Modern companies operate in a highly connected world with disruptive trends and technologies. The rise of MOBILEhttp://cdncache1-a.akamaihd.net/items/it/img/arrow-10x10.png, lean startups and social networks puts consumers in control while forcing organizations to be more human-like, more sustainable and more open.

To survive in this new era, we must be able to have meaningful one-to-one conversations with our customers. It might be easier when you are a small startup with just a handful of customers, but can be a nightmare if you work for a large multi-national corporation. The only way to achieve this is by having a comprehensive Data Strategy – a plan for distilling data into insight on an unprecedented scale and in an environment that facilitates learning and customer-focus.

We present a 7-step plan to build a Data Strategy for your organization.

1.  Identify key business problems to solve with data and analytics.

 

-Provide a specific list of issues and try to avoid building a capacity for future needs.

-Find out what the top-management want. Look into the Business Strategy for ideas and critical pains.

 

2.  Think about people before you think about technology and data.

-Secure full support from top executives and find an internal sponsor for your project. Make sure he has enough authority to help you in turbulent times of change.

-First WHO, then WHAT. Make sure you have got the right team on the job. Recruit internal talent and look for external consultants.

-Identify potential troublemakers – people reluctant to change or people that have built their entire careers around data they hold (I call such people Data Dragons – they sit on data like a dragon on a pile of GOLDhttp://cdncache1-a.akamaihd.net/items/it/img/arrow-10x10.png).

 

3.  Define core policies

-Think about governance, data ownership and areas of responsibility.

-Provide data access for analysts, developers and scientists. Will you use a liberal data-access approach or provide access only to a handful of individuals.

-Take care about data security and privacy. Wrestling with PCI and PII compliance can be a real nightmare if not done beforehand.

4.  Design a high-level architecture.

-Keep in mind your goals and resource limitations.

-Analyze multiple options, but do not get into too much detail.

-Look for best practice, but do not be afraid to experiment.

-Identify and document data generating business processes.

-Analyze existing data sources.

-If needed, plan for a central Data Platform/Warehouse.

-Create a framework for Business Intelligence.

-Manage expectations.

-THINK ABOUT YOUR PEOPLE! They are your most valuable asset.

5.  Design information feedback loops.

-Implement Test & Learn practices.

-Make sure you provide actionable insights. Always write a So-What section in your report to propose an implementation plan.

6.  Plan for future expansion.

-Try to anticipate future needs and leave room for scalability.

-If possible, design a long-term roadmap aligned with organizational goals.

7.  Decide on an implementation strategy.

-Choose a methodology that works well in your organization.

-Decide between Waterfall and Agile approaches.

-Centralized Data Warehouse vs Distributed Data Federation.

Source: www.marketingdistillery.com