Category Archives: CIO
In our interviews of CIOs, they have told us that connecting what IT is doing to business strategy has become a higher priority than even things like improving technical orchestration and overall process excellence. Being CIO today has become much more about business alignment than technology alignment. This means that CIOs and their teams need to understand their firm’s business problems almost as well as they understand their implementations of information technology. One area where CIOs say they are trying to do a better job of alignment is in working with their firm’s Chief Marketing Officer. Confirming this is a recent CIO Magazine Survey that found initiatives around revenue, customer acquisition, and customer retention receiving top IT priority these days.
Geiger IT solves a persistent business problem by aligning with the marketing team
One CIO that that has really taken this to heart is the Dale Denham who is the CIO at Geiger. Dale and his IT team decided that they needed to get closer to their firm’s marketing organization and by doing so was able to go after a persistent business problem and change the IT-business relationship in the process.
At Geiger, their marketing team was limited in their ability to add new products. Competitively, the marketing team needed to improve their product selection. However, they were hitting the wall in updating and maintaining their product mix. Geiger provides its customers with more than 5,000 products, each having as many as 350 variations. This translates to a 175,000 product permutations to price and manage. At the same time, Geiger sells its products through 500 Sales Partners—this, in turn, can create an additional layer of permutation.
The source of this business problem was that Geiger’s ERP and Website systems that required the users to manipulate multiple screens to get to product data and product codes into the system. The system was difficult enough that it took about six weeks to train someone to input product data. Think about the time needed to then do this this across all products, product permutations, and channel partners.
To fix things, Dale and his team partnered with the business. Doing it together rather than separately enabled the IT organization and the business to collaborate and to build a better and more permanent partnership. Dale says, “We have really enjoyed implementing the solution, because the business units are now working very closely with IT”. Dale claims as well the relationship with their business units has gotten to be a very solid, trusting relationship with them, and very collaborative. They have learned to trust IT’s input, and IT has learned a lot from the business units about how they operate and like to operate.”
The impact of working together is clear
The solution that the business and IT derived cut the time to train people in half. In fact, Dale says that new system users are relatively productive within a week, because the solution is faster and easier to use. Dale says that the time per product entry went down from an hour and half to thirty minutes. For this reason, marketing teams are more efficient. Overall, it reduced the process from two months to one week for them to update the customer facing website. By automating the process, they were able to speed up marketing processes. This means marketing can now add and extend to the existing marketing mix and increase customer satisfaction and potential increase customer upsell and cross sell.
The historical the process created a lot of efficiencies for marketing. Marketing staff is now much more focused on what they’re doing from day to day. They have the ability to update products faster from prices and this has stabilized business margins. At the same time, marketing was able to reduce invoice discrepancies. Given all of this, marketing staff is more engaged that they are able to get the job done in a timely manner and to be able to get to market faster with the products.
The solution took the data entry process down from ninety minutes to thirty minutes. And now with this increased efficiency, the marketing staff has focused more of its time on the quality of copy for the product and on getting the graphics of the images up to websites. This has improved overall customer experience. And of course they were able to expand their product offering. They now have three times the throughput capacity, which is what is going to allow Geiger to grow in the future as it provides more product options to customers.
Already they have found that customers are happier with the immediate larger breadth of product to choose from. Lastly, their leadership team is happier because they are able to get more opportunities to grow the business. And this gives them much more ability to satisfy customers and provide for the additional growth they need in the future.
Clearly business and IT alignment is all the rage today. But it starts and ends with a team that solves meaningful business problems. Geiger is a great of example of how to do this right. If you want to learn more about what Geiger did and how they solved their marketing problems, please click this hyperlink.
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…)
30% or higher of each company’s businesses are unprofitable
According to Jonathan Brynes at the MIT Sloan School, “the most important issue facing most managers …is making more money from their existing businesses without costly new initiatives”. In Brynes’ cross industry research, he found that 30% or higher of each company’s businesses are unprofitable. Brynes claims these business losses are offset by what are “islands of high profitability”. The root cause of this issue is asserted to be the inability of current financial and management control systems to surface profitability problems and opportunities. Why is this the case? Byrnes believes that management budgetary guidance by its very nature assumes the continuation of the status quo. For this reason, the response to management asking for a revenue increase is to increase revenues for businesses that are profitable and unprofitable. Given this, “the areas of embedded unprofitability remain embedded and largely invisible”. At the same time to be completely fair, it should be recognized that it takes significant labor to accurately and completely put together a complete picture on direct and indirect costs.
