A recent survey by IDC, commissioned by Alteryx, revealed that nearly 3 in 4 organizations will spend more on analytics software than any other software investments over the next 12 to 18 months.
But only those with a solid analytics strategy will see ROI from their investments.
So, let’s explore what an analytics strategy is, how you can see ROI from your strategy, and how to develop one.
What is an Analytics Strategy?
An analytics strategy is a plan for how you will use data analytics to improve your business outcomes. It includes specifying the data you’ll analyze, your analytics tools, the people who use them, the goals you want to achieve, and the business value you’ll gain from it.
An analytics strategy is different than a data strategy, which is a strategic plan for how to store, govern, and manage the use of data across an organization.
A well-executed analytics strategy can help you achieve better financial, customer, and employee outcomes. For example, an analytics strategy might aim to improve customer retention rates or increase sales.
To develop a sound analytics strategy, you should include these four key principles:
- Delivering insights to action from every type of data and source
- Delivering insights across all use cases
- Democratizing analytic insights for every person at every skill level
- Empowering teams to quickly and easily learn, create, and automate analytics
Why Create an Analytics Strategy?
Source: “4 Ways to Unlock Transformative Business Outcomes from Analytics Investments.” , sponsored by Alteryx August 2022 | Doc. #US49458122
Companies with solid analytics strategies make better decisions and see improved ROI on their investments. They see higher ROI because their analytics capabilities allow them to:
- Surface trends during the early stages of projects
- Discover new and hidden opportunities
- Reduce or remove bias from critical decisions
- Anticipate shifts in demand and the market
- Creating an effective analytics strategy can help you capitalize on new opportunities before competitors. You can also use your strategy to increase your market share and reduce risk.
How Leaders are Adapting Analytics Strategies for 2023
Business leaders are recognizing that they need to raise the level of their analytics maturity to inform decision-makers, solve business needs, and deliver results. And there are four key principles to remember when creating an analytics strategy:
- Using all data sources across an organization
- Democratizing insights so everyone can access information
- Empowering teams to easily learn, create, and automate analytics
- Empowering teams to make their own decisions
To do this, you should incorporate the 4 Proficiencies of Enterprise Analytics Proficiency:
- Comprehensiveness Analytics Capabilities
- Flexibility of Analytics Platforms
- Ubiquity of Analytics
- Usability to Analytics Tools and Processes
Here’s how you can use each of the 4 Proficiencies to optimize your analytics and improve business decisions.
Your analytics strategy should encompass everything within your organization, especially your data assets.
Organizations that use more data sources and types see higher ROI from their analytic investments.
Yet, 63% of organizations don’t use all their available data.1 There are many reasons why companies aren’t taking advantage of all their data, including:
- Limitation of current analytic tools
- Improper data governance
- Lack of access or no access to data needed
- Hidden or dark data
- Inability to use data types
- Inability to incorporate real-time data
- Time required to use and analyze data
- Data silos and security concerns
These roadblocks prevent analysts, data scientists, and leaders from accessing and using the right data for each project. Removing these obstacles translates into more ROI.
Data analysis should be used everywhere in your organization.
High ROI performers have analytics solutions beyond spreadsheets (e.g. interactive dashboards, predictive and prescriptive analytics, machine learning, data science, artificial intelligence, etc.) in an average of four different business domains (compared to one).
However, less than half of the departments that need a solution have an enterprise analytics solution.
The reasons why enterprise analytic solutions aren’t being deployed across multiple domains for decision-making include:
- Current analytic investments not working across multiple business domains
- Lack of awareness of analytic solution availability
- Talent gaps that prevent the use of available solutions
- Little-to-no investments in AI/ML and automation in decision making
Companies need to invest in cross-departmental solutions to increase the use of analytics everywhere. This includes expanding the use of AI, ML, and automation throughout all steps of analytic decisions.
All stakeholders must buy into the solutions, and the solutions must fit teams with various skills and experience. Your solution should empower people who know how to code, have experience with analytical tools and platforms, and people who have little-to-no experience with either.
Ensure that everyone in your organization — from the C-suite to front-line employees — is data literate and empowered to leverage their analytical skills.
Companies see improved financial metrics when more than half of a company’s users understand data outside their immediate group very or extremely well.
