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According to recent research by IDG Enterprise, more than half of (53%) decision-makers at enterprises reported that their company was currently planning on implementing a data-driven project of some sort in the near future. The same study also found that 78% of individuals surveyed felt that the analysis of data for decision-making would “fundamentally change the way their company does business”. Furthermore, 71% of these same respondents also felt that this endeavor would create additional revenue streams and opportunities for business within just a few years.
If these statistics show us anything, it’s that more and more companies looking to achieve success in today’s business landscape are beginning to see the value in data and the profound impact it can have on the decision-making process. It’s easy to understand why. Companies who adopt a data driven approach report not just higher profits, but also higher productivity than those who don’t. If you’re currently interested in learning more about data-driven decision making and how it can benefit your company, then this article will serve as a great resource to help educate and inform you on the concept.
What is data-driven decision making (DDDM)?
Data-driven decision making (also referred to as DDDM), is the process of gathering and analyzing data for the purposes of using the insights gained to influence important business decisions. Data-driven decision making is more than just simply browsing through website analytics or sales and customer data to get a feel for what future steps should be taken. It involves the creation of a systematic approach to data collection, analysis and implementation of data-driven decisions, as well as an investment in quality tools and skills in order to facilitate this approach.
Why make data-driven decisions?
Data-driven decision making is superior to other forms of decision making because it ensures that decisions are based on logic and reasoning as well as supported by numerical evidence. Without the use of data to inform decisions, decision makers run the risk of being subconsciously influenced by factors such as bias, external stimuli such as the opinions/demands of others, or acting on assumptions, gut-feeling or theory.
The benefits of data-driven decision making
There are numerous benefits to using data to influence the decision-making process. Data-driven decision making is beneficial because:
- It is objective. Data-driven decision making relies on statistics and numerical data and as a result is an objective process.
- It can be easily evaluated. The great thing about data-driven decision making is that it can be easily evaluated based on how the implementation of certain decisions impact various metrics.
- It facilitates greater control. With data-driven decision making you gain greater control over the direction of your business and the quality of your decisions. This is because it is based on objective data, concrete evidence and results can be effectively measured in order to assess impact.
- It increases agility. When data is influencing the decision making process, companies become more agile. They are able to detect new business opportunities sooner, identify issues more quickly (and at times even proactively), as well as respond to market changes more swiftly.
- It promotes greater transparency/accountability. Data-driven decision making is based on objective data and numerical information and as a result, facilitates greater transparency and accountability with regards to the decision making process.
As you can see, data-driven decision making provides businesses with numerous benefits which can have a profound impact on everything from business operations to customer service, sales, growth and expansion. Furthermore, it is extremely versatile and can be implemented in virtually any area of your business where you are seeking improvement.
Implementing a data-driven approach
There are essentially five steps to implementing a data-driven approach to decision making. These steps will provide you with a guideline when it comes to building a systematic method that integrates well with your current business model.
1. Define your goal
The first step is defining your objective. What is it that you wish to accomplish with data-driven decision making? Are you seeking greater sales? More efficient operations? Increased customer retention rates or an improved customer experience? Whatever the goal may be, it needs to be defined, focused, documented and communicated with your team in order to lay the groundwork for success. Communicating with members of your organization about the importance of this approach also helps to establish the right culture and shared values necessary in order to be truly effective. Remember, it's a team effort, and everyone needs to be on board and on the same page in order for this to work.
2. Establish a hypothesis
The next step involves formulating a hypothesis. Your goal/objective is what you would like to accomplish, however it's necessary to come up with an initial proposed strategy for accomplishing it. Focus on the area of business where you feel data-driven decision making will have he greatest impact. For example, perhaps your goal is to generate more leads by building your email list. Your hypothesis could focus on creating a lead magnet of sort such as a downloadable case study in order to impact the amount of email subscriptions you receive (i.e. If we add a lead magnet in the form of a downloadable case study to our website, we will increase email subscriptions).
3. Identify data need
The next step involves identifying your data need. There are two general types of data: qualitative and quantitative. Qualitative data is non-numeric and more subjective in nature than quantitative data, which is numeric and objective. Quantitative data is what pops in mind when people are talking about big data.
4. Build data process
Once you've identified your data need you will need to figure out how you are going to collect the data. Is this something your company is capable of doing itself or will you need to outsource the data collection process? Perhaps you're in a situation where you already have a process for collecting the data you need. If this is the case then you won't have to worry about this step, but you will have to ensure that your data is clean. If you do not currently have a process for data collection then you will need to decide who will be collecting the data you need. Is this source reliable? How is the data going to be sampled and what is the sample size? What about the number of your data sources?
Data coming from a single source is uni-dimensional and limiting in scope. As a result, it's generally best to have more than one data source. A recent study found that the average company uses five data sources. On average, three of these sources are external. What's even more interesting is the fact that more than half of these companies working in the data-driven business who were surveyed stated that the number of sources they use is expanding. If you plan on using multiple data sources, keep in mind that it's also necessary to have common variables throughout each of these sources so that information can be integrated from each accordingly.
Once this is decided upon, it will be necessary to assign data collection and management roles as well as to define various processes and protocols necessary to ensure everything runs smoothly.
5. Analyze data
Once your data process has been defined and your data begins to be collected, you will have to begin analysis. This is where an investment in quality tools is key. You may find that your company currently has the resources, skills and capabilities to analyze the data on it's own. If this is the case, then great. However, many companies find that they need a trained specialist in order to effectively handle this task. The decision is ultimately in your hands.
6. Make a decision
Once your data has been collected and analyzed it is now time to use the information and insights that were gained in order to make a decision. In order to do this, you will need to transform the insights into actionable tactics and strategies that translate to benefiting the business. It will also be necessary to present this data and communicate it in a manner that is easily understandable even to individuals who are not technically trained. Remember, presentation and timing is everything in order to make an impact. Regardless, you can rest assured that your decision is backed by hard numbers, quality data and supported by a systematic process designed specifically to ensure that your decisions are objective and sound.
Conclusion
Data-driven decision making isn’t just some new trend that businesses are striving to hop onto in order to remain relevant. It’s a statistically validated process which provides businesses with a systematic and objective approach to decision-making that can help to increase efficiency of processes, effectiveness of decisions, workplace productivity and business growth. If you’re considering leveraging the power of data in order to set your company up for success, then rest assured you’re making a sound decision.
Have you used data in any form to help inform and lead your decision-making processes? What was your experience? Let us know!
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