The CFO needs to become the point person on profitability issues
Byrnes believes, nevertheless, that CFOs need to become the corporate point person for surfacing profitability issues. They, in fact, should act as the leader of a new and important role, the chief profitability officer. This may seem like an odd suggestion since virtually every CFO if asked would view profitability as a core element of their job. But Byrnes believes that CFOs need to move beyond broad, departmental performance measures and build profitability management processes into their companies’ core management activities. This task requires the CFO to determine two things.
- Which product lines, customers, segments, and channels are unprofitable so investments can be reduced or even eliminated?
- Which product lines, customers, segments, and channels are the most profitable so management can determine whether to expand investments and supporting operations?
Why didn’t portfolio management solve this problem?
Now as a strategy MBA, Byrnes’ suggestion leave me wondering why the analysis proposed by strategy consultants like Boston Consulting Group didn’t solve this problem a long time ago. After all portfolio analysis has at its core the notion that relative market share and growth rate will determine profitability and which businesses a firm should build share, hold share, harvest share, or divest share—i.e. reduce, eliminate, or expand investment. The truth is getting at these figures, especially profitability, is a time consuming effort.
KPMG finds 91% of CFOs are held back by financial and performance systems
As financial and business systems have become more complex, it has become harder and harder to holistically analyze customer and product profitability because the relevant data is spread over a myriad of systems, technologies, and locations. For this reason, 91% of CFO respondents in a recent KPMG survey said that they want to improve the quality of their financial and performance insight from the data they produce. An amazing 51% of these CFOs, also, admitted that the “collection, storage, and retrieval financial and performance data at their company is primarily a manual and/or spreadsheet-based exercise”. Think about it — a majority of these CFOs teams time is spent collecting financial data rather than actively managing corporate profitability.
How do we fix things?
What is needed is a solution that allows financial teams to proactively produce trustworthy financial data from each and every financial system and then reliably combine and aggregate the data coming from multiple financial systems. Having accomplished this, the solution needs to allow financial organizations to slice and dice net profitability for product lines and customers.
This approach would not only allow financial organizations to cut their financial operational costs but more importantly drive better business profitability by surfacing profitability gaps. At the same time, it would enable financial organizations to assist business units in making more informed customer and product line investment decisions. If a product line or business is narrowly profitable and lacks a broader strategic context or ability to increase profitability by growing market share, it is a candidate for investment reduction or elimination.
Strategic CFOs need to start asking questions of their business counterparts starting with their justification for their investment strategy. Key to doing this involves consolidating reliable profitability data across customers, products, channel partners, suppliers. This would eliminate the time spent searching for and manually reconciling data in different formats across multiple systems. It should deliver ready analysis across locations, applications, channels, and departments.
Some parting thoughts
Strategic CFOs tell us they are trying to seize the opportunity “to be a business person versus a bean counting historically oriented CPA”. I believe a key element of this is seizing the opportunity to become the firm’s chief profitability officer. To do this well, CFOs need dependable data that can be sliced and diced by business dimensions. Armed with this information, CFOs can determine the most and least profitability, businesses, product lines, and customers. As well, they can come to the business table with the perspective to help guide their company’s success.
Solution Brief: The Intelligent Data Platform
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
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
This got me thinking: What is the biggest bottleneck in the delivery of business value today? I know I look at things from a data perspective, but data is the biggest bottleneck. Consider this prediction from Gartner:
“Gartner predicts organizations will spend one-third more on app integration in 2016 than they did in 2013. What’s more, by 2018, more than half the cost of implementing new large systems will be spent on integration. “
When we talk about application integration, we’re talking about moving data, synchronizing data, cleansing, data, transforming data, testing data. The question for architects and senior management is this: Do you have the Data Foundation for Execution you need to drive the business results you require to compete? The answer, unfortunately, for most companies is; No.
