CHAPTER 3

Challenged Organizations: When Rugged Individualism and Department Silos Aren't Enough

What we've learned so far: People, information processes, technical infrastructure, and culture are the pillars that organizations must strengthen to gain insight from information and use that insight to make sound decisions and validate strategies. The best way to do this is through an understanding of an Information Maturity Model, an unbiased, vendor-neutral approach that allows each organization to craft its own roadmap toward information maturity. The maturity model uses levels that each organization can assess their maturity against.

You might be tempted to skip this chapter, as it describes organizations with significant information maturity issues. You probably don't think your organization is that bad off. Think again. In a recent report, Gartner expects that by 2015 20 percent of Global 1000 organizations will have established a strategic focus on information infrastructure equal to that of application management.¹ That means at least 80 percent of the largest companies don't have that now. Since four out of five of you are likely in these circumstances, reading about the Challenged Level organizations will help you get a better understanding of where you stand today.

Organizations stuck at the Individual Level operate in a near total enterprise data vacuum even if they are churning out a lot of data and reports. Competitiveness and market conditions put them in a precarious state. Organizations whose operations are at the Departmental Level are common across multiple industries and exist around the world. They might be well-led or poorly run, large or small, innovative or staid. Often these organizations have units, brands, regions, and departmental silos that do a great job using their data to produce their own view and perspective of their performance. What they don't have is an enterprise-wide view of business performance. They are at particularly high risk of inadvertently cannibalizing revenue and profits due to their inability to understand their performance across business functions.

What these organizations have in common is that they are at risk. They don't have a complete view of their organization “value chain.” They don't understand the underlying metrics that drive their revenue and profits. Both Individual and Departmental organizations are considered challenged, because that verb fits them to a T.

If these challenges sound familiar, you'll want to learn more about how your organization can develop an aggressive roadmap to improve its environment today and start evolving toward a more profitable level of organizational maturity.

GETTING ALONG ONE DAY AT A TIME: ORGANIZATIONS AT THE INDIVIDUAL LEVEL

The business focus of organizations at the Individual Level is on immediate and tactical needs—the here and now. Information gathering evolves to support day-to-day operations. Narrow “stovepipe” applications and transactional systems exist, but they support fragmented business operations.

The executives, managers, and staff of these organizations generally make decisions in unplanned and chaotic information environments. Leaders do not have long-range plans regarding data use nor do they place any value on information standards. As a result, information quality and consistency is questionable. Gut feel, personal experience, and intuition take the place of information as the key factors in decision making. What information is available is often controlled by a “Data Maverick” that you'll learn more about later in this chapter. Luck and visionary leaders are probably the only things keeping these organizations in business.

While these organizations may be profitable at certain stages of the market lifecycle, their low level of information management maturity limits their ability to sustain this success over the long term. These organizations are operating in a very risky environment, and can approach a cliff with unforeseen consequences. Here are a few reasons why:

• Inconsistent views of business performance significantly increase the chance for inaccurate decisions and policies. If you are an Internet retailer offering “free” shipping for some orders, is that a marketing cost? Or does it come off the bottom line? And is the data being collected in enough detail so you can even tell whether free shipping helps or hurts your organization?
• Reaction time is slowed. When accurate enterprise or even departmental view of performance is lacking, the organization is unable to react effectively to market changes and challenges—economic, competitive, resources, or others. If your organization is tied up trying to consolidate spreadsheets sent in from regional offices all over the globe, it doesn't have time to react to market changes, let alone plot strategy to be proactive.
• Compliance with government audits and regulations is problematic. Expending extra resources and time to make the data comply with government regulations does not help the bottom line, but it is necessary in light of rules like the Basel Accords and the USA Patriot Act.
• Strong candidates leave or avoid your organization. The lack of new talent, coupled with the revolving door of individuals who don't want to deal with Data Mavericks, limits the organization's ability to operate efficiently, innovate, and survive.
• Expansion is difficult and risky. The lack of consistent data, standards, and governance presents significant challenges that hinder the organization's ability to operate in different markets and regions.

