We’ve all been there – staring at a mountain of data, reports piling up, and emails flooding in, yet still feeling paralyzed when it’s time to make a big decision. The bottom line – most businesses are drowning in data, but are not data ready. Indeed, what we need is relevant information – targeted and timely – to make informed decisions. Think of it like a detective solving a case – they don’t collect every piece of evidence in the city; they focus on what matters to crack the case.

In this article, I’ll share with you a 5-step process to keep your organization data ready. As a result, your business can routinely make timely, informed decisions using targeted, relevant information. For any type of decision-making, this information collection process starts with a decision-maker identifying their information requirements. From there the decision team or process identifies what they know and what they do not know. This is their information gap. As a result, they gather only the information needed for that decision, clarify it, and deliver the most relevant information they can in the time available. From there, the decision-maker, armed with the best information, moves forward confidently, assured that their decision will achieve the desired outcome.

Step 1: Know Your Desired Outcome: The Smart Start to Information Collection and Better Decision-Making.

To make informed decisions, it’s crucial to define a clear desired outcome before gathering information. For example, this means painting a vivid picture of what you want to achieve, such as “increasing customer retention by 15% in six months” or “reducing production costs by $100,000 this quarter.” By doing so, you’ll be able to focus on gathering relevant, time-sensitive information that matters, rather than collecting interesting but useless data. Without a doubt, clarity of purpose is essential for effective decision-making and information gathering.

Without a doubt, organizations do not need to collect and catalog every piece of data they touch for their decision processes. That’s a highway to analysis paralysis, not insight. For example, take a manufacturing firm optimizing production: they don’t need every news article or social media post about global events. Instead, they must focus on making data ready—relevant, accurate, and accessible—for their most critical decisions. For instance, like precise order backlogs, real-time machine availability, or immediate raw material lead times. Generic noise won’t do; targeted, timely information will.

“… focus on gathering relevant, time-sensitive information that matters …”

Step 2: Map Out Your Decision Criteria, Scope and Constraints to Guide Your Information Gathering.

Besides, defining the desired outcome to guide information gathering, you need to map out the decision’s scope, key decision criteria, and any constraints. With these decision elements described, information gathering and analysis is focused on only what is needed. Think of this step as creating your decision blueprint – it’s the foundation that makes everything else easier. By getting specific about what you’re choosing between, what matters most, and what limits you’re working within, you’ll save time and make better decisions quickly. Here’s how to break it down: your decision’s scope, criteria, and constraints.

a. Identify Your Decision’s Scope: What’s Possible in Terms of Actions and Capacity.

First, for any business decision, start by meticulously mapping out what is possible in terms of actions and available capacities. This isn’t about premature judgment; it’s about robust scoping. For example, if you’re selecting software, list every realistic vendor—Salesforce, HubSpot, Zoho. For a hiring decision, identify all potential candidate pools. Consider this as uncensored brainstorming. At this point, you don’t need detailed courses of actions, just a broad, honest inventory of what’s possible. As a result of this scoping effort, you and your team have the focus needed for targeted information collection, ensuring you gather only what’s truly relevant to make the best decision.

b. Define Your Decision Criteria. 

Next, to make informed decisions, define what success looks like by identifying your must-haves. For example, decision criteria for selecting software could include a user-friendly interface or other specific features. Also, limit your decision criteria to between three and eight to keep the process manageable, focusing on what’s critical. Additionally, you don’t need to finalize these criteria, just identify them well enough to guide your information gathering efforts. For example, focus on financial information if cost is a key criterion. For more information on decision criteria, see Simplicable’s 100 Examples of Decision Criteria and their decision criteria chart above. Also, see Tatyana Fittipaldi’s article, Why Is Decision Criteria Important in Decision-Making?

c. Determine Your Constraints.

Lastly, identify your limitations and major risk areas, especially any unacceptable risks. For instance, maybe you have a strict budget of $50,000, need to implement within 3 months, or require specific security certifications. These constraints act as guardrails, keeping you focused on realistic options and preventing wasted time on courses of action that are not feasible.

More References on Decision-Criteria and Risk Identification.

