How well are you using analytics to make market, customer, and product decisions? Businesses tell us they believe in the concept of using analytics to drive these types of decisions, yet, a recent study by Bloomberg Businessweek Research Services among 930 businesses across the globe in various industries, found that only one in four organizations believes its use of business analytics has been “very effective” in helping to make decisions. Even though more than half of the companies in the survey said that they rely heavily on data and metrics when making decisions, many admitted that intuition and business experience still tip the scale when it comes to decision-making.
Even though it’s been a number of years since Tom Davenport, Don Cohen, and Al Jacobson shared the results of their work in the area of using analytics to create a competitive advantage, marketing professionals remain challenged in regards to analytics. We often encounter questions from marketers that boil down to three topics: What is meant by analytics, what do we need to be successful with analytics, and how can Marketing use analytics?
The accepted common definition for analytics is applying advanced algorithms and/or mathematical techniques on large volumes of data. Businesses use the insights derived from analytics to optimize internal processes and reduce the amount of time required to solve problems and make decisions. While analytics may not fully replace experience and knowledge, they certainly provide insights and color that should be considered. The answer to the first question provides the answer to the third question. Marketers use analytics to translate data into actionable insights to help drive marketing and customer strategies and optimize marketing efforts.
Three key ingredients are needed to be successful with analytics: data, skills, and culture.
Skills. There’s no shortage of data. It’s the ability to turn the data into actionable insight that requires skill. Our research and other studies find that many organizations lack analytical talent. In May, a McKinsey study forecasted that in 2018, the United States could face a shortage of 140,000 to 190,000 people with deep analytical skills. Without the right people, it won’t matter how much you invest in analytical tools. There’s no time like now to invest in developing and growing this talent.
Culture: Organizations that emphasize fact-based decisions, measurability, and process reflect a culture that is more predisposed to analytics and the associated investments needed to build and leverage this competency. These organizations take a holistic approach to data and view data as a strategic asset and the “backbone of effective” decision making.
Data: Before you can effectively use analytics, you must be able to manage your data. Data is the fundamental ingredient to performing analytics. Unfortunately, data management is often biggest challenge for most companies when it comes to the adoption and usage of analytics. As result of many factors, including the sheer volume of data, many organizations struggle with data accuracy, integrity, and consistency. And the data needed is often housed in disparate systems.
To be useful, data must be accessible and integrated. Getting your analytics game on takes getting your data house in order. Two steps any company can do to move their data management and analytics efforts forward is to inventory the disparate data and to address data gaps. These two steps entail creating a data source inventory and dictionary.
Data Source Inventory and Dictionary
A good place to start for managing your data is to create a data source inventory. At a minimum you want your data source inventory to list the following:
Don’t be surprised if you find there are inconsistencies in your data. This is common and one of the valuable outputs from the inventory. Once you inventory your data, you will be able to determine what kinds of gaps exist and what data from which source you will need to perform the analytics. Once you complete the data source inventory you can use it as the basis for your data dictionary. The dictionary defines and describes your data, includes titles, captions, and how the data is displayed. It also includes a description of the attributes for each of the columns and tables associated with the data.
While data management is fundamental to analytics, without a CMO who advocates analytics and fact based decision making, who goes “to the mat” to secure the necessary resources (talent, tools, etc.), integrates the science side of marketing into their organization, and holds their marketing organization accountable, the organization will not be able to realize the full potential of using analytics to gain a competitive advantage. Don’t get left in the dust, get your analytics game on!