Decisions after the Fact

From the 30,000-foot perspective, organizations at the Individual Level are focused on getting the job done today. It's a tactical approach that provides few opportunities to look at the bigger picture. These organizations often end up relying too much on external consultants for strategic projects—and virtually everything is a project. Asking questions like “At what point would we be better off exiting this business?” or “How much money should we spend to gain new customers?” involves at least some significant data gathering and cleansing that is frequently accompanied by a lengthy series of ad hoc steps to hunt down the data and create a report that is out-of-date almost from the moment it arrives on the executive's desk.

True story: When a marketing executive arrived at his new job at a retailer he received a binder that showed the results of an entire year's analytics effort. It said that the best customers were the ones who shopped most frequently. It didn't address what marketing efforts worked or which were the most cost-effective—just a report that stated the obvious.

Being reactive is par for the course. Individual organizations can rarely see micro patterns emerge before they start nibbling at the bottom line. As long as data is perceived as correct for operational purposes—bills are accurate, orders are filled correctly, collections are made promptly (and even that doesn't always happen)—upper-level management is content. For everything else, managers make decisions based on hunches, or what worked at their last company, or maybe what they heard at a conference. And when they decide to find some data—perhaps to justify a hunch—efforts to track down the data meet roadblocks. Maybe the Data Maverick doesn't like the direction of the manager's request so she finds data to shape a narrative of what she thinks is going on. Or maybe the request has to go to the IT department, which puts it in a queue behind the pressing needs of the operational side of the business.

Managers often don't understand how risky the situation is. Not only are these organizations less able to respond to dips in sales or revenue—they can be bowled over by high demand for their service or product. A simple illustration of this is small and mid-sized organizations that book “daily deal” offers through companies like Groupon. Meant to drive new business at a modest marketing cost, only 44 percent of these offers were profitable for restaurants surveyed by a Rice University professor.² These organizations often had a hard time figuring out what kind of offer to construct that would not cause them to spend more to staff their operations than they would get back in repeat business at full price. Some actually shut their doors after participation in these offers caused them to lose money or they lost valuable customers paying full price.

To say the least, Individual Level organizations aren't equipped to operate globally. This is due to the fact that a fundamental understanding of the organization's business performance and value chain is lacking at the Enterprise Level. Good understanding of the internal processes, the viability of the organization's products and services, and the organization's interactions and collaboration with its external partners are all essential requirements to enable the organization to operate on a global level. The inability to operate effectively at a global level may limit the organization's competitive advantage. It is a particular burden for financial services companies eager to expand beyond their country of origin. Whether they want to provide banking services to expats, service their customers with business operations in other countries, or simply to export what they see as innovative and well-priced products, information immaturity threatens not just profitability, but it can put them at regulatory risk.

In our current economic and market conditions, these organizations can only survive if they have little or no external market pressure from the competition. Once the pressure increases, Individual Level organizations are forced to look internally at their current operation and evolve their organization to a higher capability level (maturity).

Is your organization functioning at the Individual Level? Let's take a look now at how people, information processes, technical infrastructure, and culture operate at this level.

Rogues Manning the Spreadsheets

In this type of environment, Data Mavericks thrive. These are individuals with the technical skills to work magic with a spreadsheet. They can tell you all about their favorite desktop database, or they know just who to ask in IT—and what to ask for—to gain access to operational systems or get a useable report back. A department's monthly report, weekly sales figures, or quarterly marketing plan can't make it out the door without the help of this person because no one else can access the information or knows what to do with it.

While some of these individuals try to spread knowledge across the department, often they have wised up to their value and become information hoarders and data gatekeepers. Some grow frustrated quickly and leave for companies with a more mature commitment to being insight driven—leaving a gaping knowledge void in their wake. In organizations mired at the Individual Level, these mavericks are sprinkled across the organization—with multiple mavericks in the biggest business units.

