Quality Data

“The dirty little secret of big data is that most organizations spend the vast majority of their time cleaning and integrating data—not actually analyzing it,” says Tom Davenport, a professor of IT and management at Babson College and thought leader in analytics with such books as Competing on Analytics and Only Humans Need Apply: Winners and Losers in the Age of Smart Machines.

We talk about the quality of the data often throughout this book and we want to stress it again. The quality of your data is table-stakes for any analytical exercise. Without good data, you will not be able to produce meaningful analysis for a monetization strategy. More importantly, though, the end consumer of this information will not trust the output of the analysis.

There are some key standards you want to make sure the datasets you use adhere to:

• Completeness—The completeness of the data refers to any missing or partial data in the dataset.
• Conformity—How well the dataset adheres to standards reflects its conformity.
• Consistency—Data consistency refers to the values of the data, which must be consistent throughout the dataset.
• Accuracy—The accuracy of the data is focused on the data being consistent, non-duplicative, and complete.
• Duplication—Data duplication refers to multiple records in a database that are exact or partial duplicates of each other.
• Integrity—The integrity of data refers to the accuracy and consistency of the data over its lifecycle.
• Timeliness—How often the data is updated defines its timeliness.
• Availability—The availability of the data refers to how often you will be able to access the data for analysis.
• History—How much history is available for analysis will determine how you are able to perform analysis like trends or linear regression.

The variety of data sources and types of data is important as well. We encourage you to think outside the box when utilizing data both within your organization and outside. In their article, “Analytics That Work: Deploying Self-Service and Data Visualization for Faster Decisions,” the team at Harvard Business Review Analytical Services conducted a survey of over 827 business managers and came away with several insights into the importance of varied data sources. One such use of external data comes from Belk's department store:

Insights gained from a variety of sources, both internal and external, are translating to real dollars for Belk. Work with your team to understand all data sources available to enhance your solution. The more insights you are able to deliver that are actionable, the better decisions you will empower and the more competitive your organization will be in the marketplace.

Be Specific

The more specificity you can apply to your Monetization Strategy the higher the likelihood that the actions can be executed. If your monetization strategy is too high level or abstract, the ability to derive actions and deploy them throughout the organization will be difficult. In addition, if your strategy does not fit into your team's ability to execute, it will not be actionable. This is especially true if you work in a large organization that requires you to navigate many internal groups before the action reaches a consumer.

For example, if you are an airline company, pricing may be a key focus of your strategy. You have developed a monetization strategy to price coach seats. This strategy may be difficult to deploy because it is too broad. However, if your strategy focuses on price by a particular route for a particular time period, that may be more actionable. Better yet, if you focus on a specific route, for a particular time of day, for a particular day of the week, your chances for an actionable strategy are very likely.

Limiting the scope of your monetization strategy will depend on your circumstances. Below are some suggestions to help you narrow your monetization strategy:

• Channel—What are the various selling channels your organization uses? Maybe you start with just one channel to narrow the focus.
• Geography or Region—Picking a specific country or region can help limit the options and add a layer of specificity to your strategy.
• Time Period—Choosing a daily or weekly view versus a quarterly or yearly might make the strategy more actionable.
• Customer Segment—Can you focus on just one customer type? This is a great option for providing incremental value for an underserved segment or a growth segment.
• Product or Service Category—Limiting the strategy to one product or service can provide more focus.

Be Holistic

Not to contradict ourselves, but you need to be specific and also holistic. What do we mean by this? The Monetization Strategy needs to fit into the broader organization and, therefore, it needs to be holistic. This means knowing your constraints, being collaborative, and aligning to the overall corporate goals of your company.

Knowing constraints both within and outside your organization helps you determine your guardrails. We recommend building a list of possible constraints at the beginning of your project to determine if you have a risk that needs consideration before you get too far into your efforts.

Constraints can come in all sizes and shapes. Time constraints on getting something out to market during a major selling season is a big one to consider. For example, if you are a retailer, to launch something in time for the fall season can be a time window you want to hit.

Resource constraints is another boundary you want to make sure you understand. Do you have a limited budget or number of employees who can participate? Maybe the data scientist group has low bandwidth and they will be a constraint for your effort. Other constraints include historical precedence, regulatory, internal policies, and organizational.

Collaboration is another consideration for being holistic. If you are not collaborating with other departments, they may not give the okay to move forward with any actions that come from the strategy. A great example of this comes from Aditya Joshi and Eduardo Giménez's article, “Decision-Driven Marketing,” where a firm's marketing department was building marketing collateral for the sales team. They discuss the divide that existed between marketing and sales:

To help close the gap with other departments, look to engage them early in the process. Should they be a stakeholder on the project? How is what you are doing going to benefit them? Why should they care? Spend some energy reaching out to other departments and getting them excited about your efforts and how it will benefit them.

