Key #1: Strategy

The first key to a successful Business Analytics Program that we will discuss is the strategy. In a Business Analytics Program, we mentioned that one of the most critical, yet commonly overlooked, essential elements of focus is around the changing strategy. Not only does an initial vision need to be developed for an organization, but a way to review the strategy, the changing needs throughout the organization, and the program processes developed along the way is also necessary as an ongoing and core element of the program.

Many organizations begin analytic initiatives with grassroots efforts — and sometimes it may not be the lack of strategy but rather too many silos of strategy that create the initial difficulty in managing the program. As an organization matures in its analytic capability or Business Analytics technologies, it often later surfaces that a cohesive strategy is required to increase collaboration and decision making, reduce costs, and steer the ship in the same direction to achieve corporate goals.

It is also one of the top reasons a Business Analytics Program often doesn't show expected value. Without defined direction, goals, outcomes, and a way to execute that is a shared vision with the key stakeholders, siloed initiatives occur that produce only small, tactical, and incremental gains. It is often a process of analytic maturity that helps organizations realize the opportunities and gains that can be made by strategically planning their Business Analytics programs in their organizations.

Our organizations were among the various pioneers of the early Business Intelligence Programs that evolved to Business Analytics. We experienced growing pains throughout the process, but we blazed a trail to analytic maturity where we can share practical tips for moving a program at a more rapid pace. How quickly you rise beyond the silos of analytics into a more collaborative approach can depend on how the program is managed — but the pressures of a constantly changing environment always need to be recognized and continually planned for. We will identify some key forward-looking elements that will help you shortcut some common challenges.

It doesn't mean that silo deployments aren't valuable as a starting point, or as a way to realize value. Quite the contrary: Analytics silos are often a starting point to short-term tactical gains that develop the appetite — and provide an initial training ground — for more strategic analytics. However, the longer-term benefits are frequently driven by cross-functional collaboration — which can often take more time and require more planning due to the politics and complexity of the task. Therefore, we recommend putting a program in place that supports the people, process, and technology elements that will deliver the long-term benefits as a highly successful best practice.

A successful Business Analytics Program starts with a well-defined, coordinated business and IT strategy. This will require a continual focus on the strategy itself and constant adjustments to ensure the organization understands the goals and expected outcomes, prioritizes, and connects the analytics strategy to the corporate strategy. The strategy should have both a long-term vision and a pragmatic series of steps and a roadmap on how you plan to get there. It should also address the many factors at play — factors that move beyond the technology itself and encompass the people, processes, and business drivers that create the need for a Business Analytics Program. Most important, it will recognize that it will change over time.

The Strategy Framework

In our first book, we introduced what we called the "Strategy Framework." This framework consists of three distinct parts (depicted in Figure 3):

• A business alignment strategy: Understanding the overall business strategy and then tying corporate objectives to functional objectives so that the application of the Business Analytics Strategy is of high value, understood, and aligned. Identifying what the business strategy is behind the information is absolutely the most critical step in the strategy. Technologies are not implemented for the sake of technology — there are business goals that teams need to be working toward to realize value.

• An organizational and behavioral strategy: Creating the right culture that drives performance and an organizational strategy that will tie business strategy to execution. This is the glue that will help the people in the organization clearly realize the use of technology and modify behaviors that will ensure the right processes are implemented and a data-driven culture can be embraced.

• A technology strategy: Identifying the technology infrastructure and capabilities that will enable the business to achieve excellence: Do we have the right capabilities for the right individuals to be able to monitor, analyze, predict, and develop a plan of action to support the strategy? How are we implementing these technologies to ensure we are achieving the lowest total cost of ownership (TCO) while enabling the business to be successful? How are we including newer innovation, whether it's mobile strategy, big data, self-service, cloud, or other technologies?

Under each of these aspects, several areas need to be addressed and considered when preparing a strategy. The Strategy Framework is a practical guide that organizations in any industry can use to help create a strategy. It is the foundation for creating the Business Analytics Program.