The Data Mavericks are very interested in information because they like to work with data, and they've discovered it's their ticket to life employment, at least as long as your organization stays stuck in a low level of information maturity. If no one else can whip up a report or set of numbers, they're golden. But before you look askance at the data analyst in marketing who figured out how to write Excel programs that trimmed your catalog list without impacting revenue, understand that they are often aided and abetted by managers who haven't a clue how to use data—or are frankly frightened by it.

Dismissive of business intelligence solutions, dashboards, and metric development efforts, Data Mavericks gain a powerful foothold because organizations don't value hiring, motivating, and retaining individuals with critical thinking, technology, and analytics skills outside the IT organization. And the decision makers who manage these individuals are so focused on day-to-day crises that they can't look at matters strategically.

The existence of Data Mavericks isn't a problem, per se, unless they try to fight off efforts to develop a more mature approach to information gathering. A larger issue in understanding the “people” part of the maturity puzzle is making sure decision makers want to base their decisions on quality information—and that they aren't too comfortable working with Data Mavericks to create information that makes both of them look good at the expense of the greater good of your organization. All that said, probably the best sign that you are operating at the Individual Level is that you can't produce critical reports if you lose certain staff.

WHEN “HAVE IT YOUR WAY” ISN'T A GOOD THING

You're in charge of an organization that sells subscriptions for various services. You would like to know the renewal rate. That's a really simple question, right? It should be. For companies at the Individual Level, it's anyone's guess how many different answers you're going to get, or whether the method used to answer the question one year will be the same the next. Most of the effort tends to be ad hoc. Consistent information processes often don't exist. Information is pieced together with lots of queries to IT or through requests to Data Mavericks who make decisions on the fly as to how to interpret the questions and present the data.

When organizations operate at this level they struggle with performance metrics because of their sloppy information processes. On the financial side, there is usually a set of metrics (often standardized by industry) and information is gathered to report on them. But other types of metrics are generally not collected and used, including information on customer satisfaction, internal efficiencies, and external market conditions. Most of the metrics are lagging metrics; that is, they focus on past performance. Rather than a dashboard with information updated regularly, you get a report that is quickly out of date. IT and data quality governance rarely exist. People who prize autonomy appreciate the lack of standard protocol—it lets them gather and report data in whatever manner suits them. And without documented processes, standards, and policies, nothing is repeatable and any effort to analyze your data becomes a project.

SUPERHIGHWAYS AND DIRT ROADS

It's not all bad news at the Individual Level. There are often strong pockets of technology use, including enterprise resource planning (ERP) and supply chain systems. IT typically has the mission-critical processes running smoothly—from keeping the e-mail virus-free to processing the payroll (if that's done in-house). But the business performance calculations—the “where are we now and where are we going in the future”—is often powered by a collection of unconnected and unsophisticated desktop and personal productivity tools, such as Microsoft Excel and Access. Everyone has his or her own pool of data, way of analyzing it, and business rules—sometimes his or her own customized tool. Methods are rarely documented, so when the Data Maverick who created the program leaves, the program is orphaned.

If there are no technology standards at the department or Enterprise Level, sharing data is a challenge. If more sophisticated tools are used, it is only because ambitious, self-taught employees have acquired them. Automating the distribution of information to decision makers is not a common practice. Consequently, decision makers frequently rely on instinct. Multiple and inconsistent reports and business views create confusion and redundancy and result in questionable decision quality.

As the hunt for data is often time-consuming, there is very little time to analyze the data. Organizations that have matured and are operating at the Enterprise Level frequently report that the biggest difference (other than just having accurate, reliable data available) is that they now have time to analyze data.

It's also very tough for the Individual Level organization to take advantage of new technologies. With such a scattered ad hoc infrastructure, it would be difficult to calculate how much money you could save using cloud computing, for instance. Master data management and service-oriented architecture are beyond the ability of the organization to use effectively. You can forget about analyzing Big Data. But even smaller efforts can be problematic. A hotel chain, for instance, might want to use text analytics to monitor online comments. It could outsource the effort—but without mature information processes in-house it can't sync up the information it's receiving (complaints about front desk staff, product quality, or marketing offers) with internal information and then get the right information to the right people to quickly fix the problem—or even determine the severity of complaints and how they should be addressed.