Another key concern regarding being holistic is making sure what you are doing fits into the broader strategy of the company. If you align your hypothesis and business objective back to corporate objectives, you should be fine. However, you don't want to be caught going in one direction while the firm is pivoting in another. Maybe your firm sells services and products and has decided to get out of the services business. If your monetization strategy deals with the service side of the business, it may not get legs in the organization.

Along with fitting into the broader strategy of the company, leveraging other departments' work will often be necessary if you are in a large organization. As an example, if in developing your monetization strategy for the airline industry, your strategy charges higher baggage fees, it may not fit the overall pricing strategy for baggage fees for your company. In this case, the strategy is unlikely to be adopted as the one-off in pricing will be difficult to support.

Be careful to get input along the way as you develop your strategy and leverage other departments' good work to inform your work.

Actionable

The ability to take action on the decision from the Monetization Strategy is paramount. So many of the analytics developed today simply help someone “read the news.” They are informative, but do not guide you to a specific action they should take to capture an opportunity. Your monetization strategy needs to be actionable and should consider this guiding principle as not optional.

As you develop the actions that someone will execute on, consider the following points:

1. Specific—The level of specificity associated with each action often determines your ability to execute. We discussed this in depth earlier in this chapter.
2. Resources—The level of resources, both human and budget, is important to understand to determine if the strategy is actionable. Does your strategy require a skillset to develop a model that does not exist internally? Does the strategy involve increasing your salesforce in order to execute? Think big when you are developing your strategy, but make sure the resources are available to make it actionable.
3. Senior Management Buy-In—Attaining consensus from senior leadership about the monetization strategy and the actions it recommends can make or break the strategy. If leadership has bought into the idea, they can provide resources from various parts of the organization to assist in making the strategy successful. If they have not bought in, they can be significant roadblocks. We recommend having a stakeholder group of senior leaders who walk the journey with you to obtain buy-in as you go.
4. Complexity—The level of complexity to execute both within your organization and outside will be a big factor to consider. If your strategy requires a lot of hoops to jump through—for example, regulatory change—it may be overly complex and not a great candidate.
5. Holistic—The action needs to fit into the broader organization structure. We discussed this in depth in the prior section.
6. Organizational Energy—Regardless of the size of your company, organizational energy is key. It is particularly true if you are a small company. Taking on too many initiatives and priorities can often lead to getting nothing accomplished. Be sure that the monetization strategy fits within the energy level of the organization. The good strategy that is easy to implement is better than the best strategy in the world that is never implemented.
7. Business Lever—The action needs to be tied to a business lever and business objective. This will ensure organizational support and that the company will get behind the action. We discuss this many times as it is worth repeating.

Decision Matrix

Displaying the actions available to a manager is best deployed through a Decision Matrix. As you will learn in the Decision Theory chapter (Chapter 8), a Decision Matrix reflects the outcome and values of various decision scenarios in a grid format.

The matrix is useful for looking at a large quantity of decision factors and assessing each factor's relative significance. It allows the manager the ability to quickly analyze the relationship between the decision factors in order to come up with the optimal decision. The values within the matrix can be numerical or descriptive in nature.

The four building blocks of a decision matrix are: acts, events, outcomes, and payoffs. Acts are the actions or decisions that a person may take. Events are the occurrences taking place, usually with some level of uncertainty. Outcomes are the results of the occurrences, and payoffs are the values the decision maker is placing on the occurrences.

In Table 6.1, we see a Decision Matrix for a Customer Acquisition Monetization Strategy. The acts in this scenario are the channels we want to spend our marketing dollar on. In this example, we have $100,000 to spend on one channel. The events are the Click-through (CTR) and Conversion rates. The outcome is the Sales Volume. Finally, the payoffs are the Revenue and ROI metrics.

Decision matrixes are our preferred structure for displaying monetization strategies, but there are several cases where we leverage graphical techniques to depict similar messages.

Grounded in Data Science

Along with confidence in the quality of the data, trusting in the method used to calculate the expected results of the monetization strategy is important. If the consumer of the strategy feels like the results are not achievable or accurate, they are not likely to take action to achieve them. However, if you ground your strategy in data science that the manager trusts, you are likely to get buy-in for the prescribed actions.