However, there are times when creation of the Business Analytics Strategy has also run awry — when teams prepare a strategy in a silo without consulting the broader organizational stakeholders that need to embrace the strategy. These deviations may occur intentionally or unintentionally — unintentionally when teams attempt to boil the ocean, or intentionally when they become too focused on technology, risking loss of confidence and support of critical key stakeholders. So let's take a moment to look at what a strategy should and should not be:

• A Business Analytics Strategy is not:

* A single destination or one-time project

* A siloed effort of one department (it may start in one area, and there may be tactical strategies in that department, but it should not remain a siloed initiative if analytic maturity is the goal)

* A requirements document for reports or a dashboard

* Just about information technology and the IT department (e.g., a document the IT team prepares about technology selection)

* A 400-page document that is circulated to all the teams

* An architecture design or vision

• A Business Analytics Strategy is:

* A roadmap that demonstrates and includes a long-term vision, created as a roadmap of smaller wins and iterations supported by key stakeholders that supports business strategies (e.g., gaining market share, increasing revenues, reducing costs, discovering opportunities)

* A collaborative effort across teams — line of business, finance, IT — that takes people, process, and technology into consideration

* A journey that is fluid, changing, and agile and requires commitments of people, funding, and governance

* A series of documents agreed, communicated, committed to, and embraced by a particular audience at a particular point in time

Implementing a Business Intelligence technology is not a Business Analytics Strategy. It is but one tactic of many that will help facilitate the end goal.

Tactics will help an organization achieve the larger corporate or organizational strategic goals, such as lowering operational costs, increasing market penetration, and/ or achieving better returns on investment for shareholders. However tactics, in and of themselves, don't rise to the level of strategies.

Tactical Conflicts

When a tactic is implemented as a strategy, confusion rises among the masses. The tactics of one department, subsidiary, or silo may actually result in conflict with the tactics of another entity, further confusing management's alignment with the overall business strategy. A strategy needs to be supported by objectives, and tactics should definitely support the overall plan — but it is easy for organizations to jump to tactics to try to solve a problem quickly.

For instance, multiple Business Analytics Programs within a company may develop conflicting data and reports, making it more difficult for information users to get a clear perspective on progress toward strategic or tactical goals. Trying to rectify the problem by implementing a common technology platform may not, and likely will not, solve the problem if the information that is being presented is different or subject to interpretation (e.g., lack of consistent master data, dimensional conformity, metadata).

This presents a delicate conundrum: How can an organization execute on its strategy in an environment in which a wide variety of conflicting tactical tools are used across multiple information silos?

There should be a clear overall business strategy as a first step. All companies develop short- and long-term business plans. The Business Analytics Strategy should then support these plans — managing the processes required to bring the intelligence (via the information value chain) together. Companies then need to bring the IT, line-of-business, and various other teams together to develop insights and drive action that stems from these insights to move forward. This step is as critical as the strategy itself in a successful organization. Harnessing the technology that can better inform and enable these teams forward is a necessary task. Technology is the relatively easy part, however, only if these other components of the Business Analytics Strategy are in place.

This framework provides a practical guide to help an organization understand many of the considerations it needs to include in a strategy. What it will not do is provide you with a "cookie-cutter" strategy. It recognizes that each organization is different; culture, structure, maturity level, and strategy will all affect a Business Analytics Program, and each of these needs to be part of the well-thought-out plan to ensure success.

Just as a Business Analytics Program is a journey, so is the strategy — an ongoing effort that should, in fact, change over time, should be measured regularly against established benchmarks, and should be flexible enough to change. It should also be reviewed, adjusted, and agreed to on a regular basis and tweaked and realigned to ensure it is meeting the evolving expectations of the business.

In this chapter, we provide specific practical tips that will help you create and manage your Business Analytics Program strategy to ensure it takes into account the various areas of strategy and allows for change, maturity, and growth. We discuss:

• Maturity of a Business Analytics Program strategy

• Assessment of strategy

• Strategy design

• Business strategy alignment

• Prioritization and roadmap

• Metrics framework and measurement

• Managing ongoing strategy change

By understanding these areas and proactively building a strategy that will support a growing Business Analytics Program over time, organizations will benefit with a more rapid road to success and the ability to achieve performance goals.

