to legal entities, the bank included variables that aimed at preventing the consumption of capital as well as other variables used to calculate the probability of underpayments and Basel models. Variables are classified as essential, required, and desirable. This evaluation of data quality allows for the subsequent definition of new policies and initiatives for transactions, the network of branches, and internal processes, among other aspects. In addition, the bank is also working on the in-depth analysis of quality variables for improving its critical business processes including mortgages.

Some Parting Remarks

In the end, Banco Popular has shown the way forward for analytics. In banking the measures of performance are often known, however, what is problematic is ensuring the consistency of decision making across braches and locations. By working first on data quality, Banco Popular ensured that the quality of data measures are consistent and therefore, it can now focus its attentions on improving underling business effectiveness and efficiency.

Related links

Related Blogs

Analytics Stories: A Financial Services Case Study
Analytics Stories: A Healthcare Case Study
Who Owns Enterprise Analytics and Data?
Competing on Analytics: A Follow Up to Thomas H. Davenport’s Post in HBR
Thomas Davenport Book “Competing On Analytics”

Solution Brief: The Intelligent Data Platform

Author Twitter: @MylesSuer

 

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Who Owns Enterprise Analytics and Data?

processing dataWith the increasing importance of enterprise analytics, the question becomes who should own the analytics and data agenda. This question really matters today because, according to Thomas Davenport, “business processes are among the last remaining points of differentiation.” For this reason, Davenport even suggests that businesses that create a sustainable right to win use analytics to “wring every last drop of value from their processes”.

The CFO is the logical choice?

enterpriseIn talking with CIOs about both enterprise analytics and data, they are clear that they do not want to become their company’s data steward. They insist instead that they want to be an enabler of the analytics and data function. So what business function then should own enterprise analytics and data? Last week an interesting answer came from a CFO Magazine Article by Frank Friedman. Frank contends that CFOs are “the logical choice to own analytics and put them to work to serve the organization’s needs”.

To justify his position, Frank made the following claims:

  1. CFOs own most of the unprecedented quantities of data that businesses create from supply chains, product processes, and customer interactions
  2. Many CFOs already use analytics to address their organization’s strategic issues
  3. CFOs uniquely can act as a steward of value and an impartial guardian of truth across the organizations. This fact gives them the credibility and trust needed when analytics produce insights that effectively debunk currently accepted wisdom

Frank contends as well that owning the analytics agenda is a good thing because it allows CFOs to expand their strategic leadership role in doing the following:

  • Growing top line revenue
  • Strengthening their business ties
  • Expanding the CFO’s influence outside the finance function.

Frank suggests as well that analytics empowers the CFO to exercise more centralized control of operational business decision making. The question is what do other CFOs think about Frank’s position?

CFOs clearly have an opinion about enterprise analytics and data

A major Retail CFO says that finance needs to own “the facts for the organization”—the metrics and KPIs. And while he honestly admits that finance organizations in the past have not used data well, he claims finance departments need to make the time to become truly 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”. This CFO claims as well that “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”. A Food and Beverage CFO agrees with the Retail CFO by saying that almost every piece of data is financial in one way or another. CFOs need to manage all of this data since they own operational performance for the enterprise. CFOs should own the key performance indicators of the business.

CIOs should own data, data interconnect, and system selection

A Healthcare CFO said he wants, however, the CIO to own data systems, data interconnect, and system selection. However, he believes that the finance organization is the recipient of data. “CFOs have a major stake in data. CFOs need to dig into operational data to be able to relate operations to internal accounting and to analyze things like costs versus price”. He said that “the CFOs can’t function without good operational data”.

An Accounting Firm CFO agreed with the Healthcare CFO by saying that CIOs are a means to get data. She said that CFOs need to make sense out of data in their performance management role. CFOs, therefore, are big consumers of both business intelligence and analytics. An Insurance CFO concurred by saying CIOs should own how data is delivered.

CFOs should be data validators

Data AnalysisThe Insurance CFOs said, however, CFOs need to be validators of data and reports. They should, as a result, in his opinion be very knowledgeable on BI and Analytics. In other words, CFOs need to be the Underwriters Laboratory (UL) for corporate data.

Now it is your chance

So the question is what do you believe? Does the CFO own analytics, data, and data quality as a part of their operational performance role? Or is it a group of people within the organization? Please share your opinions below.