For example, you are putting together a monetization strategy for attachment products purchased at a convenience drugstore. These are companion products that people purchase with an anchor product, like cereal and milk. Your task is to help your marketing department and merchandizing teams understand which products are most likely to be companion products for major purchases. Your goal is to provide a lift by solving for correct pricing of these products, placement in stores, and how they are advertised. Your initial analysis does not produce obvious attachments. But with exploratory data visualization, you discover that diapers and Tylenol are two purchases that are often made together and that you can achieve a 5 percent lift in revenue by offering a coupon for the companion purchase. If you went to the various groups with this insight, without additional analysis, you might get strange looks. However, if your data scientist is able to prove, through some basic profiling and market basket analysis, that 20 percent of the time when a consumer purchases diapers they also purchase Tylenol, the marketing manager will probably listen.

Due to the nature of a monetization strategy having a financial value and some type of implied mathematical function to determine a revenue increase or cost saving, data science will often be a part of your solution. This bring us to our next section, applying some monetary or economic value to the action.

Monetary Value

Every monetization strategy will need some type of economic value associated with it, whether a cost savings or revenue increase. The goal of the monetization strategy is to assign a value to an action in order to determine the most optimal decision.

Anchoring back to your Business Levers is a great place to start when trying to depict an economic value for a particular action. We covered this topic in the Monetization Strategy chapter (Chapter 5), but let's do a quick recap. The Business Levers should be aligned to your company's P&L statement and are the levers by which you can drive monetary value to your organization. Examples of business levers to drive revenue include: Price, Volume, Number of Sales Reps, Market Share, Customer Acquisition, and Frequency of Customer Visits. The Business Levers provide you with plenty of fodder to align an action to your strategy.

Our primary recommendation for showing an economic value that provides a tradeoff in decisions is a dollar amount, a value showing revenue increase, profit increase, or cost saving. These are tangible numbers by which the manager can make a direct impact on the organization and clearly understand the tradeoff between actions.

Another way to depict an economic value is through a metric like Return on Investment (ROI). While this metric can provide guidance, we still suggest showing an actual dollar amount as well. An ROI of 200 percent that returns $1 million to the company is not the same as an ROI of 25 percent that returns $100 million to the company. Depending on what is important to the business objectives, either option could be correct.

Let's take a hypothetical example involving a productivity saving strategy through optimization that translates to revenue. In this case we are a trucking company looking to optimize our maintenance schedules for a fleet of trucks. By determining when a truck should be scheduled for general maintenance and proactively looking for maintenance issues that occur in trucks with similar mileage, haul loads, and repair histories, we are able to conclude the optimal schedules for repairs and maintenance.

This analysis can generate millions in revenue by delaying unnecessary maintenance and keeping trucks more productive. It can also save millions in costs by determining when a truck is most likely to need service or a major repair. By getting ahead of any maintenance issues, we can reduce costly outages and extensive repairs. Table 6.2 is an example of this analysis in a decision matrix.

If you are the fleet manager managing thousands of vehicles, this level of specificity can assist in driving actions to select which vehicles to schedule for maintenance. Based on the Optimal Schedule Service for mileage and Projected Productivity Savings, you conclude that truck numbers 35–2287 and 35–9001 should be scheduled for early service. If you multiply this analysis across thousands of vehicles in productivity savings, the numbers add up quickly.

We could have stopped our analysis and not included the Projected Productivity Savings metric, but the monetary value associated with the decision helps us determine priority as well as urgency. Monetary value may be one of the most important aspects of your monetization strategy. Put the time and energy to solving for the economic value you apply to each action and your analytical solution will have a bigger impact on the organization and drive managers to better decisions.

Confidence Factor

As we will discuss in the Decision Theory chapter (Chapter 8), a confidence factor or probability can help navigate an executive to the action with the highest likelihood to achieve the desired results. There are several ways to depict opportunity; a probability score or descriptive measure are the two most prominent methods.

A probability score is an assigned numerical value attributed to an outcome, such as 95 percent. A descriptive measure may be the use of High, Medium, Low, or it could be a relative score of 1 to 5 where 1 is difficult to achieve and 5 is easiest to achieve.

Let's look at examples of both. In Table 6.3, we have a Propensity to Purchase score that has been calculated as a confidence factor of a particular consumer's ability to purchase a product from our company.

The second method we recommend is a descriptive measure or relative score. These are typically associated with higher level monetization strategies versus specific targeted customers. In Table 6.4, we see the Ability to Achieve as a relative score that can be applied where 5 is the easiest to achieve and 1 is the hardest.

Calculation of the Probability score depends on a number of factors. We recommend working with your data science team to come up with the best method that is most likely to be adopted and accepted by your organization.

Measurable

To know whether your actions are working, you need the ability to measure them. This is one of the hardest guiding principles to achieve. It is based largely on the level of automation an organization is able to achieve and the channels in which your organizations sells through. If these actions are mostly through offline channels, they are considerably harder to measure than online channels.