Maturity of a Business Analytics Program Strategy

To help understand the journey of what strategy evolution looks like over time for a Business Analytics Program, we will use the concept of the Analytics Quotient Maturity Model that demonstrates the journey over time. While each journey often has many evolutions, there are common patterns that we have seen regardless of our industry or organizational makeup. By understanding some of these common evolutions and charting a typical journey, we feel it will help an organization identify the current state of its Business Analytics Program and outline a path to build its vision.

If we look back to the early stages, before a formal Business Analytics Program was officially kicked off, a Business Analytics Strategy may not have formally existed within the organization. There is likely always a corporate business strategy, but it may be supported by a variety of disconnected analytics strategies on how to achieve those goals — each monitoring the business the best way it knows how. A variety of tools and varying levels of skilled individuals that can use analytic tools and data management strategies exist in the various business areas. Without a defined Business Analytics Strategy, there is potential for disconnect between business units, technology strategies, and information silos.

It is often not the lack of business strategy that creates a challenge, but rather the instance of too many silos of strategy evolving from the core framework that creates chaos. Without a coordination beyond the top-level strategy, it creates an organization and infrastructure where information likely resides in various pockets within the organization, but there's no clear consensus between both business and IT to bring that information into a form that is useful to support the business strategy. Individuals get used to running heroics to pull data when asked and spend time on spreadsheets and various tools to answer business questions in a reactive fashion. This may create local heroes, but it is not optimal for the enterprise and may actually be detrimental. IT teams understand that there is a data challenge, but they may not understand the priorities or have the support of the business to manage the data.

The early stages of analytics in an organization may be perpetuated for a considerable period of time as the different entities within the organization struggle to meet continual information demands and as the enterprise fails to understand the benefits of data integration and the accompanying analytics that are enabled via a coordinated Business Analytics Strategy. In fact, quite often these various entities don't completely understand the overall strategy but are only responding to the requests for unique pieces of information. As time goes on, each siloed entity may have developed its own techniques for defining goals and accumulating data, forming its own automation strategy to make that data available. This includes using a variety of spreadsheets, databases, dashboards, and other analytic tools and analysis methods.

Yet, the longer organizations take a tactical approach to respond to business challenges without a clear image of how the information can be used by senior management and across teams and business domains, the greater the danger of redundancy, the potential for misinformation, and, in the worst case, the chance of failure to comply with regulations or internal company rules. Plus, the more diverse the implementations of tools, the more difficult it is to pull together accurate or consistent information across the enterprise.

When these needs are recognized among a savvy team of champions, this is the time that the Business Analytics Program often begins to formulate. A group of stakeholders begins to identify the need to apply analytics with a consolidated set of data and reporting tools, apply structure to the various information requests, and consider the necessary metrics required to move into the next stage of the process. There may be a specific driver that is recognized as requiring cross-functional collaboration, such as trying to get a 360-degree view of the customer. Sometimes, a savvy executive or champion that has become versed in Business Analytics or who has seen success in the past from analytics initiatives that are cross-functionally oriented pulls the teams together. The Business Analytics Program is born, and communication across information domains begins to be realized. As the needs of the decision makers become clearer, departments or domains begin working together to understand how best to source and supply the supporting information. This working group typically focuses on a few top needs of the business where a few information areas can most logically come together. We call them sweet spots of information — the proposed outcomes and key areas that deliver value to the business strategy as identified by the group; the process is best managed by designing a roadmap detailing how to prioritize and then accumulate and organize the data for analysis. At this stage, the value of the sweet spots needs to be rated against the ease of creating and deploying solutions to achieve the desired results. The roadmap should be prioritized to facilitate a series of small successes to drive momentum for the project. Over time, following this skeletal roadmap, more sweet spots will be identified, prioritized, and achieved in the process. This step-by-step iterative process helps to eliminate initial frustrations, keeps the initial project on track, and builds support for the overall program through time. This process is also critical to staying agile over time, with teams working closely to achieve the project together.