Everything is different now. It follows that you need to update your business strategy and therefore your supporting data strategy, but how do you actually do it? How do you know where to begin when faced with an unpredictable economy, changing priorities and requirements, and nearly infinite technology choices?It starts by taking a step back and taking a fresh look at your business. Not just the data; but the people, processes, and technology that drive your business decisions—all of which encompasses a data strategy.A Data Strategy Guides the Entire Organization to Make Smarter Decisions A data strategy is not only relevant to executives. Every decision maker benefits from the analytics that result from a data strategy. In order to maximize the benefit to your company, start by putting together a small data strategy team with representatives from your executive suite, directors and managers, and individual contributors.Executives In charge of making business-wide decisions that will make or break the company, you demand a lot from your data and analytics. Your role in a data strategy effort should be to make sure that the efforts are supporting your most important business initiatives. Don’t delegate your voice in defining the goals of a data strategy.Especially in a time of crisis or uncertainty, you should be sure to consider your data needs to support your operational decisions (crisis mitigation, capital preservation, efficiency, etc.) and to support innovation (how will we know if a new business idea is having the result we need?)Thinking about operational and innovation activities separately can help focus and prioritize your data needs. You’ll need analytics to support both, but different stakeholders may be involved.As an executive, you also have an excellent perspective into where and how the work of individual departments intersects to achieve results. Make sure those connections are reflected in your company’s data by playing an active role in refreshing your data strategy.Directors and Managers A director or manager is often in the lead role for developing or updating your company’s data strategy. If this is you, you have a big responsibility. Make sure the data strategy team is on task and hearing from the appropriate stakeholders.If you are a business stakeholder, your role is as an advocate for your department or team. Look for common requirements with your peers in other departments—those needs that cross departmental lines are likely to result in the highest priority projects to flow from a data strategy effort.Data-driven decision-making is built on trust. Do you trust your team to make good decisions independently? Do they trust the data they use to make those decisions? Do they trust that you will be their advocate when it comes to giving them the best tools and data? As a leader of department or of a small team, you set the culture for that team. Use a data strategy effort as a way to build a trusting data-driven culture.Contributors As an individual contributor, you are the one working with customers, suppliers, partners, or other employees to get the business of your company done. Do you have the right data, tools, and training to do make the best decisions on a daily basis?Are you spending a disproportionate amount of time collecting and combining data using individual spreadsheets? Or even worse, does it seem impossible to get the data you need just to make educated guesses?Your role in a data strategy effort is to expose the difficulties you have using data to make decisions. Additionally, if you figured out something on your own (maybe you have an incredible spreadsheet that others could use), make sure that the data strategy team knows about it. Many of the most useful enterprise-wide analytics came from an innovative employee’s personal project.From small “course adjustments” to complete reinvention of a business, your data strategy should empower everyone at every level to use data and analytics to support your business objectives.How to Update Your Data Strategy Once your data strategy team is formed, here are a few practical steps to kick off a refresh of your data strategy.List out your business initiatives and the data needed to support those initiatives. Take note of any new data sources you might need to pull from. For example:We’re launching new direct-to-consumer web store -> We need to analyze the sales data, web traffic, and customer sentiment on social media.We have an updated diversity and inclusion initiative -> We need to improve insights about candidate tracking and employee engagement reporting.We need to better understand our customers -> We should consider doing customer surveys and a customer segmentation projectWe need to reevaluate our supplier relationships -> We should analyze supplier pricing and service level data.Look at your data infrastructure and determine if it will support the kinds of analytics you want to do.Are you on the cloud? If not, consider the potential benefits: new capabilities, opportunities for cost reduction, and performance improvements.Do you have an appropriate relational database at the heart of your analytics capabilities? There are great, cost-effective options for any amount of data you work with. There have been massive improvements in database technology in recent years—make sure you are aware of them.Do you have a good general-purpose Business Intelligence platform? And if so, are your people using it? If they aren’t, it’s likely because it is poorly deployed, not because the tool isn’t capable. You may need a new tool, but before you assume you do, take stock of what you actually have and what your business needs are. Don’t shy away from spending some money here if you truly need to, but don’t just assume that the first thing you need is a shiny new tool.Can you easily incorporate new data sources without straining your infrastructure? If you have the right infrastructure in place (especially if you are deployed in the cloud), you can better handle integrating data from anywhere without capacity issues, long query times, or manual efforts.Can you reliably and consistently move, replicate, and cleanse your data? This starts with an Extract-Transform-Load (ETL) tool. There are many options for this technology—Python is one of our favorites and it’s free.Will data science or machine learning help you make better decisions and innovate your business? Don’t jump in until you identify what business problem or use case you want to solve, and then figure out the data, technology, and infrastructure you need to get there.Take stock of the specific analytics capabilities you already have. Talk to each business department about reports/spreadsheets/visualizations they’re using.What is already working really well?What is widely adopted? What isn’t but should be?Who is getting value from your current analytics? Who is not? Who needs to get value from your analytics?What capabilities do you have in-house to do more? Do you have the skills and the time?Is anyone doing really cool analysis on the side that could be mainstreamed?At this point, it’s time to develop (or update) your prioritization matrix, develop (or update) high-level data models, or update some of your infrastructure. From an organizational perspective, you may decide to develop a long-term analytics program and you may even be ready to embark some of the high-priority projects.Now is the Time to Update Your Data Strategy Circumstances change rapidly, and your ability to remain agile relies on a well-defined and widely adopted data strategy. When we help our clients with their data strategy, we never presume to know the details of what they might need to do next. Rather, the focus is laying the foundation with a strong data infrastructure so that no matter what changes occur, they’re equipped to make informed decisions with the right data.