A Little Too Much Rugged Individualism

The words and phrases that have positive connotations in many cultures—“maverick,” “rugged individualism,” and “gut instinct”—are not necessarily positive when it comes to working with data. This doesn't mean that a mature information organization is run by humorless statisticians crunching numbers in an effort to stamp out all signs of creativity. Instead, it's using data effectively to foster creativity—and that's not what is happening at the Individual Level. Instead, these organizations have a culture that allows chaos.

You try to reward people for the right reasons, but in Individual Level organizations, people tend to be rewarded for all the wrong reasons. These are the people politically aligned to a certain decision maker, or whose “gut” bet paid off big (even if it may have cannibalized profit because this organization often doesn't know what drives profit), or who are seen as “indispensable.” In this politically charged organization, managers exercise a lot of command and control. Although they issue edicts, the Data Mavericks hold the day-to-day power, since they hold the key to the information that managers need. The environment is internally competitive. Thought leaders and innovators who propose anything “outside the box” are not encouraged or rewarded. They may, in fact, be viewed as a threat. And even if the situation is chaotic, the culture doesn't really like change.

Internal top-down communication is limited, and may only focus on providing general direction or financial targets.

This bunker mindset at the Individual Level tends to reward personal or product successes without analyzing their impact on other products or unknowingly undermines enterprise-wide profitability. Because success depends on the efforts of one or two talented workers, the organization's ability to identify and repeat successful information processes, products, or services is limited, especially if key personnel leave.

The ironic aspect is all the money that Individual Level organizations save by not investing in people and infrastructure costs indirectly in lost opportunity. Organizations at this level will sometimes invest in technologies to deal with data volume, or attempt to solve a problem because a Data Maverick convinced management a new solution was needed. But without consistent validation, quality standards, governance—and a culture populated with individuals ready to act on data—the technology investment is for naught. These organizations are the most likely to “turn off” an expensive investment because the groundwork wasn't prepared to effectively use it.

What is the most unfortunate thing about operating at the Individual Level? So few recognize that they are. Too often, organizations at this level face a major crisis that forces them to quickly evolve—an expensive and wrenching experience. Better to take a proactive approach to candidly identify their level before that happens.

CONSOLIDATED, BUT NOT COHESIVE: ORGANIZATIONS AT THE DEPARTMENTAL LEVEL

An interesting dilemma occurred around a convention booking at a resort hotel. The hotel's convention and marketing units were becoming increasingly savvy about using data to create offers. There was only one problem—they never worked together. Rates were assigned by a revenue management system. Both the marketing and the convention units were looking for slow periods to market more heavily, when there would be plenty of rooms available at a low rate. And they both independently locked on a specific weekend. A large convention was booked, rooms were blocked, but when individual travelers called to get the special rate created by marketing they were met with an “I'm sorry; we don't have any rooms available at that rate.” Marketing's time and expenses were wasted, and instead of making customers happy, they ticked them off.

Business units at this level don't ask: “How will this decision affect the organization as a whole?” They ask: “How will my department's metrics look better?” Unlike the Individual Level organization, these businesses often have entire departments that are savvy about using data, follow solid processes for working with and governing data, and take a team approach. Data Mavericks have been induced to play team ball. These are organizations that boast marketing departments that understand the total value of a customer or warranty groups that have slashed costs and optimized processes.

The problem is that data is stored and analytic applications are designed, developed, and supported from a departmental perspective without much consideration for how well those data might integrate with other units in the enterprise. As business units at the Departmental Level continue to act and think locally, the enterprise will end up with many information silos, each with its own version of the truth.

