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Is Your Business Data Driven? The Ultimate Guide to Running a Data Driven Business

  • Writer: Travis Rawls
    Travis Rawls
  • Jan 16, 2024
  • 6 min read

Data-driven is so much more than buzzy headlines, it is a true differentiator for a business –it drives 2.5X better results, our Founders have experienced this firsthand at Adobe, Accenture, Google, and Freshworks.


Adobe transformed into being Data Driven; investing in systems, process, and culture, to successfully navigate from perpetual software to a SaaS model, and now the AI revolution. Adobe is one, if not the best, case study in major business model overhaul, and did so seamlessly, due in large part to their data-driven culture.


In 2023, we saw many companies that did not operate in a data-driven way, causing missed numbers and reductions of force. Here we learn how to avoid this mistake and take steps to become more data-driven.



What does it mean to be data-driven though? Why is it such a competitive differentiator? How can the organization become more data-driven and increase data literacy? We will get to the bottom of these important questions throughout this blog post!


In short, being data-driven is about listening to what the data tells us, operating with slight ambiguity, and challenging the status quo! Let's dive deep into what this all means.



How does being data-driven drive 2.5X Better Results?


This all may seem a little buzzy and like PR Headlines, it is not, our Founder has seen this all in action and it is the reason one of the world's best MBA Programs built a model for simulation of the Data Driven Operating Model Pioneered at Adobe.


Being Data Driven, and having a transformative data culture drives real results:

  • For companies that were leaders in data and analytics, there was a three-times-higher growth in revenue.

  • They were also three times more likely to have quicker time-to-market.

  • In addition, they were twice as likely to report improvements in profits, customer satisfaction, and operational efficiency. (IDC White Paper)


Okay, so being data-driven can help across the board. It helps remove biases, ensure the right decisions are being made, and if not, allows the business to quickly learn and do differently!


At River.io we try not to speak in absolutes, but nearly everyone has an opportunity to be more data-driven!


Sounds expensive...Sure you can invest in expensive systems, headcount heavy models, and deploy the most advanced technologies, but being data-driven does not need to be so expensive or complex.


Most businesses can take non-disruptive, yet transformative steps in 2024 to redefine the business!


Okay, so what Does Data Driven Really Mean?


You will find lots of spirited debate on what it means to be data-driven, but most can be summarized by the 5 Pillars we track at River.io.


A great example of how at River.io, we believe in Frameworks versus playbooks, your data-driven culture may look a little different, but these core tenants should always be present.


Pillars to Being Data Driven:


  1. Data Literacy -  Ability to read, understand, create, and communicate data as information.

    1. How well is the data understood within your business?

    2. Does your executive staff understand your data and data as a whole?

    3. Do you have employees with data acumen across the entire organization?

    4. Are there regular training programs in place to enhance employees' data literacy skills? Are new hires trained in the organization's data?

    5. Is data visual and/or craft compelling stories?

  2. Repeatability & Accessibility - Data repeatability ensures consistent research results when procedures are duplicated, while data accessibility focuses on the ease of obtaining and using data.

    1. Is there a set of KPIs across each business?

    2. Are the KPIs shared across groups?

    3. How do you ensure the consistency of data collection and analysis methods across various projects?

    4. Is there a centralized data repository accessible to all relevant departments?

    5. How do you address discrepancies in data interpretation among different teams?

    6. Are there standard protocols for data sharing and collaboration between departments? How is data quality maintained when sharing data?

  3. Data Democratization - The practice of making data easily accessible and understandable to non-experts, allowing a wide range of people to use data for informed decision-making without specialized skills.

    1. Are there OKRs? Do OKRs cascade throughout the organization?

    2. How is data made accessible to non-technical staff in your organization?

    3. Are there tools in place that allow employees to easily interact with and understand data?

    4. Does your organization have a culture of trust where people feel comfortable bringing their insights, theories, and opinions to the table? How is data that goes against conventional wisdom treated?

