Market Planning: A New Data Science Approach for 2020 and Beyond

When conducting an evaluation of markets, competitors, trends and opportunities, strategic business planners have relied heavily on a set of long-established financial measures like “top down” market sizing and trend analysis as a basic component in their market models.

This briefing will make the case that traditional analytical methods and tools are missing a level of depth that is critical to understanding today’s complex buyer and competitive environments in a meaningful and actionable way.

By the end of this briefing, readers will have a clear understanding, that intelligence on companies and their information technology buying activities is now available at a quality, level of depth and scale to correctly model the opportunities that exist within companies globally. It will be established that this missing intelligence must be included in all future planning models if a more accurate and consistent representation of the size and characteristics of the markets under review is to be achieved.

Typical accepted sources of input into market planning have remained largely unchanged over the last three decades. To date, planning input factors have relied heavily on reported vendor sales to perform market sizing and market share analysis. More recently this data has been supplemented with vendor and customer interviews to improve accuracy and provide a more balanced perspective of a market.4

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Analysts have long used market sizing and market share analysis to balance the potential biases in internal sales data. Introducing an external market perspective, while also benchmarking external competitors, provides a representative market model that seeks to illustrate a vendor’s performance against its addressable market opportunity.

This depth of market model has long given decision-makers what was believed to be a sufficient level of detail to analyze their markets. In today’s complex and more congested market environment it is a lot more challenging.

Decision-makers should be asking market planners how the information technology choices and infrastructures of companies that make up their markets under review have been captured and brought into their market models to better support decision making.

In determining market opportunity, decisions must factor in market addressability by considering:

• The complexity of a company’s technology infrastructure, including the physical installation and distribution of products on premises and in the cloud
• Whether or not the technology products are compatible with each other, rely on other products or could be replaced by a consolidated solution
• An organization’s plans for major IT transformation activities such as moving services to the cloud or moving toward more digital processes
• Organizational structures and their impact on the buyer’s decisions
• The influence that indirect routes to market across ISVs, MSPs, VADs, VARs have on supply that can obstruct an accurate view of endpoint customer markets

While internal sales data and market share analysis still provide a method for measuring relative opportunity size and shape at a certain level, they are inadequate in today’s complex markets.

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Without a thorough consideration of the target companies and their IT infrastructures—also known as market constituents—the traditional approaches fail to provide the granular insights needed to produce detailed analysis that includes data on addressability to support more reliable and effective decision making.

Additionally, without this missing information, a gap will quickly become evident as plans are operationalized and departments are staffed and resourced based on decisions made from data that is too limited and often too high level. This frustrates alignment in the organization. With strategy, budgets, and resourcing all emanating from the decision based on traditional market planning, this gap often remains unplugged or is actually found to be in conflict with the market requirements for the planned opportunity to be realized.This culminates in inefficiencies, increased costs, and ultimately unmet performance goals.

Constituent Analysis- An Introduction

To understand a market beyond its macro factors, business planners need to expand the data under review to include detailed analysis of the companies (the constituents) that make up the market under review and their respective infrastructures. These companies are the endpoint customers and prospects that make up the opportunity and market being analyzed.

The inclusion of constituent companies in market modeling can be defined as constituent analysis.

Constituent analysis provides many benefits through a granular review of the companies that make up the markets under observation. Top down planning supported by small scale customer surveying misses this detail. This creates an abstracted helicopter view of a market, missing the company level detail that it is now critical to understanding and thriving in current and future markets.

Constituent Analysis Now Possible through Advanced Data Science

The barriers to meaningful constituent analysis have historically been:

1. The availability of an accurate global scale technology intelligence dataset to represent the technology being used at a specific company and location.
2. A valid and current index of companies informed by their group structures correctly attributed with industry, employee size, annual revenue, and other firmographic markers.
3. Relevant and proportional coverage of constituents within each market structure to allow for a balanced and unbiased view of a market to be achieved.

Advanced data science and technology have enabled companies to eliminate these barriers and can now deliver constituent analysis at scale. For example, by analyzing billions of documents programmatically, we have accurately profiled the infrastructures of over 700,000 companies without bias and placed them each correctly within a market structure.

With the barriers to constituent analysis removed, strategic planners now have the granular insights they need to make much more strategic and effective business decisions.

Benefits of Constituent Analysis

Constituent analysis gives planners access to detailed technology intelligence on the companies that matter in their markets. This includes information on what technologies these companies have installed, what product decisions they have made, and how much they spend in different categories of IT.

In addition, all this information can be aggregated by market for analysis. Since this data represents actual purchase decisions rather than high-level observations from a survey, planners can accurately segment this fact-based data to provide a much richer and more detailed view of their markets.

This approach provides complementary triangulation points into traditional analysis, while also providing a line of sight from aggregated market overviews down to the actual companies representing those markets. This helps execution, simplifying the route from decision to execution while also removing the traditional end customer blind spot created by distribution and other channel routes to market.