By becoming subject matter experts with regard to the information under their control, these business units tend to use their information access for political power and may even go so far as to shield the department from scrutiny at the enterprise reporting level. In many cases, enterprise goals and objectives are secondary to departmental goals, so much so that they may be tracked manually or not at all. To reach any enterprise-level decision or attempt to gain any enterprise-wide perspective, these conflicting silos of information must be painstakingly merged and rationalized. It is not uncommon for organizations at this level to have sophisticated data gathering and reporting abilities at the unit level—and for those units to then cut and paste their results into a spreadsheet that someone in a C-level executive's office must try to reconcile and synthesize.

In fairness, there are data-savvy groups aware of the possibilities that exist if they can integrate data with other units in the enterprise. They often report that significant roadblocks exist that they are not equipped to break down.

SUBJECT MATTER EXPERTS AND GATEKEEPERS

The Data Mavericks who agreed to be team players have migrated to jobs with titles like business analyst. Although the business units may have data governance and processes in place these analysts still spend a lot of time preparing and integrating information, and, if no automated business intelligence system is available, more time is needed to develop reports that put the best departmental spin on the data. Note the word “spin.” There still tends to be a lot of emphasis on using data to match a business unit's expectations versus reality. In other words, if the marketing department invested a lot of money in a specific advertising medium, they're going to look for data points to justify that expense.

Business analysts in the consolidated organization are valued and paid for their information skills. In some cases, they've built up shadow IT empires that clash with an organization's actual IT operation. In addition, a key differentiator between organizations at the Departmental Level and those at the Enterprise Level is that investment in resources, hardware, and training is usually funded by business units to satisfy departmental needs rather than any enterprise program for information and skills development.

The good news is that team players thrive in this type of organization. They have strong managers who defend the department and create internal cohesion. Those with an interest in information management are recognized and appreciated for their skills. The bad news is that the business unit-centric model tends to make it difficult for these individuals to work cooperatively with other departments. After all, those are competitors in the internal corporate struggle for power, recognition, and budget. If someone suggests a Center of Excellence to help create a more enterprise-wide method of dealing with data, the business units are likely to resist, fearing that their budgets or autonomy will be compromised.

Strong Interior, Weak Exterior

At this level, information is collected, assembled, accessed, and tracked on a Departmental Level. Data management processes are fairly well defined within each department but not across departments. Since analysis is based on a myopic view, it will not accurately reflect influences from outside the department. Sales and marketing, for instance, might be working with a similar set of numbers but reporting and analyzing them differently. Duplication of effort is common.

Even the simplest things, such as the definition of a “customer” or “sale,” can vary by business unit. Standardizing business rules across all the brands to better analyze costs is difficult and politically challenging. For example, if you charge for shipping, should that be revenue or should that be considered part of the cost? At one multichannel retailer, every brand defined it differently.

There is also a heavy focus on static reporting of operational measures, such as gross margins, total revenue, total expense, or inventory on hand. Business analysts perform some interactive analysis to distill other performance measures, but only at a Departmental Level.

If enforced, enterprise rules are left to interpretation by individual departments. Because these departments do maintain individual standards, they are pretty good at outsourcing functions (just like they are fairly good at finding their own technology providers). But just like with technology purchases, there is little corporate governance of this activity, limiting the advantages for economies of scale and consistent quality and vendor management.

Many Roads, Not Enough Bridges

There are some enterprise-wide approaches at Departmental Level organizations. Hardware and networking standards have been established across the enterprise, but each department prefers to use its own tools and data standards. Except for basic organization technical infrastructure, there are no enterprise-wide technology standards or frameworks. There might be dozens of departmental databases on servers stored in offices and maintained by individuals, most of them unknown to IT and some even unsupported by the central IT department or their vendors.

At this level, each department acquires and uses its own business intelligence tools—niche or proprietary solutions that address a specific function, such as campaign management, supplier evaluation, or budgeting. These tools might be quite sophisticated, but they cannot be used for broader applications outside the department. Without the oversight or control of an enterprise architecture group, redundancy of tools and applications is both a problem and an added expense. Moving to the next maturity level (Enterprise Level) may force business units to comply with the organization's IT standards or justify the use of their favorite applications to increase the overall return from existing technologies.

