Every business, regardless of its size, is continuously generating data. Sales receipts, invoices, time cards, status reports are just some examples of data that a business generates during the normal course of its operation. This data can be used in many ways – to find and remove inefficiencies in the business, to increase sales, improve customer retention etc. For example, a restaurant chef can improve his food purchasing decisions by looking at data for what dishes were popular at the restaurant over the last few months. A used car dealership can get better ROIs by looking at the correlation between the sales price, time to sell, and cost of refurbishing the used cars before selling them.
To use its data effectively, a business must have a plan or strategy on how to do so. This articles discusses WHAT is a Data Strategy, WHY businesses should have one, and HOW to create a Data Strategy.
WHAT is a Data Strategy
Simply put, a data strategy is a plan created by key players in a business to leverage data that the business is generating daily and use it to improve, grow, and sustain the business. Data strategy should evolve alongside the business.
An important thing to note: Data strategy is not Data Management. Data Strategy is about what to do with the business’s data and why. Data management deals with how to execute the Data Strategy.
WHY businesses should have a Data Strategy
When it comes to data strategy, businesses fall into 1 of 2 categories:
1. Business strategy drives Data strategy
Business owners are constantly strategizing on how to beat the competition – product offerings & promos, service differentiation, marketing & social media etc. These business strategies should use the data the business already has, to form a plan of attack. The success of a business strategy should also be measured and data about the outcome of the strategy should be used for future decision making. For example, restaurant that wants to cut food waste can look at what customers are ordering (including weekly and seasonal trends) to scale back on expensive,perishable ingredients that are rarely used.
2. Data strategy drives business strategy
Of late,with Big Data and AI being mentioned in the mainstream press very often, companies are realizing they have an enormous amount of data and they *should* be extracting value from it. In this case, data strategy comes first – the business can examine all the data they have and see which parts of it can help improve the business.
HOW to create a data strategy
The following are basic steps to create a data strategy:
1. Identify your stakeholders. Ideally, one representative from each area of the business should be chosen. Buy in from the top decision makers is key.
2. Define clear goals: Whether your data is driving business strategy or vice versa, define the goals to be achieved. Data strategy should not be an exploratory activity. The goals must be concrete and measurable.
3. Ensure data integrity: Examine the data you have. Is it clean and error-free or do you have too much invalid data? Its important to remember that more data is not always better.
4. Consolidation: Identify the data silos across your business and make a list of the ones that need to be combined. Platforms such as data.world are great collaboration tools for this purpose.
5. Legal and compliance: Consider the legal implications of using and combining your data. Questions to ask: Can we use this data without violating our customer’s privacy ? Do we have any personally identifiable information (PII) which needs to be encrypted ? How long can we keep this data? How are we securing customer data?
6. Lastly, apply the Build-Measure-Learn process made famous by the Lean Startup movement to your data strategy:
Build: Create your Data Strategy and execute it
Measure: Examine how well the data strategy worked and what failed
Learn: Use data from the Measure step to improve.