All too often data management is an add-on to larger application-based projects. The result is unconnected and non-interoperable islands of data across the organization. That simply is not going to work in the coming competitive environment. Here are a couple of quick examples:
- Many companies are looking to compete on their use of analytics. That requires collecting, managing, and analyzing data from multiple internal and external sources.
- Many companies are focusing on a better customer experience to drive their business. This again requires data from many internal sources, plus social, mobile and location-based data to be effective.
When I talk to architects about the business risks of not having a shared data architecture, and common tools and practices for enterprise data management, they “get” the problem. So why aren’t they addressing it? The issue is that they find that they are only funded to do the project they are working on and are dealing with very demanding timeframe requirements. They have no funding or mandate to solve the larger enterprise data management problem, which is getting more complex and brittle with each new un-connected project or initiative that is added to the pile.
Studies such as “The Data Directive” by The Economist show that organizations that actively manage their data are more successful. But, if that is the desired future state, how do you get there?
Changing an organization to look at data as the fuel that drives strategy takes hard work and leadership. It also takes a strong enterprise data architecture vision and strategy. For fresh thinking on the subject of building a data foundation for execution, see “Think Data-First to Drive Business Value” from Informatica.
* By the way, Informatica is proud to announce that we are now a sponsor of the MIT Center for Information Systems Research.
Sometimes, the choice of a name has unexpected consequences. Often these consequences aren’t fair. But they exist, nonetheless. For an example of this, consider the well-known study by the National Bureau of Economic Research study that compares the hiring prospects of candidates with identical resumes, but different names. During the study, titled a “Field Experiment on Labor Market Discrimination,” employers were found to be more likely to reply candidates with popular, traditionally Caucasian names than to candidates with either unique, eclectic names or with traditionally African-American names. Though these biases are clearly unfair to the candidates, they do illustrate a key point: One’s choice when naming something can come with perceptions that influence outcomes.
For an example from the IT world, consider my recent engagement at a regional retail bank. In this engagement, half of the meeting time was consumed by IT and business leaders debating how to label their Master Data Management (MDM) Initiative. Consider these excerpts:
- Should we even call it MDM? Answer: No. Why? Because nobody on the business side will understand what that means. Also, as we just implemented a Data Warehouse/Mart last year and we are in the middle of our new CRM roll-out, everybody in business and retail banking will assume their data is already mastered in both of these. On a side note; telcos understand MDM as Mobile Device Management.
- Should we call it “Enterprise Data Master’? Answer: No. Why? Because unless you roll out all data domains and all functionality (standardization, matching, governance, hierarchy management, etc.) to the whole enterprise, you cannot. And doing so is a bad idea as it is with every IT project. Boiling the ocean and going live with a big bang is high cost, high risk and given shifting organizational strategies and leadership, quick successes are needed to sustain the momentum.
- Should we call it “Data Warehouse – Release 2”? Answer: No. Why? Because it is neither a data warehouse, nor a version 2 of one. It is a backbone component required to manage a key organizational ingredient – data –in a way that it becomes useful to many use cases, processes, applications and people, not just analytics, although it is often the starting block. Data warehouses have neither been conceived nor designed to facilitate data quality (they assume it is there already) nor are they designed for real time interactions. Did anybody ask if ETL is “Pneumatic Tubes – Version 2”?
- Should we call it “CRM Plus”? Answer: No. Why? Because it has never intended or designed to handle the transactional volume and attribution breadth of high volume use cases, which are driven by complex business processes. Also, if it were a CRM system, it would have a more intricate UI capability beyond comparatively simple data governance workflows and UIs.
Consider this; any data quality solution like MDM, makes any existing workflow or application better at what it does best: manage customer interactions, create orders, generate correct invoices, etc. To quote a colleague “we are the BASF of software”. Few people understand what a chemical looks like or does but it makes a plastic container sturdy, transparent, flexible and light.
I also explained hierarchy management in a similar way. Consider it the LinkedIn network of your company, which you can attach every interaction and transaction to. I can see one view, people in my network see a different one and LinkedIn has probably the most comprehensive view but we are all looking at the same core data and structures ultimately.
So let’s call the “use” of your MDM “Mr. Clean”, aka Meister Proper, because it keeps everything clean.