With offline channels like advertising, connecting an action to an outcome can be difficult. If one of your channels is billboard advertising where an inferred response is needed, it is difficult to measure. If the action has a promotion code associated with it that is captured at the time of sale, we can make a direct link back to the action to measure the results. Depending on your organization, the action type, and the various selling channels, you may or may not be able to measure a particular action.

If the channel is online or fully automated, measurement gets considerably easier. If the campaign involves a banner ad placement on a website, we can measure impressions and click-throughs. If the action is associated with a recorded event, for example, a truck stopped for service within a particular mileage window, the service systems should be able to provide us with this information. If the action is to see if our churn rate decreases, we can measure this through the number of customers that canceled service over a period of time. The better the automation, the easier it is to measure the outcome.

We suggest you determine up front how you plan to measure your actions when considering your monetization strategy. Measurement of actions impacts the metrics you put in your decision matrix along with the level of specificity you apply to the actions.

Motivation

Motivating individuals to align their actions with your strategy may be necessary depending on the type of monetization strategy you deploy. People have busy agendas and often have too much work to do already. Taking on yet another task is not something most people do lightly unless there is some incentive.

For example, one of your actions is to deploy a sell-in strategy for additional space inside of a retail outlet. Your strategy will compete with the selling of major product lines that produce the bulk of the salesperson's salary along with other sales initiatives from other departments. The field sales team is not likely to jump at the chance at selling in your strategy if they don't see value in the effort. You will need to get senior management support and most likely a financial incentive for the sales reps to execute on your plan.

Here are three ideas on incentives to create an environment for a higher execution rate:

1. Corporate Initiative—Align your strategy to a major corporate initiative to give it energy as other groups will also be working on projects to implement this initiative. Your work efforts may help them progress their efforts, creating a winning scenario for both teams.
2. Performance Management—Another effective approach is getting the work effort associated with the strategy included as a key goal for the individual's performance review. This ensures that the person will get credit for their participation.
3. Financial Rewards—Providing a financial incentive is a powerful motivator. If someone is rewarded financially for their participation or execution of an action, they are more likely to act.

Depending on your monetization strategy and organization, adding an incentive to the strategy can drastically increase the probability that the actions are executed upon.

Organizational Culture

According to Robert E. Quinn and Kim S. Cameron in their book, Diagnosing and Changing Organizational Culture: Based on the Competing Values Framework, there are four types of organizational culture:

1. Clan—Consensus and collaboration drives the organizations that fit into this grouping. They are internally focused and flexible. These organizations have cultures that are family-like with a focus on facilitation, mentorship, and team building.
2. Adhocracy—The adhocracy culture is defined by being creative. They are externally focused and flexible in nature. Innovation, entrepreneurial, and visionary are the focus of their leadership style.
3. Market—Competition is the focus of this organizational group. They are hard driving and focus on results. They are externally focused and controlled.
4. Hierarchy—Controlled with a focus on operations best describes hierarchy-oriented cultures. These cultures are internally focused and controlled in nature. Their leadership is focused on monitoring, organizing, and coordinating the various aspects of the company.

Which culture does your company fall into? Knowing how to navigate your organization's culture will help you figure out how to get support for your monetization strategy. If your organization is an adhocracy, then you will have more autonomy to drive a strategy through to the consumer. If you are in a clan organization, building consensus every step of the way will be vital. Leverage these four organizational types as you build your plan to gain the right type of support for your monetization strategy.

Drives Innovation

The last of the Guiding Principles is the ability of the strategy to drive innovation. This is not a necessity as many of our strategies are associated with normal blocking-and-tackling of day-to-day business. However, a good percentage of our energy when building our monetization strategies is centered on driving growth for our organization, often through some type of new product introduction or innovative technique.

There are several avenues to drive innovations, many of which come from within the walls of your company. In their article, “The New Patterns of Innovation,” authors Rashik Parmar, Ian Mackenzie, David Cohn, and David Gann ask the question, “How can we create value for customers using data and analytic tools we own or could have access to?” They write about the coming wave of innovation that will be created through the new data that will be generated with the upcoming technology of the Internet of Things, where machines talk to each other:

Innovation can take many forms. Product innovation can include launching a brand-new product to the marketplace. Other product innovations can include package innovations or bundles of products to sell together. It can also include an understanding of when to innovate as a particular product may have reached its end of life.

The ability to drive innovation is an important component to consider when developing your monetization strategy. It may not be necessary for all the various types of strategies you deploy, but it can help in situations where product or service growth are key goals.

In the next chapter we will cover an example of using the Monetization Strategy framework to solve a hypothetical challenge to reinforce many of the concepts we have discussed.