Individuals within a department typically have ready access to data for their department. Departmental data marts assemble data from the group's users and make it available in numerous reports, but these reports often present conflicting results across departments and provide limited enterprise context. For instance, marketing might be measuring the overall success of campaigns—the “lift” rates—but can they follow how the lift rate impacts the company's bottom line? One multichannel retailer, with multiple brands, discovered that discount coupons offered in one catalog cannibalized sales for another brand when it began taking an enterprise-wide view of its information. In addition, offering discount coupons on websites tends to draw in customers who buy one item with no deeper loyalty to the retailer. Finally, they realized that customers who discover the retailer through comparison shopping engines are rarely worth further promotion. This wouldn't work if brands kept their own information silos.

Departmental Level organizations aren't known for sharing information across business units. Needed information might be owned by other departments, and there is no formal way of accessing it. There is some collaboration via meetings, memos, and simple file sharing. But understanding the data still requires the tribal knowledge and goodwill of information gatekeepers. There is too much time spent finding, assembling, and debating the interpretation of information; too little time is spent making sense of it.

If standards aren't kept across silos, even efforts to get departments to share information are likely to fail. For example, the technical infrastructure may define customers, suppliers, and partners differently or use different account codes across departments. Enterprise master data is not well managed.

Departmental Level organizations can adapt to cutting-edge technologies within business units. High-speed analytics, for instance, is possible. But realizing a technology's full enterprise value requires more effort. Financial institutions have to calculate risk exposure across an enterprise and many have embraced high performance analytics to do that quickly—dropping the time to calculate loan defaults from several days to four hours. But if a mortgage group is doing that independently of commercial loans and that group is working independently of consumer loans, what happens when it is time to look at overall risk? Out come the electronic scissors, the virtual paste, and the spreadsheets.

In the area of text analytics, a marketing department might do a fabulous job of determining exactly what consumers like and dislike about a product. But without an enterprise approach, the exercise is just that—an exercise. The marketers can send their report to the warranty, manufacturing, and product development units, but their data might be telling them something different. “We're not getting reports that the buttons are sticky,” warranty will say. “Sticky buttons are a warranty problem,” says manufacturing. “Our data shows people like those buttons,” says product development.

By comparison, in Enterprise Level organizations, the technical infrastructure is capable of analyzing consumer comments and distributing them to all stakeholder groups who will collaborate in analyzing the results. Warranty could mine its own data to look for claims that relate to “sticky buttons” (but aren't called that), manufacturing can look for root causes, sales can track whether sticky button chatter is impacting sales, and product development can begin looking for a workaround at the next stage.

“Us versus Them”

The rewards in a Departmental Level organization revolve strictly around the success of a given unit, brand, or department. These units become expert at using data as “proof” of localized needs and accomplishments. Incentives are based on meeting departmental goals, which may or may not be in line with the best interests of the enterprise.

Change is embraced when it results in political or self-improvement gain for the department—or if it takes place in someone else's department (especially if it creates an opportunity to gain more resources). Change is viewed as a threat if it disrupts the department's own carefully groomed processes or if it requires disparate functional units to work together. Departments might actively resist change that benefits other groups or distracts them from their own missions, even if the company as a whole would benefit. Even under the best of circumstances, change is poorly communicated, cautiously approached, and limited in results.

One of the worst features of Departmental Level organizations is a tendency to assume that if the business units are individually meeting goals, then the enterprise will meet its goals. And if business units aren't meeting goals? Well, they'll argue individually for more money and support. You can see where this is headed. It's the Monday morning meeting where the heads of each business unit present their own version of the truth in the board meeting with the C-level executives and squabble for additional resources. And worse, these organizations don't know what the truth is because there is no one with information that isn't enmeshed in a unit or department. It's “us” versus “them” to the nth degree. The unfortunate consequence of this is the inability of the executive team to make accurate and timely decisions based on well integrated and agreed upon enterprise performance information. They may eventually generate the correct and required information, but it is usually too late and some decisions may have already been made based on gut feeling or intuition.