While naming is definitely a critical point to consider given the expectations, fears and reservations that come with MDM and the underlying change management, it was hilarious to see how important it suddenly was. However, it was puzzling to me (maybe a naïve perspective) why mostly recent IT hires had to categorize everything into new, unique functional boxes, while business and legacy IT people wanted to re-purpose existing boxes. I guess, recent IT used their approach to showcase that they were familiar with new technologies and techniques, which was likely a reason for their employment. Business leaders, often with the exception of highly accomplished and well regarded ones, as well as legacy IT leaders, needed to reassure continuity and no threat of disruption or change. Moreover, they also needed to justify their prior software investments’ value proposition.
Aside from company financial performance and regulatory screw-ups, legions of careers will be decide if, how and how successful this initiative will be.
Naming a new car model for a 100,000 production run or a shampoo for worldwide sales could not face much more scrutiny. Software vendors give their future releases internal names of cities like Atlanta or famous people like Socrates instead of descriptive terms like “Gamification User Interface Release” or “Unstructured Content Miner”. This may be a good avenue for banks and retailers to explore. It would avoid the expectation pitfalls associated with names like “Customer Success Data Mart”, “Enterprise Data Factory”, “Data Aggregator” or “Central Property Repository”. In reality, there will be many applications, which can claim bits and pieces of the same data, data volume or functionality. Who will make the call on which one will be renamed or replaced to explain to the various consumers what happened to it and why.
You can surely name any customer facing app something more descriptive like “Payment Central” or “Customer Success Point” but the reason why you can do this is that the user will only have one or maybe two points to interface with the organization. Internal data consumers will interact many more repositories. Similarly, I guess this is all the reason why I call my kids by their first name and strangers label them by their full name, “Junior”, “Butter Fingers” or “The Fast Runner”.
I would love to hear some other good reasons why naming conventions should be more scrutinized. Maybe you have some guidance on what should and should not be done and the reasons for it?
If you ask a CIO today about the importance of data to their enterprises, they will likely tell you about the need to “compete on analytics” and to enable faster business decisions. At the same time, CIOs believe they “need to provide the intelligence to make better business decisions”. One CIO said it was in fact their personal goal to get the business to a new place faster, to enable them to derive new business insights, and to get to the gold at the end of the rainbow”.
Similarly, another CIO said that Big Data and Analytics were her highest priorities. “We have so much knowledge locked up in the data, it is just huge. We need the data cleaning and analytics to pull this knowledge out of data”. At the same time the CIOs that we talked to see their organizations as “entering an era of ubiquitous computing where users want all data on any device when they need it.”
Why does faster, better data really matters to the enterprise?
So why does it matter? Thomas H. Davenport says, “at a time when firms in many industries offer similar products and use comparable technologies, business processes are among the last remaining points of differentiation.” A CIO that we have talked to concurred in saying, “today, we need to move from “management by exception to management by observation”. Derick Abell amplified upon this idea when he said in his book Managing with Dual Strategies “for control to be effective, data must be timely and provided at intervals that allow effective intervention”.
Davenport explains why timely data matters in this way “analytics competitors wring every last drop of value from those processes”. Given this, “they know what products their customers want, but they also know what prices those customers will pay, how many items each will buy in a lifetime, and what triggers will make people buy more. Like other companies, they know compensation costs and turnover rates, but they can also calculate how much personnel contribute to or detract from the bottom line and how salary levels relate to individuals’ performance. Like other companies, they know when inventories are running low, but they can also predict problems with demand and supply chains, to achieve low rates of inventory and high rates of perfect orders”.
What then prevents businesses from competing on analytics?
Moving to what Davenport imagines requires not just a visualizing tool. It involves fixing what is allying IT’s systems. One CIO suggested this process can be thought of like an athlete building the muscles they need to compete. He said that businesses really need the same thing. In his eyes, data cleaning, data security, data governance, and master data management represent the muscles to compete effectively on analytics. Unless you do these things, you cannot truly compete on analytics. At UMASS Memorial Health, for example, they “had four independent patient registration systems supporting the operations of their health system, with each of these having its own means of identifying patients, assigning medical record numbers, and recording patient care and encounter information”. As a result, “UMass lacked an accurate, reliable, and trustworthy picture of how many unique patients were being treated by its health system. In order to fix things, UMASS needed to “resolve patient, provider and encounter data quality problems across 11 source systems to allow aggregation and analysis of data”. Prior to fixing its data management system, this meant that “UMass lacked a top-down, comprehensive view of clinical and financial performance across its extended healthcare enterprise”.