However, 9 out of 10 respondents to an IDC survey said that less “than half of their knowledge workers are active users of analytics software” beyond spreadsheets. Additionally, 93% also reported they’re not using the full analytic skill sets of their employees.2 These issues boil down to:
- A lack of exposure to analytic solutions
- Little-to-no opportunities for upskilling
- Analytic investments that don’t support learning
- Barriers to collaboration, sharing, and scaling
You can increase collaboration and data literacy by providing learning opportunities and supporting workers with platforms that encourage growth. Invest in solutions that promote sharing assets so others can leverage them.
Online courses, lessons, and communities can also provide excellent learning opportunities for your company. Where possible, seek areas where your team can automate analytics across the board, including advanced analytics, ML, and AI.
Your analytic solutions need to be easy enough for anyone to use for the entire analytic process, especially the more technical work of advanced analytics, AI, and ML.
77% of high ROI performers report integrating all five steps of the analytics process into one end-to-end platform.
Yet 56% of organizations haven’t done this yet. 3. Why? Reasons include:
- Point solutions that only solve one step of the analytics process
- Lack of analytics integration with current and new data sources
- Lack of integration with reporting platforms
- Little-to-no automation of data preparation processes
- Complicated user interfaces and/or coding required
Logically, the first step is implementing an end-to-end platform that incorporates all five analytics steps. However, the platform also needs to provide an intuitive user interface that anyone can use while automating repetitive and manual processes.
Ensure your organization can use the platform to find and access all available assets, properly govern and assign permissions, and schedule and automate reporting.
How to Build an Analytics Strategy
Before creating your analytics strategy, you must establish teams, goals, metrics, and more. Building these before you create your analytics strategy will help you clearly understand what your organization is trying to accomplish and solve business problems.
Here are the nine things you need to do to build an analytics strategy.
1. Establish Your Business Goals. Establish what it is you’re trying to do. Tie your objective to business goals. These might be common goals such as:
- Delivering better products
- Increasing sales
- Increasing customer satisfaction
- Reducing costs
2. Establish an Analytics Vision. Determine what it is you’re trying to learn from your analytics. This will help you focus your strategy on producing a measurable outcome. Examples include:
- Gaining a better understanding of what customers want
- Anticipating trends and using analytics to drive decisions
- Understanding the root causes for underperforming campaigns
- Discovering new ways to improve patient care
3. Determine and Assign Stakeholders. Your business goals and the metrics the insights you gain from your analytics will best serve those making business decisions. Determine the stakeholders who will benefit the most from your analytics output. Stakeholders could include the person who:
- Develops and launches new financial offers to customers
- Heads product demand
- Administers healthcare pricing
- Oversees regional promotions and campaigns
4. Tie Your Strategic Initiative to Your Business Goal. Consider what you’d like your data to tell you and how you would share that information with others. Think about this in terms of presenting a business decision and how you could back up your idea. This could include:
- We know what kind of financial offers people are looking for based on income, age, and goals and can offer them personalized packages.
- Based on in-store promotions, we can anticipate the products people will buy in conjunction with other products and can confidently increase orders for XYZ.
- We now have a better idea of the services our customers need and can more adequately staff and provide the right services, lowering costs.
- We understand how regional differences affect consumer demand and supply chains and can increase sales by stocking products that appeal to each region.
5. Determine How You’ll Measure Success. Use metrics to help you determine whether or not your strategy is effective. This will help you evaluate your strategy as you move forward and determine whether or not you need to adjust it. Meet with your stakeholders to determine what they’re trying to accomplish to help set these goals. Include metrics/goals such as:
- Increasing sales by 10% YoY
- Reducing costs by 3%
- Increasing demand forecast accuracy by 5%
- Decreasing patient wait times
6. Determine How to Pay for Your Initiative. Ensure your analytics initiatives will have proper funding to kick off your project, continue supporting it, and handle any delays or obstacles that may pop up. You should be able to answer the following questions:
- How will the project be paid for at the start?
- How much will it cost to continue paying for it?
- How much will it cost to expand?
- How much should we allocate to unforeseen costs?