Risk Mitigation For Supply Chains: How To Best Identify, Make Assessment, Overcome

For further insights on these topics, here are some recommended readings:

• For decision-centric information gathering, check out Mark Zangari’s article on The Decision-Centric Dashboard.
• To better define your business intentions and targeted outcomes, my article Schwerpunkt: The Way Businesses Get Their People To Seize Opportunities, Shatter Competitors provides valuable guidance.
• For strategies on identifying and mitigating risks in supply chains, see my article Risk Mitigation For Supply Chains: How To Best Identify, Make Assessment, Overcome.

“By getting specific about what you’re choosing between, what matters most, and what limits you’re working within, you’ll save time and make better decisions quickly.”

Step 3: Think Through What Relevant Information You Need to Know.

Now that you know where you’re going and what stands in your way, you can figure out what information actually matters to assure a superior decision. For example, let’s take a product launch. Here, you’ll need vital data like competitor pricing and customer pain points, not trivial details about their office setup. Also, keep tabs on your business trends and any unusual patterns in your data feeds, but don’t get lost in the weeds. The key is to gather information that helps you reach your desired outcome – nothing more, nothing less. To break this down, let’s look at in detail the different sources of information and how to quickly determine which is relevant.

a. The Sources of Relevant Information: Data, Information, and Knowledge.

In modern businesses there are many sources of relevant information. For example, this can mean tapping into both internal enterprise systems (e.g. CRM, ERP, HRM, BI) and external feeds (e.g. market indicators, weather patterns, social media sentiment). Further, these sources can include raw data and pre-processed information. Also, another source of relevant information is organizational knowledge. All of these sources of information can have relevance, leading to insights for making the best decision. However, what specific information is actually relevant? To help sort out these sources of relevant information, see chart below, The Flow from Data to Information to Knowledge. and subsequent descriptions.

Organizational Insights: Data, Information, and Knowledge Sources

Knowledge Management Breakthrough – The Best Way With AI, Data, And Graph Tech

• Raw Data as a Source of Information. This is the digital representation of facts or events, acquired through various means such as observation, IoT devices, and other systems. Additionally, data is usually stored in raw alphanumeric values (e.g. “Customer Number”, “Unit Price”). Further, it can contain generated values (e.g. “Net Pay”, “Percent Complete”).
• Information Is the Result of Analysis. Here, information is derived from analyzing raw data, providing insights that enable decision-makers to make timely and actionable decisions. Moreover, it is a perishable commodity that transforms into knowledge when recorded and used to aid in future decision-making. For more on this subject, see Tim Bryce’ post, Defining Information Requirements.
• Knowledge Is What Is Know. Lastly, knowledge refers to the collective understanding and past experiences of an organization, based on decisions, policies, and best practices. Also, organizations are increasingly leveraging knowledge tools like graph technology to store and rapidly access this knowledge when needed. For more on knowledge management and tools, click here.

Also, for an excellent source for the flow of data, information, and knowledge in the context of decision-making, see The Internet of Water Coalition’s posting, What are Data, Information, and Knowledge.

b. How to Determine What is Relevant Information.

To determine if information is relevant, start with your core decision requirements identified earlier: what outcome do you want, what is possible, what criteria matters to you, and what limits you face. Think of these elements as a filter – they help you quickly separate useful data from noise. Specifically, you can use these decisions elements to determine relevancy in terms of the information’s applicability, accuracy, and timeliness. So the key relevancy questions to ask are:  

Information Relevancy Questions

• Applicability: Is it applicable to achieving a successful outcome? Would it help rule out certain options?
• Accuracy: Will it validate any key assumptions or confirm accuracy of the situation?
• Timeliness: Can we collect and analyze it in time?

More References of Information Relevancy.

For further reading on determining relevant information, consider the following resources:

• Accounting Insights’ article, Think Through What Relevant Information You Need to Know, provides clear criteria for identifying relevant information.
• Marine Corps University’s slide packet on Intelligence Preparations of the Battlespace offers a detailed process for identifying relevant information.
• My article, Organizational Situational Awareness: How To See Remarkably In The World Of Digital Tech and AI, discusses the importance of gaining organizational situational awareness.

“Now that you know where you’re going and what stands in your way, you can figure out what information actually matters to assure a superior decision.”

Step 4: Determine What Relevant Information is Missing – the Raw Data You Need.

In this step of getting your data ready, you now look at the information gap between what you know and what you need to know. For example, maybe you have great customer feedback but no clear picture of your production costs. Or perhaps you understand the market well but aren’t sure about regulatory requirements. So to sum it up, what you do not know is the relevant information that you need to get the data ready for informed decision-making. Consequently, you can then identify the data sources such as a system or data repository that will close the information gap. Also, you need to think through how you will acquire and analyze this data to support timely decision-making.