Related links

Solution Brief: The Intelligent Data Platform

Related Blogs

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

Twitter: @MylesSuer

 

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Posted in CIO, Data First, Data Governance, Enterprise Data Management | Tagged , , , | 6 Comments

CFO Rising: CFO’s Show They Are Increasingly Business Oriented

The Rising CFO is Increasingly Business Oriented

CFO risingAt 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

CFO risingThe 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

CFO risingThe 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

CFO risingThe 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

Data AnalysisThe 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

FixThe 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.

Final remarks

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.

Related links

Solution Brief: The Intelligent Data Platform

Related Blogs
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
Twitter: @MylesSuer

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Analytics Stories: A Financial Services Case Study

As I indicated in my last case study regarding competing on analytics, Thomas H. Davenport believes “business processes are among the last remaining points of differentiation.” For this reason, Davenport contends that businesses that create a sustainable right to win use analytics to “wring every last drop of value from their processes”. For financial services, the mission critical areas needing process improvement center are around improving the consistency of decision making and making the management of regulatory and compliance more efficient and effective.

Why does Fannie Mae need to compete on analytics?

Fannie MaeFannie Mae is in the business of enabling people to buy, refinance, or rent homes. As a part of this, Fannie Mae says it is all about keeping people in their homes and getting people into new homes. Foundational to this mission is the accurate collection and reporting of data for decision making and risk management. According to Tracy Stephan at Fannie Mae, their “business needs to have the data to make decisions in a more real time basis. Today, this is all about getting the right data to the right people at the right time”.

Fannie Mae claims when the mortgage crisis hit, a lot of the big banks stopped lending and this meant that Fannie Mae among others needed to pick up the slack. Their action here, however, caused the Federal Government to require them to report monthly and quarterly against goals that the Federal Government set for it. “This meant that there was not room for error in how data gets reported”. In the end, Fannie Mae says three business imperatives drove it’s need to improve its reporting and its business processes:

  1. To ensure that go forward business decisions were made consistently using the most accurate business data available
  2. To avoid penalties by adhering to Dodd-Frank and other regulatory requirements established for it after the 2008 Global Financial Crisis
  3. To comply with reporting to Federal Reserve and Wall Street regarding overall business risk as a function of: data quality and accuracy, credit-worthiness of loans, and risk levels of investment positions.

Delivering required Fannie Mae to change how it managed data

AnalyticsGiven these business imperatives, IT leadership quickly realized it needed to enable the business to use data to truly drive better business processes from end to end of the organization. However, this meant enabling Fannie Mae’s business operations teams to more effectively and efficiently manage data. This caused Fannie Mae to determine that it needed a single source of truth whether it was for mortgage applications or the passing of information securely to investors. This need required Fannie Mae to establish the ability to share the same data across every Fannie Mae repository.

But there was a problem. Fannie Mae needed clean and correct data collected and integrated from more than 100 data sources. Fannie Mae determined that doing so with its current data processes could not scale. And as well, it determined that its data processes would not allow it to meet its compliance reporting requirements. At the same time, Fannie Mae needed to deliver more proactive management of compliance. This required that it know how critical business data enters and flows through each of its systems. This includes how data was changed by multiple internal processing and reporting applications. As well, Fannie Mae leadership felt that this was critical to ensure traceability to the individual user.

The solution

analyticsPer its discussions with business customers, Fannie Mae’s IT leadership determined that it needed to get real time, trustworthy data to improve its business operations and to improve its business processes and decision making. As said, these requirements could not be met with its historical approaches to integrating and managing data.

Fannie Mae determined that it needed to create a platform that was high availability, scalable, and largely automating its management of data quality management.  At the same time, the platform needed to provide the ability to create a set of business glossaries with clear data lineages. Fannie Mae determined it needed effectively a single source of truth across all of its business systems. According to Tracy Stephan, IT Director, Fannie Mae, “Data quality is the key to the success of Fannie Mae’s mission of getting the right people into the right homes. Now all our systems look at the same data – that one source of truth – which gives us great comfort.” To learn more specifics about how Fannie Mae improved its business processes and demonstrated that it is truly “data driven”, please click on this video of their IT leadership.

Related links
Solution Brief: The Intelligent Data Platform
Related Blogs
Thomas Davenport Book “Competing On Analytics”
Competing on Analytics
The Business Case for Better Data Connectivity
The CFO Viewpoint upon Data
What an enlightened healthcare CEO should tell their CIO?

Twitter: @MylesSuer

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