UMASS demonstrates how IT needs to fix their data management in order to improve their organization’s information intelligence and drive real and substantial business advantage. Fixing data management clearly involves delivering the good data that business users can safely use to make business decisions. It, also, involves ensuring that data created is protected. CFOs that we have talked to say Target was a watershed event for them—something that they expect will receive more and more auditing attention.
Once our data is good and safe, we need to connect current data sources and new data sources. And this needs to not take as long as it did in the past. The delivery of data needs to happen fast enough that business problems can be recognized as they occur and be solved before they become systemic. For this reason, users need to get access to data when and where they it is needed.
With data management fixed, data intelligence is needed so that business users can make sense out of things faster. Business users need to be able to search and find data. They need self-service so they can combine existing and new unstructured data sources to test data interrelationship hypothesis. This means the ability to assemble data from different sources at different times. Simply put this is all about data orchestration without having any preconceived process. And lastly, they need the intelligence to automatically sense and respond to changes as new data becomes collected.
Some parting thoughts
The next question may be whether competing upon data actual pay business dividends. Alvin Toffler says “Tiny insights can yield huge outputs”. In other words, the payoff can be huge. And those that do so will increasingly have the “right to win” against their competitors as you use information to wring every last drop of value from your business processes.
Solution Brief: The Intelligent Data Platform
As adjunct university faculty, I get to talk to students about how business strategy increasingly depends upon understanding how to leverage information. To make discussion more concrete, I share with students the work of Alvin Toffler. In The Third Wave, Toffler asserts that we live in a world where competition will increasingly take place upon the currency and usability of information.
In a recent interview, Toffler said that “given the acceleration of change; companies, individuals, and governments base many of their daily decisions on obsoledge—knowledge whose shelf life has expired.” He continues by stating that “companies everywhere are trying to put a price on certain forms of intellectual property. But if…knowledge is at the core of the money economy, than we need to understand knowledge much better than we do now. And tiny insights can yield huge outputs”.
Driving better information management in the information age
To me, this drives to three salient conclusions for information age businesses:
- Information needs to drive further down organizations because top decision makers do not have the background to respond at the pace of change.
- Information needs to be available faster which means that we need to reducing the processing time for structure and unstructured information sources.
- Information needs to be available when the organization is ready for it. For multinational enterprises this means “Always On” 24/7 across multiple time zones on any device.
Effective managers today are effective managers of people and information
Effective managers today are effective managers of information. Because processing may take too much time, Toffler’s remarks suggest to me we need to consider human information—the ideas and communications we share every day—within the mix of getting access to the right information when it is needed and where it is needed. Now more than ever is the time for enterprises to ensure their decision makers have the timely information to make better business decisions when they are relevant. This means that unstructured data, a non-trivial majority of business information, needs to be made available to business users and related to existing structured sources of data.
Derick Abell says that “for (management) control to be effective, data must be timely and provided at interval that allows effective intervention”. Today this is a problem for most information businesses. As I see it, information optimization is the basis of powering the enterprise through “Third Wave” business competition. Organizations that have the “right to win” will have as a core capability better-than-class access to current information for decision makers.
Putting in place a winning information management strategy
If you talk to CIOs today, they will tell you that they are currently facing 4 major information age challenges.
- Mobility—Enabling their users to view data anytime, anyplace, and any device
- Information Trust—Making data dependable enough for business decisions as well as governing data across all business systems.
- Competing on Analytics—Getting information to business users fast enough to avoid Toffler’s Obsoledge.
- New and Big Data Sources—Connecting existing data to new value added sources of data.
