Data helps you understand and improve business processes so you can reduce wasted money and time. Every company feels the effects of waste. It depletes resources, squanders time, and ultimately impacts the bottom line. That’s why each company should start with strategy, instead of beginning with the data itself. What data you collect, which data your competitors collect, or what new forms of data are available, does not matter at this stage. Nor does if your company is able to provide you with mountains of analytical data, or neither.
"A data strategy is a highly dynamic process employed to support the acquisition, organization, analysis, and delivery of data in support of business objectives.” — Gartner
A good data strategy does not refer to what data is readily or potentially available. Rather, it’s about what you want to achieve, and how data can help you get there.
Main reasons why companies need a data strategy
It is absolutely crucial to have a clear data strategy when considering the volume of data available today. Many companies try to collect Big Data as much as possible, without really considering what they want to do with all of it. This is because of the following:
Definition of key success criteria across the company.
A data strategy defines the company's priorities, including performance standards and support for finance, marketing, as well as stakeholders’ needs and expectations. It also reinforces consistency for how initiatives are measured, evaluated, and tracked across all levels of the company.
Leveraging data while integrating business goals.
Aligning business goals and the value of data for the company is included in data strategies. It ensures the continuity of the data capabilities of various departments, which also reduces redundancy and uncertainty from data. This too decreases operating costs and optimizes efficiency because of the increased data quality and reusability.
Linking business and IT perspectives.
A collective data strategy makes it possible to position the business and IT groups, by understanding their needs, skills, and priorities in leading the company. This allows them to understand how to take a "business-led/technology-enabled" approach not just for internal operations, but also for supplier+partner partnerships.
Understanding customers better
Through data strategy, businesses gain better insights about whether customers do or don’t like their products and/or services, and if there are sufficient efforts to understand these changes. Moreover, expenditures are budgeted accordingly to create efficient implementations. However, if you do not have the correct tools to understand it, it can be easy to get lost in all the data that you have.
Components of data strategy
In order to achieve strategic goals and generate real value, data must address specific business needs. It starts with is identifying who are the leaders and experts that will support and represent specific departments or functions within the company. The next step is to define strategic objectives and to link departmental activities with overall company objectives. For the success of the data strategy, it is crucial to set objectives for data management and use. It will drive and enhance your data management activities, as well as set short and long-term objectives.
Process and Standard Documentation
Proper standard data documentation and policies, such as standard of procedures (SOPs), help processes in data management understandable, consistent, and repeatable. Especially for data collection, storage, sharing, and use. Also, it helps monitor your progress in the implementation of your data strategy, so you can update your plans on an ongoing basis.
Data governance becomes a key process for managing and controlling data, and it is based on the results of the data strategy. Effective data governance helps define the guiding principles, goals, policies, roles, accountabilities, and metrics while ensuring that data is consistent, reliable, and not misused. This is becoming increasingly important as organizations are faced with new privacy rules, and are increasingly relying on data analysis to enhance business decision-making.
A strong data roadmap is designed to help you chart the path from data wrangling to data success. This means that all data-related initiatives should align to the strategy roadmap, the goals/objectives of the data strategy, and how an organization adapts and develops with it. It is important to ensure that the first iterations of implementing the data strategy are attainable, and deliver measurable value before pursuing higher maturity goals. Additionally, your data strategy roadmap will outline how you plan to achieve your short-term and long-term goals, which helps set priorities and emphasize to employees what is important.
Six steps to building a corporate data strategy
1. Get support
The support of executives and others at all levels of your organization is crucial for successful data strategy implementation. You gain support by creating a proposal or a report that would encourage their acceptance and willingness to actively take part in it and provide the resources you need to put in place for the strategy. It will show them also what are its business goals, how it will benefit the organization, and what are its economic logic (the positive returns over cost).
2. Manage the 3Ps around data
The 3Ps refer to People, Process, and Policy. You can start this by organizing a data management team, who will have direct involvement in the implementation of the strategy. Establish a team that understands the value of data, has the right business’ technological and organizational capabilities, and has data governance roles. This will ensure compliance in the data strategy with standards, deploying technologies, providing updates to employees about policy changes, and etc.
3. Identify source & types of data
Determining what data you’ll collect and how you’ll get it will help avoid avoidable factors (i.e. wrong, unreliable, or inaccurate data) that can impede the success of your data strategy. You can narrow down your search by basing it on the business goals of your strategy, then look from different sites (i.e. article groups, social media, and etc.) or buy it from second/third-party data. Also, while the strategy is in progress, this will secure quality information to support future decisions and insights.
4. Create an action plan
Outline a roadmap that will help achieve the short-term and long-term data strategy goals, step by step, and that can leverage and manage data for a strategic advantage. These plans should be specific and include what process and technology to use, how much it will cost, how long it will take, and the intended outcome. It should also be flexible so it can be adjusted if something will not work as expected or when circumstances change.
5. Coordinate & organize the process
It will be crucial to coordinate the steps of your data strategy to related departments, as they help determine how actionable and shareable your data is. Here, you'll also need to consider how data will influence data sharing, ease of access, and its usage for different departments. Different approaches may work best for different companies, but the overall goal is to create an accessible system that can help make the strategy's progress as steady as possible.
6. Earn approval & implement
Once you have set your goals and roadmap, it's ready to be packaged into a business plan and presented to company leadership's approval. The business plan should include other strategies you’ll use to achieve the company’s data goals and the resources you’ll need to implement the strategy (i.e. capital investments, new hires, new processes, or new organizational structures). Once you gain final approval, you're set for your data strategy's implementation and should be adjusted as needed.
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