Surprisingly in this tech-driven world, we’re facing a unique challenge. Namely, we are collecting more data than ever, but struggling to analyze it effectively. To keep up, we must continually look to leverage new tools like AI and advanced data analytics to make sense of this vast information generated by our systems. For more on information overload, see Peter Gordon Roetzel’ paper, Information Overload in the Information Age.

“… look at the information gap between what you know and what you need to know.”

Step 5: Gather, Clarify, and Deliver the Most Relevant Information You Can in the Time Available.

Lastly, in this final step you and your team will need to pull together the relevant information necessary to make a timely decision. Without a doubt, timeliness is critical for decision-making as it minimizes information latency and maximizes agility. To have the ability to gather, clarify, and deliver relevant information in a timely manner, businesses need to have the right digital infrastructure in place. To meet these information requirements , a “Data Ready” infrastructure needs to focus on the organization’s most prized asset, data, and not be application-centric. Also, businesses need rapid, secure access to the right information on-demand. To detail a “Data Ready” infrastructure further, see below.

Major Components of a Data Ready Infrastructure

A Data-Centric Business: The Best Way To Agility, One Truth, Simplicity, Technology Innovation

• A Data-Centric Architecture: Enables Agility, One Truth, Simplicity, On-going Tech Innovation. Today, most organizations trap their data within an application-centric architecture, a cycle of legacy software silos and endless data migrations. To get “Data Ready,” businesses need to change. They need to prioritize establishing a data-centric architecture that eliminates data as a disjointed by-product of software and free it to be a durable, insight-driven asset. For more on how to start building a data-centric architecture, see my article, A Data-Centric Business: The Best Way To Agility, One Truth, Simplicity, Technology Innovation.
• Seamless Data Exchange: Accessible, Understandable, Secure. Also, a primary barrier to Data Readiness is the slow, laborious process that IT departments go through to integrate systems. Worse, even when businesses can transfer their data securely, the shared data is still not interoperable for the receiving systems and decision-makers. This is because the data is neither understandable, nor actionable. For advice on how to achieve true seamless data exchange. See my article, Logistics Data Interoperability: Advice To Make It Understandable, Usable, Secure, on how.

Logistics Data Interoperability: Advice To Make It Understandable, Usable, Secure

Indeed, to be competitive, businesses need a “Data Ready” infrastructure and processes to make good decisions rapidly. Additionally, businesses must balance timeliness over gathering “perfect” information. So, decision teams must focus on getting the most crucial missing information pieces first. Remember the focus is on making a rapid, informed decision, not delivering an elaborate slideshow. Hence, this process doesn’t need to be pretty as long as it results in the best information for making an informed decision at the optimal time.

“… it is key to balance timeliness over gathering “perfect” information.”

Conclusion.

In this article, I’ve shown you a 5-step process to get your data ready, resulting in targeted, relevant information to make a timely, informed decision. Specifically, this information gathering process starts with a decision-maker providing guidance for information gathering. From there the decision team identifies what they know and what they do not know. This is their information gap. Consequently, this void in information reveals what data they need. As a result, they gather what is necessary using their “Data Ready” digital infrastructure, clarify it, and deliver the most relevant information they can in the time available. From there, the decision-maker, armed with the best information, moves forward confidently, assured that their decision will achieve the desired outcome.

For more on using tech to help executives make rapid, informed decisions, see my article, An Agile Decision Platform to Empower Executives For Superior Supply Chain Performance: Here Are The Best Attributes.

An Agile Decision Platform to Empower Executives For Superior Supply Chain Performance: Here Are The Best Attributes

Lastly, if you are in the supply chain industry and have a need to supercharge your decision-making cycles, please contact me to discuss next steps. I’m Randy McClure, and I’ve spent many years solving data analytics and decision support problems. As a supply chain tech advisor, I’ve implemented hundreds of successful projects across all transportation modes, working with the data of thousands of shippers, carriers, and 3rd party logistics (3PL) providers.  I specialize in launching new analytics-based strategies, proof-of-concepts and operational pilot projects using emerging technologies and methodologies. To reach me, click here to access my contact form or you can find me on LinkedIn.

For more from SC Tech Insights, see the latest articles on Data Analytics and Decision Science.