Some information age
Lots of things, however, get in the way of delivering on the promises of the Information Age. Our current data architecture is siloed, fragile, and built upon layer after layer of spaghetti code integrations. Think about what is involved just to cobble together data on a company’s supply chain. A morass of structured data systems have vendor and transaction records locked up in application databases and data warehouses all over the extended enterprise. So it is not amazing that enterprises struggle to put together current, relevant data to run their businesses upon. Functions like finance depend largely upon manual extracts being massaged and integrated in spreadsheets because of concern over the quality of data being provided by financial systems. Some information age!
How do we connect to new sources of data?
At the same time, many are trying today to extend the information architecture to add social media data, mobile location data, and even machine data. Much of this data is not put together in the same way as data in an application database or data warehouse. However, being able to relate this data to existing data sources can yield significant benefits. Think about the potential benefit of being able to relate social interactions and mobile location data to sales data or to relate machine data to compliance data.
A big problem is many of these new data types potentially have even more data quality gaps than historical structured data systems. Often the signal to noise for this data can be very low for this reason. But this data can be invaluable to business decision making. For this reason, this data needs to be cleaned up and related to older data sources. Finally, it needs to be provided to business users in whatever manner they want to consume it.
How then do we fix the Information Age?
Enabling the kind of Information Age that Toffler imagined requires two things. Enterprises fix their data management and enable the information intelligence needed to drive real business competitive advantage. Fixing data management involves delivering good data that business users can safely make decisions from. It, also, involves ensuring that data once created is protected. CFOs that we have talked to say Target was a watershed event for them—something that they expect will receive more and more auditing attention.
We need at the same time to build the connection between old data sources and new data sources. And this needs to not take as long as in the past to connect data. Delivery needs to happen faster so business problems can be recognized and solved more quickly. Users need to get access to data when and where they need it.
With data management fixed, data intelligence needs to provide business users the ability to make sense out of things they find in the data. Business users need as well to be able to search and find data. They, also, need self-service so they can combine existing and new unstructured data sources to test data interrelationship hypothesis. This means the ability to assemble data and put it together and do it from different sources at different times. Simply put this is about data orchestration without any preconceived process. And lastly, business users need the intelligence to automatically sense and respond to changes as new data is collecting.
Tiny insights can yield huge outputs
Obviously, there is a cost to solving our information age issues, but it is important to remember what Toffler says. “Tiny insights can yield huge outputs”. In other words, the payoff is huge for shaking off the shackles of our early information age business architecture. And those that do this will increasingly have the “right to win” against their competitors as they use information to wring every last drop of value from their business processes.
Solution Brief: The Intelligent Data Platform
The CIO Challenged
If you ask a CIO today about their challenges, several things would clearly make the list. CIOs that I know personally are feeling a bit of Future Shock. They say that things are changing a lot faster these days than they did in the past. One CIO said to me in exasperation, “things are changing every 18 months”. Given this, I recently sat down with CIOs from several different industries to get their perspectives on how the CIO role is changing and the challenges they feel in their role as CIO. This post will focus upon the latter.
The healthcare CIO participating said that CIOs need to manage four large mega trends simultaneously—mobile, cloud, social, and big data. At the same time in healthcare, they have the added complexity of Meaning Use, ICT 10, and HL7. For these reasons, this CIO worries about keeping the IT lights on while at the same time helping the business to expand. This CIO sees healthcare is clearly entering an era of ubiquitous computing with the iPad becoming the rounding and vitals instrument of choice. This links mobility, integration, and compliance around a standard like HL7. HL7 provides this CIO with a framework for exchanging, integrating, sharing, and retrieving of electronic health information. Like other CIOs that we talked to, our healthcare CIO says he needs to understand his enterprises business better in order to be a better partner.
Our next CIO is from the insurance. He sees CIOs in general being challenged to move from being a builder of stuff to an orchestrator of business services. This CIO sees cloud and loosely oriented partnerships bringing vendor management to the forefront. At the same time, he feels challenged to provide application integration in a service oriented manner. He says that IT organizations need today to orchestrate across IT regardless of device. As well, he believes that IT organizations need to stitch together an IT that is fungible and support service oriented architecture. At the same time, he says that his business users “believe that data is strategic but they need it provided to them in a way that creates predictive capabilities and drives top line revenue”. We and our business customers know that we need to fix our mutual data problems in order to use data better. This CIO said believes that he needs to fix his enterprise’s data hygiene first in order to improve business outcomes.