The “everyone is in it for themselves” mentality that grips Departmental Level organizations is obviously damaging. The decision that best benefits my group might be gained at your expense. The high cost to maintain the organization's technical infrastructure will continue to grow, allowing more duplication of efforts, hardware, and technology. The inconsistency in coding and maintaining the master data and in storing critical information will continue to introduce challenges in integrating data from various business units. Since the organization is challenged by its inability to develop and analyze its business performance at the Enterprise Level, inaccurate decisions and strategies are made and adopted. You can't achieve a competitive advantage in the market, and deal with market changes and challenges, working in this level.

Failure to see the big picture really poses problems during an economic downturn or when faced with competition that is savvier about gaining insights from information. Root cause analysis for the failure of something—a new product or long-existing popular product—is compromised by never-ending rounds of finger pointing. And businesses operating at the Departmental Level are hamstrung during merger and acquisition discussions by not fully understanding their organizational value chain. If they buy a company and let it work as another silo, they create a problem. If they buy a company and try to integrate operations, the level of information discord can be eye opening.

The good news is that these organizations often possess almost everything necessary to have a unified, enterprise-wide view of information. There is data talent capable of playing for a team and technologies are used that yield strong results. It takes leadership and guts—but not gut instinct—to get to the next level. Let's find out how.

UNDERSTANDING THE TRUE CONSEQUENCES OF THE CHALLENGED LEVELS

It is difficult, frankly, to get many companies to understand what level they are at and why it is such a problem. Many of today's successful executives climbed the corporate ladder before there was even that much data to be had. Their leadership, strong gut instinct, and boldness in moving their organizations into new areas was done in a less competitive environment—certainly as it pertains to information. The Individual Level organizations are, to some extent, more aware of issues because executives who ask a simple question and can get no answers are aware of the problem. Even when getting conflicting answers at the Department Level organizations, executives often figure that this is less an institutional problem than a little turf fighting between departments. If putting an end to those conflicting answers (by moving to the Enterprise Level) involves draining internal battles, maybe a few conflicting answers is a small price to pay. Increasingly, this just won't suffice. Maybe the best way to muster up the courage to face down the silos is to see what an Enterprise Level organization looks like.

BUSINESS TRANSFORMATION STRATEGY OBJECTIVES FOR CHALLENGED ORGANIZATIONS

In Chapter 2, three requirements were described for organizations to successfully embark on a business transformation journey. Organizations will need to develop a business transformation strategy, sponsored by the executive team, to adequately address the three requirements and gradually transform the organization. Chapter 7 is dedicated to the strategy discussions. The strategy will depend on the maturity level of your organization. If you believe your organization has the symptoms and characteristics just described as associated with Challenged organizations, the following should be key objectives for your business transformation strategy:

• Assess your current organization capabilities in the four key pillars to determine which maturity level your organization is operating on and determine capability gaps.
• Identify critical business areas with the highest information and organizational challenges as well as the highest potential business value.
• Leverage your current key talents and resources as part of your strategy. Although they may not be operating in the most efficient manner, they still have significant knowledge of the business.

NOTES

  1. Roxane Edjlali, Regina Casonato, Ted Friedman, Mark A. Beyer, and Donald Fineberg, “Predicts 2013: Big Data and Information Infrastructure,” Gartner, November 30, 2012, www.gartner.com/document/2258415?ref=QuickSearch&sthkw=Predicts%202013%3A%20Big%20Data%20and%20Information%20Infrastructure.

  2. Utpal Dholakia, “How Businesses Fare With Daily Deals As They Gain Experience: A Multi-Time Period Study of Daily Deal Performance Fair,” June 2012, http://news.rice.edu/wp-content/uploads/2012/07/2012-07-05-DailyDeals.pdf.