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How Real-Time Data can Help CEOs Make the Right Decisions

7 Steps to Transforming your Data for Better Decision Making

CEOs can use data to make the right decisions

CEOs need real-time data to guide their decisions and utilize past information to predict future trends; in the same way, Frodo needed Gandalf’s guidance to help him avoid the treacherous paths to successfully deliver the one true ring to Mordor and save The Shire. Instead of saving the Shire, you’re saving your business from disaster as a result of poor decision making.

A highly successful retailer at the top of its category generates terabytes of consumer data on a minute-by-minute basis. In order for the CEO to make decisions, she asks her head of Business Intelligence (BI) to write a brief and submit it to their external data consultancy. The results can take weeks or even months in some instances as the data lies in various formats and sources and needs significant manipulation before making decisions, leaving her effectively ‘flying blind’.

While we do not reside in the dark ages, many CEOs find themselves trapped in the dark due to a lack of clarity with no access to the insights hidden in their data lakes or warehouses.

CEOs are used to making decisions based on limited or ambiguous data, and often these decisions have far-reaching consequences. It’s often critical to make decisions early because later on, there is no longer anything fundamental to decide.

Danish theorists encourage CEO’s to be courageous and make decisions based on minimal information, but is there another way?

The Consequences Model

How then can a CEO bridge the gap between doubt and decision? (2015) conducted substantial research that showed that big data analytics offers several benefits for data-driven decision making:

  • Cost reductions (47%)

  • Improved understanding of customers (52%)

  • Increased control over operational processes (54%)

  • Better strategic decisions (69%)

Today’s CEO suffers from analysis paralysis brought on by having access to too much data yet too little information: According to extensive statistics gathered by SeedScientific (2021), around 2.5 quintillion bytes of data gets generated daily, and by 2020 the data tally had spiked to 44 zettabytes worldwide. The global data prediction for 2025 marks a total of 175 zettabytes, which is a staggeringly titanic amount of data.

Instead of driving innovation and business decisions, these warehouses of data your customers generate are highly fragmented (known in the industry as disparate data), coming at you from all angles and in various formats. This disparate data actively holds CEOs back from making the right decisions towards future success.

In an ideal world, CEOs can review insights from data at their fingertips and in real-time, using custom-built reports, but getting to this Utopia is going to involve first passing through the wasteland and battling a few Saurons along the way.

Fig. 1. A simulated report reflecting data analyzed by SEDGE for a tanker company to determine the influence on vetting inspection outcomes.

Most CEOs struggle to make accurate decisions based on online data; the definition of this process is data-driven decision making (DDDM). Bright Data (2021) defines DDDM as a tactical approach that utilizes data to make strategic predictions and influence business decisions. DDDM involves gathering data related to a key performance indicator (KPI) or quantifiable goals; after acquiring the data, it gets analyzed to identify recurring trends or patterns that can generate actionable insights.

When it comes to DDDM, four primary types of data analytics will assist CEOs in making more calculated decisions; Bright Data (2021) lists them as follows:

  1. Descriptive Analysis Uses raw data to describe a given/current situation; examples include monthly sales and conversion rates or an analysis of customers by demographic. This type of data analytics practice uses techniques like data mining and visualization.

  2. Diagnostic Analysis Analyzes the data to ascertain the “why”, focusing on identifying trends or recurring patterns. BI dashboards use this technique to determine the root cause of company issues.

  3. Predictive Analysis Analyzes previous and current data to predict what will happen in the future; predictive data analytics gives companies the ability to predict future market trends, revenue and sales. Methods used to analyze this data include machine learning and data modeling.

  4. Prescriptive Analysis Analyzes the findings collected by the previous three data analytics techniques to deliver value by providing a possible solution to the issue at hand. A practical example of this is Google Maps (or any other mobile GPS application) which uses prescriptive analysis to calculate the quickest route to reach your desired destination.

Without measurable data to support your business decisions, you are navigating blind and would have no better luck than Frodo traveling through the mines of Moria alone and without the guiding light of Gandalf. While taking risks and trusting your gut in business is a commendable (and often vital) skill, you cannot rely on intuition alone; basing your decisions on factual data and accurate information results in risk mitigation.

CEOs can make informed business decisions and formulate effective strategies to improve and expand their companies using quantitative data instead of relying on intuition.

We have highlighted the path to data-driven decision making below, with seven key steps needed to transform disparate data into measurable live data.

Data Based Decision Making Process

1. Define Business Goals and Evaluate Your Data

Before you can break free from the shackles of disparate data, you need a plan. Like Frodo met with the Fellowship of the Ring to discuss his plan to deliver the ring to Mount Doom, you must first plan to ensure your company’s success and ensure you surround yourself with suitable companions for the journey.

Asana (2021) defines setting business goals as a predetermined target that a business (or individual) plans to achieve in an allocated period. Companies can set measurable and attainable goals that influence motivation and boost overall performance.

Therefore, you must first define your business goals and the outcomes, then scope the project and determine the approach and deliverables. You should also evaluate the potential risks to create practical action steps to mitigate, prevent or eliminate them.

Secondly identify your companions for the trip: working with an experienced guide like SEDGE.AI will help you understand your company’s needs and help you navigate this perilous territory.

2. Organize Your Data:

The CEO of that successful retailer we mentioned above had data sitting in various formats and sources, from point-of-sale (POS) data in one data format, eCommerce website data in another data format, enterprise resource planning (ERP) and stock data in another format, plus the loyalty system in yet another data format.

Consolidating these data sources is the first step towards obtaining real-time data that can drive effective decision making; without it, you cannot make any measurable progress.

To effectively use this fragmented data, you must convert it into a single cohesive stream, ignoring columns, removing outlier data and transforming it into a single efficient format that is easy to read and understand.