The Manufacturing CIO participating said that CIOs have an opportunity to create informative analytics and help the business find value. However, this CIO worries that CEOs and CFOs are about to start complaining to their IT organizations that the information garnered from Big Data and Business Intelligence does not really make them more money. He claims, to make more money, IT organizations need to connect the dots between their transactional systems, BI systems, and the planning systems. More specifically, they need to convert insight into action. To do this, the business needs to be enabled to be more proactive and to cut the time it takes to execute. This means that IT needs to enable the enterprise to generate value different than its competitors. This CIO worries, therefore, about IT’s ability to drive flexibility and agility. We need to respond to the rate of change and be able to prototype faster at the same time as we cut the cost of failure. This CIO claims that CIOs needs to more actively manage the information lifecycle even though the business may own the data. Lastly, this CIO says that IT organizations need to be more forward looking. We need to be looking at things cross discipline. We need to be looking for new business insights. We have piles and piles of data from which to draw interesting insights from. How do you connect and create new business insights?
Getting the CFOs to understand that technology is not a cost center was really important to our 4th CIO. We need to get everyone to understand that IT isn’t separate from the business. At the same time, we need to get business leaders to understand technology better. There is a real West Coast vs. East Coast split regarding business technology literacy. We need business leaders to start asking for digital services that support their product and service offerings. And this is all about data. “Think about it. What we do in IT is all about the intake of data, storing data, processing data, and analyzing data. And we need to provide the intelligence to make better decisions. Competing with analytics is what we need to enable. Like an athlete that needs muscles—data needs cleaning, security, mastering, and governance to enable the business to compete with analytics”.
Our broadcast CIO is focused on the explosion of Big Data. “I need to get my management team exposed to Big Data Analysis. I need as well to get the resources to do this well”. We need for example to get the business answers to its questions around customer behavior. From an integration perspective, this CIO said that she needs to get service based technology deployed. At the same time, she said I need to be able to have business apps for my business and consumer users to subscribe. This CIO said that speed to clients from integrated systems is a big issue. We need today to connect everything together.
CIOs as whole feel are feeling challenged
CIOs regardless of industry feel challenged. They feel challenged by changes coming at them in general and in industry specific mandates and standards. They clearly need to move faster and to move from organizations that are about getting the internals of IT running well to organizations that can absorb new technology models, scale up and down in “Internet time”, and flex seamlessly to support business model innovation. For more information, see the related links below:
Adrian gathered experts and built workgroups to dig into the issue and do root cause analysis. The workgroups came back with some pretty surprising results.
- Most people expected that “incorrect data” (missing, out of date, incomplete, or wrong data) would be the main problem. What they found was that this was only #5 on the list of issues.
- The #1 issue was “Too much data.” People working with the data could not find the data they needed because there was too much data available, and it was hard to figure out which was the data they needed.
- The #2 issue was that people did not know the meaning of data. And because people had different interpretations of the data, the often produced analyses with conflicting results. For example, “claims paid date” might mean the date the claim was approved, the date the check was cut or the date the check cleared. These different interpretations resulted in significantly different numbers.
- In third place was the difficulty in accessing the data. Their environment was a forest of interfaces, access methods and security policies. Some were documented and some not.
In one of the workgroups, a senior manager put the problem in a larger business context;
“Not being able to leverage the data correctly allows competitors to break ground in new areas before we do. Our data in my opinion is the ‘MOST’ important element for our organization.”
What started as a relatively straightforward data quality project became a more comprehensive enterprise data management initiative that could literally change the entire organization. By the project’s end, Adrian found himself leading the data strategy of the organization.
This kind of story is happening with increasing frequency across all industries as all businesses become more digital, the quantity and complexity of data grows, and the opportunities to offer differentiated services based on data grow. We are entering an era of data-fueled organizations where the competitive advantage will go to those who use their data ecosystem better than their competitors.
Gartner is predicting that we are entering an era of increased technology disruption. Organizations that focus on data as their competitive edge will have the advantage. It has become clear that a strong enterprise data architecture is central to the strategy of any industry-leading organization.
For more future-thinking on the subject of enterprise data management and data architecure see Think ‘Data First” to Drive Business Value