7. Ensure Adoption and Buy-In. The easier you make life for the people using your new analytics platform, the more likely they’ll be to adopt it. As you build a strategy, think of areas where you can:
- Reduce learning curves for your teams
- Provide assets and resources for learning
- Make sure everyone understands the goal
8. Prepare for Challenges. Reduce potential delays by meeting with everyone involved and creating a list of potential challenges. Some potential problems might have been raised during previous meetings about your analytics strategy and implementation. Common problems include:
- Installing and integrating technology
- Not providing enough training
- Rolling out to too many people, too soon
- Not having enough people to support adoption
9. Review Progress of Projects, Programs, and Technology. Ensure everything is running smoothly by creating a group to oversee and review the progress of projects, programs, and technology. Often, companies focus on the results of projects in terms of sales or deduction in costs, which they should. But they should also focus on the performance of training programs and how well technology is performing. Things you can do include:
- Reviewing projects based on projected timelines and roadmaps
- Assessing learning plans and programs based on completion
- Evaluating technology integrations based on use and results
4 Analytics Strategies to Optimize ROI
Now that you know the elements needed to build an analytics strategy, it’s time to create one.
Here are four strategies you can implement to create a successful strategy that will deliver on results.
Strategy 1: Use Comprehensive Platforms that Limit the Number of Tools End Users Must Master. To select the right tools for your analytics needs, first, identify your organization’s specific needs, then find a solution that meets those needs. As previously mentioned, you should look for a solution that enables your organization to access data, find assets, analyze, and export everything in one platform. The platform should also allow you to solve business issues, such as:
- Improving customer satisfaction
- Increasing revenue
- Reducing costs
- Improving employee satisfaction
- Improving product quality
Consider other important factors, such as scalability and sustainability when selecting a platform. Your solution should be easy to use by everyone in your organization — including non-technical users.
Strategy 2: Involve as Many People as Possible in Analytic Outcomes. Ensure everyone in your organization understands how to use data and what it means. When you create a data literature culture, everyone should understand how to use data to improve their work. To establish a data literate culture:
- Start at the Top: Senior leadership needs to lead your analytics initiative and model the desired culture
- Make Data Part of Everyone’s Job: Everyone should be responsible for using data to improve their work, not just the analytics team
- Measure Essential Metrics: Select the metrics that help you solve business issues; avoid creating data just to say you have it
- Encourage a Growth Mindset: Help employees see failures as opportunities to learn and grow
- Reward Success and Experimentation: Try new things and reward employees for their creativity
- Make Data Accessible: Make sure everyone has access to the data they need to do their jobs
- Invest in Training: Provide training on how to use data and analytics tools
Additionally, develop these goals in alignment with your IT department to ensure all of these goals can be met. They’ll be vital to overcoming any obstacles that may arise.
Strategy 3: Add Flexibility to Your Analytics Deployment. Raw data is not helpful unless it can be transformed into actionable insights. To do this, data must be available, transparent, and managed properly.
- Data Availability: The data you need should be easy to find and access. It should be stored in a central location where everyone in your organization can discover it — provided they have been authorized to access it.
- Data Transparency: Data should be understandable and consistent. Everyone in your organization should be able to understand what the data means. They should be able to leverage work that others have created to ensure scalability, which also requires clear data lineages.
- Data Management: Data needs to be appropriately managed to ensure it is accurate and up to date. This includes maintaining a clean database, ensuring data quality, and establishing processes for data governance. Implement data catalogs and classification to help with data management and lifecycles. How you implement this will depend on the specific governance requirements and compliance regulations your organization adheres to.
Strategy 4: Ensure Usability for All Across Your Analytics Investments. The tools and platforms you invest in need to serve all stakeholders and their needs. While leaders, analysts, and data scientists will use different processes and applications to get information, they will all be working towards the same goal. Identify analytic tools or platforms that:
- Can automate multiple steps of analytics, including cleaning, analyzing, data science, machine learning, and more
- Provide an end-to-end range of features, including analysis, governance, and lifecycle management
- Easily integrate with other data sources, types, and services you have, including those used by third parties and others you partner with
As you build your analytics strategy and implement it, you need to view it as a process and ensure that all the technology you invest in supports it. This requires a strong understanding of your current analytics maturity, which you can assess here.
A solid analytics strategy can help your organization see ROI from its current analytic investments. The right strategy requires an approach that includes everyone in your organization. By including everyone, everything, everywhere, and making analytics easy, you can improve your analytics maturity and deliver business value on any goal.
Read the full report from IDC here.
*1-3 “4 Ways to Unlock Transformative Business Outcomes from Analytics Investments.” , sponsored by Alteryx August 2022 | Doc. #US49458122