Flexible Market Definitions

With constituent analysis, markets are defined by selecting and aggregating companies based on many parameters, enabling planners to now create flexible market definitions to better align to their company’s solution and ICP (Ideal Customer Profile) requirements. This frees market definitions from the limitations of traditional segments, such as location, size, industry and other generic markers.

Analyze Markets as a Whole or in Detail

Consider the example of the French market.

With constituent analysis, you can now conduct an analysis including all constituent companies in France as a whole or further refine the market definition by examining only large international companies within France.

You can also choose to be more specific, analyzing only the largest spenders in the storage market or including only the companies that have Vendor X and Product Y deployed. Such flexibility allows for detailed market modeling while also providing planners with the ability to aggregate and extract results in more traditional segments if required by their existing systems or stakeholders.

This flexible approach is critical in today’s markets that require more granular definition.

For example, consider the difference between sizing and shaping the market for the ERP category versus sizing and shaping the market for companies who have installed the product SAP R/3.If SAP R/3 site installs are a dependency for your market, this distinction is transformative, providing insights to influence how you plan and execute.

New Data Points for Better Analysis

Constituent analysis introduces new data points that allow strategic planners to now view market shares and structures as penetration rates in the context of company counts.This leverages the IT infrastructure profiles of constituent companies to provide an indicator of whether a company uses, has used or buys specific technology products or services.

These data points allow for a comprehensive view of the shape and size of a market as well as to its degree of penetration bringing the customer into the heart of the analysis.

For instance, continuing with our French example, planners cannot only see that the French market is a specific size in a chosen currency, they can also see that this market is made up of X companies of a given size and industry, Y% of which consume a pre-defined set of products or use a competitor and Z% represent white space opportunities, all dynamically segmented to suit the planner.

Market penetration can be used in this case to inform how and if a market can be addressed and its real density.

Analyzing End Point Markets is Finally Possible

Analysis of end point customers has long been difficult. The complexity of supply routes with distribution channels, GSIs, and ISVs has made it difficult to know who is really buying the vendor solution, keeping best available market analysis at the macro level. Constituent analysis allows for end point customer infrastructures to be analyzed and rolled up to a market level thus providing a more accurate and detailed view of the true buyer.

Powerful market insights incorporating buyer level detail then become available:

• Co-residence of technologies
• Dominant vendors and products by infrastructure area
• Emerging vendors and products supporting partner identification
• Infrastructure maturity and change over time
• Infrastructure aging and obsolescence
• Vendor product density

Timely and More Accurate Data for Better Decisions

Granular data views save time and costs as well as provide more robust and transparent intelligence that can then be included within traditional models.

Traditionally, market models have taken significant time and resources to research and build.

With detailed constituency level data, planners can dramatically reduce the time it takes to build their models because this data helps simplify and test model assumptions, provides new insights to increase accuracy, and supports traditional segmentation that allows planners to easily deliver this incremental analysis into existing processes.

Data driven insights at the company level allow for timely dynamic updates into market models. No longer is it a requirement to wait for an entire market’s data to be refreshed before it can be used.

Monthly data updates allow for changing customer and competitor behaviors or market events to be quickly captured, analyzed and integrated into planning or operations.

A line of sight through the data – from decision to execution – enables alignment across the organization.

The time from decision to action compresses. As all data is mapped at a company level, drilling from market aggregation to a territory or region then down to a company is simple. Questions can now be asked using verifiable constituent analysis with clear and traceable outcomes.

Data versatility allows planners to see markets by size, shape and market share percentage. This can now be done:

• Globally
• Regionally
• By Country
• By Industry
• Through peer comparisons
• Using territory level aggregations
• Through aggregation based on:
  • Installed technologies
  • IT spend levels in different categories
  • Multiple criteria

By being able to analyze client infrastructures, planners can finally see the detail of markets. Example detail includes:

• What are the company dynamics of each market?
• How big are the markets? How many companies are there by industry, size and location?
• Are companies international or domestic, group or single entity?
• How many decision HQs are there in each market?
• How penetrated is each market?
• Who are the dominant vendors?
• What is the spending profile of the market?
• What technologies are each company using within their infrastructure?
• Which competing vendors are present and what is there share of customer penetration and wallet?
• What changes in technology are being seen in the companies?
• How much whitespace is in the market?
• Which service providers are present?

Recommendation

Decisions supported by fact-based data have been proven to accelerate performance. No more is this true than in times of change. Reacting to change in a timely way is critical to every organization.

Change is also accelerating the transformation of the information and communications technology infrastructures of companies.

It is imperative for planners to extend or validate their existing strategic and operational models through incorporation of constituency data into their working models today.

Granular detail on a market’s constituent companies will allow planners to get an enriched and more detailed view of their markets to reinforce or reshape current and pending decisions.