Often this is the longest and most perilous part of the journey and one where your guide’s experience is critical.

SEDGE can offer guidance to help you along this challenging path; We provide advanced data collection and management expertise alongside artificial intelligence (AI) analytics capabilities that can help you to efficiently convert and organize disparate data into a single stream of live measurable data that offers actionable insights.

3. Engage in Data Governance

Now that you have consolidated the data into a single stream, you can clean it up and create processes and policies around the data to ensure it remains clean.

Data governance is an umbrella term for processes, roles, policies, standards, and metrics that ensure an organization’s effective and efficient use of information to accomplish its goals. Data governance advises the processes and responsibilities that affect the quality and security of data within an organization. This governance determines who has the authority to act in any situation and decides what methods get used.

According to Mordor Intelligence (2021), the Data Governance Market reached a value of USD 1.81 billion in 2020, and studies predict this value to increase to USD 5.28 billion by 2026, registering a Compound Annual Growth Rate (CAGR) of over 20.83% during the forecasted period (2021 - 2026). In dark times, knowledge is power, and actionable data assists businesses in making the right decisions; organizations that establish efficient data governance programs fare much better than those without any programs in place.

SEDGE can assist you with regulatory compliance and help companies adhere to all the necessary business and data policies.

4. Employ Business Intelligence

After Gandalf fell to his supposed death at the claws of Balrog, he took time to gather his power and wisdom; according to TechTarget (2020), an enterprise’s BI (Business Intelligence) systems collect, store, and analyze data produced by a company’s activities. Negash (2004) elaborates further, stating that the objective of a BI system is to boost the quality of inputs to the decision-making process.

Companies use BI systems to understand better their available resources, capabilities and technology; recurring trends and the actions of their competitors (Negash, 2004).

After the data gets analyzed, the BI system can use this actionable data to build visualizations and descriptive analytics timeously - you can better access, read and understand these insights after transforming the data into visual formats like tables or graphs.

TechJury (2022) states that most businesses adopted Business Intelligence in 2020 and predicts that over 33% of large-sized companies will practice decision intelligence by 2023. TechJury further indicates that the global business intelligence market will grow to $33.3 billion by 2025. BI systems are crucial for up to 60% of development and research departments, and data analytics increase the speed of decision-making up to five times more for businesses.

Therefore it is clear that the companies require an effective BI reporting system to obtain accurate data-driven insights.

SEDGE can assist by providing your company with efficient BI systems that will give you a competitive advantage through advanced insights. We can produce high-quality visualizations and descriptive analytics you can utilize to guide your business towards future success.

5. Build Visual Reports

Once you quiet the chaos and organize your disparate data into measurable real-time data, you can start to build visual reports.

According to Datumize (2020), there are many advantages to data visualization; CEOs, decision-makers and managers can use data visualization to build and analyze vital metrics. If any of these metrics display anomalies in the data — for example, sales have dropped dramatically in a particular region — decision-makers can delve deeper into the data to ascertain why these anomalies occurred. The other primary benefit of visual reports is identifying recurring patterns and trends. Datumize states that data visualization allows us to recognize emerging patterns or trends and respond accordingly. These patterns or trends are better understood when presented with visuals and diagrams, hence why data visualization and building reports are crucial to any business’s success.

You can use these comprehensive visual reports to evaluate past data, gain real insight into your company, and use these insights to predict future business trends and make smarter decisions based on the forecast of this data.

A practical, custom-based report will pull live data in real-time onto visual dashboards for straightforward interpretation.

custom-built visual reports and data dashboards

6. Utilize Machine Learning

TechTarget (2021) defines Machine Learning (ML) as a branch of AI that gives software applications the ability to more accurately predict trends and outcomes without explicit programming or human intervention. TechTarget states that machine learning algorithms input historical data to predict new output values.

According to Sanghavi (2021), the Global Machine Learning Market will increase at 42.08% CAGR during 2018–2024 and 65% of companies who plan to adopt ML state that technology assists businesses with the decision-making process. Sanghavi goes on to state that North America (80%) currently leads the ML adoption, followed closely by Asia (37%) and then Europe (29%). These figures are unsurprising considering the adoption of Machine Learning in business recently boosted to unprecedented levels and deadlocked so many companies and companies in the race to ascertain, analyze and leverage data insights. The marketing, sales, operations and product/service development departments, in particular, displayed the highest increases due to Machine Learning.

In layman’s terms, this means that almost all businesses, regardless of size, have begun to adopt the machine learning process on an enormous scale.

Frodo could easily outsmart the Orcs, who lacked any significant intelligence while fearsome and vicious. In much the same way, SEDGE’s machine learning utilizes AI to outsmart tough challenges by building custom models that are unique to your company’s specific needs to help forecast trends or recurring patterns.

7. Use Visual Reports to Make Effective Business Predictions and Decisions

After your data gets compiled into visual reports, you can now analyze the past and pinpoint particular recurring patterns or trends. You can use this insight to make predictions of future trends or patterns and make better decisions accordingly.

SEDGE can assist you with interpreting these visual reports in a concise and easy to understand manner. With all the guidance and tools available at your fingertips, you can save your company from impending doom, like Frodo, who delivered the ring to Mount Doom in Mordor and prevented it from falling into the hands of Sauron.

In the end, it all comes down to data, and without access to live data, you, CEO, are stuck in the dark ages of disparate data and will continue to make the wrong decisions which could ultimately lead to the failure and collapse of your business and help you to stay ahead of the competition.

SEDGE can assist you on this journey by implementing a predictive AI analytics platform that uses machine and deep learning to decipher patterns and perform advanced statistical analysis to predict outcomes.

We can help you optimize your decision-making process through powerfully visualized data.

Contact SEDGE today for more insight into how you can save your business from impending collapse.

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