    5. Are goals interlocked across the organization and bought into? Or forced top-down?

  4. Data-Driven Decision Making (Most Difficult) - The process of making choices based on data analysis rather than intuition or observation alone. It involves collecting and analyzing relevant data and using the insights gained to guide decision-making processes

    1. Can you provide examples where data-driven decision-making significantly influenced the business outcome?

    2. How do you integrate qualitative insights with quantitative data in decision-making?

    3. What mechanisms are in place to evaluate the impact of data-driven decisions? How do you make decisions with ambiguity?

    4. What steps are taken to continuously improve the data analysis skills of decision-makers?

    5. How frequently do different departments utilize data analysis in their decision-making processes?

  5. Transparency and Authenticity - Data transparency ensures open, understandable information about data sources, processes, and results, while data authenticity verifies the data's originality and integrity. Both are crucial for trust and reliability in data use.

    1. What processes are in place to ensure the transparency of data sources and methodologies?

    2. How do you verify the authenticity and accuracy of external data sources?

    3. What steps are taken to communicate the limitations or uncertainties of data used in reports?

    4. How is data authenticity maintained in collaborative projects or partnerships?

    5. What role does leadership play in promoting a culture of data transparency and authenticity in the organization? Does leadership embrace bad news? Or only good news?

    6. How do you balance the need for open data access with maintaining data security and privacy? How do you ensure that sensitive data is protected while promoting data democratization?


If you do all 5 of these Pillars well, you may be able to say you are a Data-Driven Organization, but if you only do a few well, it is likely there is room to be much more data-driven in your approach! Next, we will look into low-hanging fruit to become more data-driven.


Subscribe and stay tuned to our blog for deep-dive posts on each of the 5 Pillars of Being data-driven.


Or Reach Out and Take the Data-Driven Maturity Assessment to see how your business benchmarks!



The Low-Hanging Fruit to Become More Data-Driven


Being data-driven does not need to be a costly exercise, shouldn't require years-long consulting work, and real steps that change your culture may be made in a short period.


We are still in January, there will never be a better time than the present to be more data-driven, but as we sit at the start of Q1, now is the perfect time to kick off the work and reap the results throughout the year!


The Low-Hanging Fruit to Become More Data-Driven:


  1. Data Literacy -  

    1. Establish a New Hire Curriculum

    2. Cross Functionally Train on KPIs

    3. Create Data Dictionaries and Depositories

  2. Repeatability & Accessibility -

    1. Establish North Star Metrics if none exist, expand to 3 Top KPIs if North Stars exist

    2. Build a Unified Monthly Reporting Cadence across the entire Customer Journey

    3. Kickoff creation of interlock schedule and process flows

  3. Data Democratization -

    1. Create a centralized Dashboard of the Customer Journey, if too much effort, start with sharing each group's primary dashboards amongst other groups

    2. Validate Tops Down Assumptions with Bottoms Up Modeling, implement strategies for gaps or relief for unsustainable plans

    3. Encourage staff to bring insights forward and look across the entirety of the business

      1. "The best employees are those who take ownership of their work and feel like they are part of the company, not just working for it." - Ben Horowitz

  4. Data-Driven Decision Making (Most Difficult) -  

    1. Foster a culture of accountability based on data

    2. Evaluate decision-making to determine if data was adequately used to inform decision-making

    3. Encourage that great ideas can come from anywhere in the organizations, and ensure ways of collaboration and communication that foster this

  5. Transparency and Authenticity -

    1. Implement OKR based on KPIs, and cascade these throughout the organization

    2. Share the Executive KPI Progress at Each All Hands, provide a truthful and realistic perspective on performance

    3. Encourage a culture of 1-1's with staff and periodic extended staff meetings


Complete all of these tasks, and huge strides will be made, even a handful or two may have a profound impact on your business.


Adopt a more data-driven approach to drive 2.5X better results!



Contact us to learn more!

 
 
 

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