Developing and implementing a data strategy can lead to data stores representing a 360-degree view of members, customers and subscribers across the organization. The data collected, managed and mined as specified in a data strategy and plan can enable real time descriptive, predictive and prescriptive intelligence using rules, models and algorithms that create an opportunity to use data driven management decision-making. Using your gut feeling to make decisions based on a few customer discussions is sometimes great but it can be fraught with risk. Why not back up that gut feeling with data driven proof?
A data strategy and plan reflective of an organization’s strategic goals, focus and products defines what data elements and types are to be collected and managed about customers, members and subscribers. The strategy sets goals for collection and denotes what possible questions can be asked of the data.
A data strategy and plan offers benefits beyond data driven decision-making and providing insights and intelligence.
The consistency of collection, management, reporting and use across all staff assists in educating staff about who the customer, member or subscriber is, what customers, members and subscribers want, how they interact across the organization departments and channels and how an organization can meet their expectations. The knowledge can improve staff performance resulting in increased revenue and high customer satisfaction. Of course, increased revenue and satisfaction are tightly connected.
In person and via this blog I have often talked about the Age of the Customer and the urgency faced by organizations to establish customer focused programs to meet expectations and remain competitive in a dynamically changing marketplace. Organizations need to know more and better understand who their customers, members and subscribers are and how to target services, products and information to meet their expectations. Your customers, members and subscribers also have a lot to tell you and can shed light on the impact and direction of your organization.
An organization that is actively listening and engaging their customers/members is collecting and capturing deep and insightful details about their customer interactions, customer use, customer profiles and can combine the data with externally available data that deepens knowledge, matches customer data to industry trends and aids in creating and defining and describing the personas of current and prospective customers.
Critical Elements of Your Data Strategy and Plan
The now available volumes of information create a challenge in understanding how and what data should be joined, how different pieces of data aid in creating insight and what tools, technologies and human resources are needed to extract insights from the data.
Organizations must know what questions are to be asked of the data. Data as data does not result in insights. Data can tell an organization many different things depending on the view (human or technological) but the organization needs to place the data in context of the business, the goals, KPIs and in other views that directly speak to the business.
The quality of data can be a significant limitation. Technological collection and storage systems aren’t perfect. Humans who enter customer and other data into a system are not perfect. Therefore, all organizations need to accept that there will be errors (bad data) in the system and plan accordingly.
The Simple List
- Data elements and types to be collected that reflect a 360 degree view.
- Internal and external data sources.
- Data mapping of internal and external data elements and types.
- Tools, technologies and platforms.
- The questions to ask of the data.
- Models, rules, and algorithms that provide “answers”.
- Staff and Contractor Responsibilities/needs and of course an implementation plan.
What You Need to Consider?
Organizations who want to move into data driven decision-making and create a Data Strategy and Plan should consider the following requirements and costs:
- Technology based systems and tools that collect, store and provide views into the data. The costs of the systems can range from fairly inexpensive considering cloud based or open source solutions like Hadoop and are predicated on the size of the organization and the amount of data available to collect and manage.
- Report writing, query generation or other software that creates views into the variety of data sources. Depending on the size and types of available data, along with logic needed to join data elements, costs will vary from inexpensive to very expensive.
- Human Resources, preferably a team of data scientists or those that know how to manage and provide reports to the organization.
- Reports, templates and approaches that allow for appropriate communication and relevance of reports and findings. (Executive views as an example).
The training and skills of staff are critically important to experiencing the benefits and results. Staff (or contractors) must receive training on the tools and technologies used to gain access to the data and derive reports and insights. Additionally, staff should be trained in developing and applying various statistical, mathematical and other models that can be applied to the available data.
An organization’s management must on an ongoing basis develop the questions they need answered. What problems currently exist or are perceived. Perhaps descriptive analytics demonstrates product sales aren’t hitting targets, churn is higher than expected or a new product is being developed for an unfamiliar market. Frame questions to gain the answers needed.
Don’t keep guessing and don’t always trust your gut. You have great opportunities using data and along with solid data strategies and plans create insights, intelligence and evidence to make your organization soar and stay relevant in a dynamically changing market. Contact us, we can help.