Being in business is not as simple as it seems. I know most entrepreneurs will agree with me. Lots of planning and strategies are needed before any decision-making. If you are also facing issues in decision-making, I suggest you go through this article once. Lots of new dimensions have been involved in business in recent times.
For example, now business strategies are planned based on facts. And, not just facts it also uses metrics and data to help you achieve your goals, initiatives, and objectives. If I have to tell you in short it’s called data-driven decision-making.
Basically, this data helps you to make better decisions for your business and company, whether you are a manager, analyst, or consultant.
I’ll Explain to You the Process of Guiding Business Strategy Using Facts- Data-Driven Decision Making
Having a normalization of data-driven decision-making helps employees to build curiosity and think critically. All the conversations and decisions then become data-backed, and their data skills gradually improve with practice and application.
What you need for implementation is quick and guided access to the required data, which is stored safely and the access is governed too. The whole shift towards this data usage across all job levels will create proficiently trained people, who can then encourage others to follow suit.
The Icy Whiz team interviewed Timothy J Williams, Principal Consultant at Thinksia, about the intricacies of data-driven decision-making. Here is what he said:
“In my experience as a seasoned executive with a focus on using data-informed insights for business growth, one of the pivotal challenges in the data-driven decision-making process is ensuring the relevance and accuracy of the data collected.
Within my role at Thinksia, we emphasized the critical need for precision monitoring, utilizing real-time analytics to not only collect data but also to guarantee its applicability and integrity.
For example, in developing marketing strategies for our clients, we deployed targeted analytics to sift through vast amounts of consumer data, focusing on specific metrics that directly influence campaign performance, such as engagement rates and conversion metrics.
This approach of selective data analysis helped in overcoming the challenge of data relevancy, streamlining the decision-making process.
Transitioning from data collection to actionable strategies often presents the challenge of translating insights into practical, executable plans.
Leveraging my certification in SOSTAC® Planning and my experiences, I’ve found the application of structured planning frameworks instrumental.
These frameworks guide the segmentation of insights into strategic and tactical actions, enabling a coherent transition from ‘what the data tells us’ to “how we can utilize this information.”
In one instance, by adopting such frameworks, we identified a gap in digital channel utilization for a client, subsequently crafting a digital expansion strategy that directly addressed this gap, significantly improving their market reach and customer acquisition rates.
The final hurdle, fostering organizational buy-in for data-driven strategies, requires a sophisticated blend of communication, demonstration of value, and inclusivity.
From my leadership experiences, I prioritized instilling a culture of data appreciation by highlighting success stories where data-driven decisions had led to growth or improved efficiency.
Utilizing insights from our precision monitoring and strategic planning, I regularly facilitated workshops that showcased the tangible benefits of our data-informed decisions, such as improved ROI on marketing campaigns, to foster a deeper understanding and appreciation for data across all levels of the organization.
This approach significantly reduced resistance, cultivating a more data-positive culture which in turn empowered more informed and effective decision-making.”
One Needs to Understand the Importance of Data-Driven Decision-Making
Data that is available with any company, or with the decision-making sector of any company is huge, analyzing this data is a big task. Indeed, it has been seen that many companies even after spending a lot of money can not really succeed in helping their businesses using this data.
This is where data-driven decision-making comes into play. It starts with companies building data proficiency, analytics agility, and community. Transforming the entire data analysis and decision-making process is not easy but eventual incorporation of these will help you and your organization.
Dhari Alabdulhadi, CTO and Founder of Ubuy New Zealand emphasized the investment in data-collection tools in data-driven decision-making. Here is an excerpt from the interview:
“Businesses face several challenges during the different phases of data-driven decision-making.
The major challenge is collecting relevant and accurate data from different sources. Businesses should invest in data-collection tools, implement validation processes, and check data-governance standards.
Another challenge is organizing data for easy access and analysis and ensuring data security. Businesses can opt for cloud-based storage and organizing tools to address these challenges.
Aligning data insights with business objectives can be challenging for businesses. However, this can be overcome by communicating and establishing a decision-making process.”
It’s the New Era of Data Culture
Collective behavior of people and their beliefs to value and practice, encourage the use of data in the decision-making process.
Data thus becomes a part of the operations and its mindset and helps in identifying the organization. This data-driven culture helps you to tackle complex business challenges.
To follow data culture one must align the data and its analysis to come to business outcomes/conclusions. Organizations also need to prioritize data in all decisions and processes of their business.
In an interview with the Icy Whiz team, Emma Collins, CEO of Trading.biz, shared her views on data-driven decision-making and the integration of data-centric approaches. Here is what she had to say:
“I think, one of the initial hurdles in data-driven decision-making is the collection of high-quality, relevant data. Often, the challenge lies not just in the collection but also in ensuring the accuracy and consistency of data.
To combat this, I’ve prioritized establishing strict data governance standards in my company. This ensures that the data we collect is reliable and forms a solid foundation for analysis.
Another significant challenge is the analysis and interpretation of data. With the vast amounts of data available, it can be overwhelming to discern what is truly valuable for decision-making. To address this,
I’ve invested in advanced analytics tools and trained my team in data literacy skills. This enables us to efficiently sift through data and extract actionable insights.
Implementing these insights into business strategies presents its own set of challenges, primarily due to resistance to change within the organization. To overcome this,
I’ve found that leading by example and demonstrating the tangible benefits of data-driven decisions can cultivate a more receptive culture.
Regular training sessions and clear communication of data-driven successes further encourage adoption across all levels of the organization.
