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Data and Analytics: The Gold Standard Report

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90% of the world’s data has been created in the last two years alone. Think about that, and realize that the volume of data produced will continue growing, exponentially, into the future. The amount of data available to help organizations understand their customers is immense. Yet, it is only of value if they can capture, organize, analyze, and utilize it to improve customer outcomes, increase revenue and profitability, and retain market share in the face of disruptive new competitors.

Program Maturity Leads to Improved Outcomes

In ISM’s experience, there is a strong linkage between the maturity of your data & analytics program and your organization’s ability to accomplish your business goals. As your organization’s data and analytics program matures, you will begin to see better outcomes for your company. You will progress from a state of data chaos, to being able to trust in your data and have a holistic view of your customer, eventually, gaining actionable insights that you can use to improve customer outcomes and compete in a dynamic marketplace.

Data Analytics Value Model

We recommend a Data and Analytics Maturity Model that is based on an enterprise evaluation and scoring of an organization’s proficiency related to people, process, technology, enterprise data, and analytics. This model has been developed by ISM partner, Sodalia.

 Data and Analytics Maturity Model

Data & Analytics programs typically begin in an initial state (Level 1), where online and offline customer information, transactional data, and third party data are poorly integrated and not well maintained, often existing in functional siloes or separate, incompatible systems. In this initial state, there are few processes that support the use of data, little training for employees on improving customer outcomes through data, and no reliable or actionable insights. Generally, progress starts when an organization begins to centralize and integrate their data and focus on cleansing that data to make it current and accurate (Level 2). Some companies at this level will also have begun developing and implementing processes related to data and will have started training employees on the use of data. However, this is table stakes today. Until a company reaches Levels 3 and 4, it will be very difficult to compete in today’s dynamic and disruptive business environment. And only companies that have achieved Level 5 will become disrupters themselves.

The Gold Standard

Working with more than 400 clients from a variety of industries, we have found that fully mature and successful data & analytics programs share the following characteristics:

      1. Customer information is well organized and easily accessible.
      2. There is a single version of the truth regarding customer information, which gives people confidence in the data.
      3. Analytics provide immediately actionable information.
      4. Analytics insights and predictions are reliable.
      5. Employees understand what is important to customers, are trained to use analytical tools, and routinely use data to improve outcomes.
      6. Systems are integrated, with centralized data storage.
      7. Processes for data use are at the core of the company’s approach to working with customers, and key metrics are used to monitor outcomes.
      8. The company’s governing structure provides key stakeholders with the authority and mechanisms to act on data insights.

People, Process & Technology

We have also found that in order to develop a mature data & analytics program, you have to get the mix of people, process, and technology right. Many organizations focus almost entirely on implementing new technologies, when this is only one element of the challenge. Perhaps that is why 85% of data and analytics initiatives still fail.

How to Build a Mature Data & Analytics Program

How do you develop a data and analytics program that matches the gold standard for your industry? Here are four recommended steps:

      1. Build a Solid Data Management Foundation

In order to have a mature data and analytics program with data your employees can trust, you need a strong foundation of data management practices. Two of the most important aspects are integration between data sources, and data quality in terms of completeness, accuracy, reliability, and accessibility. Remember, it is not enough to put in technology changes – you have to develop appropriate internal and customer-facing processes, and train users to maintain and contribute to the data. You also need to make sure employees can effectively use the good data you have made the investment to create.

Does your company have a Chief Data Officer who is responsible for your company’s data strategy? If not, consider creating the role. 80% of top companies have already done so.

      1. Create Holistic Customer Profiles

Good data isn’t just about quality, but also how you structure it, and what data you keep. At the core of every successful data & analytics initiative is the creation and implementation of holistic customer profiles, also known as customer master files. Companies use identity resolution tools to compile customer data from online sources such as website visits or social media participation, as well as offline sources such as point-of-sale data or calls into a contact center. These tools next apply identity recognition techniques to map online and offline data to a single individual. The result is a merged, single customer data record.

These merged, single records are then used to generate insights that provide true customer knowledge, leading to greater understanding of customer lifecycles and journey maps, improved lead scoring and routing, and better forecasting and cross selling. Companies are also able to better model customer behaviors for more effective marketing campaigns. Simply put, enhanced customer knowledge, allows you to deepen customer engagement and build loyalty.

      1. Employ Sophisticated Analytics

Once you have a solid data management foundation and a holistic structure for your data, you can progress to sophisticated analytics generating quality actionable insights. Today’s technology presents an incredible array of techniques and approaches that include:

          • Customer Segmentation
          • Propensity Modeling
          • Predictive Analytics
          • Prescriptive Analytics
          • Machine Learning
          • Artificial Intelligence

Not all may be appropriate for your business, and the complexity, cost, and level of change required by some can present obstacles, but ISM can help. Some of the outcomes we have seen for clients are improvements in customer engagement and loyalty, upticks in revenue, and better customer knowledge leading to changes in business strategy and competitive advantage.

      1. Look at the Entire Lifecycle

Fundamental to marketing these days is the practice of delivering the right content through the right channel at the right time to customers at all stages of the buying journey – including after the sale. It is important to consider the entire customer lifecycle, and looking at the customer holistically with an eye toward the customer’s lifetime value is one of the hallmarks of an advanced business analytics program. You always want to acquire new and more profitable customers, but you also want to identify when existing customers are at risk for churn, ready for up-selling or cross-selling, or appropriate for engagement campaigns to increase loyalty and advocacy.

Roadmap Required

The steps above are the building blocks of a mature data & analytics program. Over the past 34 years, ISM has found that successfully developing such a program starts with a high-level strategy tied to the company’s business direction. Then, build a multi-step roadmap addressing people, process and technology that clearly identifies key milestones, and ties into to the company’s strategy and operations. Finally, commit appropriate resources across the organization to ensure effective implementation at each stage. Having good partners to guide you through every step of this process is extremely beneficial. When properly deployed, we know from experience that our clients’ data and analytics programs can achieve sustainable user adoption and produce a significant return on investment.

The massive availability of data and advanced analytics enable companies to become more agile and realize new growth opportunities through innovation that lead to intelligent market disruptions. ISM would like to be your guide to these new opportunities. We invite you to click below to review this report in relation to your self-assessment results with one of our consultants.