Moreover, ensuring the security and privacy of data is an ever-present concern. Robust security measures and ongoing compliance with data protection regulations are essential to safeguard sensitive information, thus maintaining trust and integrity in our data processes.
Finally, I continually assess the impact of our data-driven decisions to refine and adjust our strategies.
This iterative process helps in stay aligned with both market conditions and internal goals, ensuring that our data utilization remains effective and relevant.
I hope my insights offer a comprehensive view of the real-world challenges and strategies in data-driven decision-making.”
Here Are the Steps for Making Data-Driven Decisions
1. Identify Business Objectives
This lays the foundation of the goals and targets of your organization, both executive and downstream. Targets can be literally in any spectrum like increasing sales, or website numbers it can be something as simple as increasing brand awareness also.
Having these goals figured out beforehand you will be able to identify your key performance indicators and other data and metrics that will help you form decisions. This will also give you an understanding of which data needs to be analyzed and what are the questions to be raised, to get closer to the objectives of your business.
2. Survey Business Teams for Key Resources of Data
The short-term and long-term goals of the employees as well as the organisation as a whole should be clear. This data will help in the analysis process, the data strategy will inform you about the relevant questions that need to be asked and what data sources should be considered.
In the end, this will help you to make better decisions when it comes to deciding about roles, responsibilities, and processes of your business.
3. Collect and Prepare the Data You Need
If all your data sources are disconnected then fetching data that is of good quality and that can be trusted becomes very difficult. So having an idea about the amount of data that you possess, you can start data preparation.
The first step is to create data with high impact and low complexity, for this first prioritize the data sources with larger applications to create quick impact.
4. View and Explore Data
Visualize all your data and try using impactful visualization methods so that you can have a better understanding. It can influence the decisions made by the seniors as well as staff members.
This can be done using charts, graphs, and maps. So, you can easily accentuate any trends, pretends, and outliers to provide conclusions and even inferences where usually, a bar chart is used for comparison, maps for spatial data, a line chart for temporal data, and a scatter plot to compare two measures.
5. Develop Insights Using Critical Thinking
Use critical thinking, which basically means finding insights and communicating them in a useful and engaging manner, as well as using visual analytics to ask and answer questions from your data in an intuitive manner.
Find out opportunities or risks that could help your business grow.
Based on the analytic interpretation, develop business recommendations that strategically align with the objectives of your organization.
6. Act and Share Your Insights
Once your insights are in line, you need to put out the word for implementation and collaboration on the same. You can build hypotheses about the possible strategies that could work as solutions to your business problems or opportunities.
Then test these hypotheses by various methods like A/B testing or surveys, whatever seems fit.
Once you have validated your hypotheses highlight, the key insights and use proper visualization methods to help influence the decision-making process, by taking the route of the most effective strategy.
7. Monitor and Evaluate
When you are presenting the findings to the decision-making authorities or to the board members make it clear why everything has been suggested. After the presentation and the collaboration has started you need to continuously monitor the work progress.
Check for bottlenecks if any, and make sure that the data collection and analysis process is perpetual and that the implementation is being done in a manner that benefits the business. As you go along the whole work, tweak any shortcomings, add what has been missing, and measure the effectiveness by analyzing the results.
Dr. Adam R. Cebulski, CEO and Founder of transform.forward, talked to the Icy Whiz team on this topic. Here is what he said:
“We often use the term data-informed rather than data-driven. The transition from data-driven to data-informed terminology in decision-making in today’s data-rich environment underscores a crucial evolution in business strategy: understanding that while data can guide decisions, it must be contextualized with human judgment and organizational nuance to truly be effective.
A common pitfall for many organizations is having access to vast amounts of data but lacking the expertise or processes to interpret it meaningfully. This is where data governance comes into play.
Establishing clear data governance practices is essential not just for managing and securing data, but also for building consensus on its meaning and use.
Without a unified understanding and agreement on how data should be interpreted, even the most data-rich organizations can find themselves paralyzed by information overload or misled by incorrect assumptions.
You’d be surprised how many times we end up in a room of executives who all have wildly different interpretations of a single data point and its impact on the organization.
Moreover, it’s critical to recognize that data points alone do not constitute a strategy. Many organizations fall into the trap of assuming that by presenting data and metric goals, stakeholders will understand and follow through with the necessary changes.
This overlooks the vital role of change management in the process. Effective data-informed decision-making involves not just presenting data, but also articulating a clear narrative that connects the data to strategic objectives and includes a roadmap for implementation.
To bridge the gap between data availability and strategic execution, organizations need to integrate change management principles into their decision-making processes.
This means preparing and supporting stakeholders through the transition that data-informed decisions entail, from initial understanding to full implementation.
Ensuring that people are motivated, equipped, and aligned with the new direction is as important as the data points that suggest that direction.
Thus, by focusing on data governance to secure a common understanding of data, and by employing robust change management to activate and sustain change, organizations can more effectively leverage their data to drive meaningful and successful outcomes.”
I Hope This Will Help You Out!
As we can clearly see data-driven decision-making is evolutionary. The transformation is huge and leads to better interpretations and understanding of the problems and the risks. It helps to get better decisions that are data-backed and helps your business to grow bigger and better every day.
Guest Author: Saket Kumar
Last Updated on May 17, 2024 by Pragya
Authors
I now recognize that making decisions based on evidence is an evolutionary process. There has been a significant shift that improves our comprehension of the dangers and challenges.