What is data-driven decision making?

Original article was published by Abrar Ahmed on Artificial Intelligence on Medium


What is data-driven decision making?

Photo by Franki Chamaki on Unsplash

Data-driven decision making (DDDM) is defined as using facts, metrics, and data to guide strategic business decisions that align with your goals, objectives, and initiatives. When organizations realize the full value of their data, that means everyone whether you’re a business analyst, sales manager, or human resource specialist is empowered to make better decisions with data, every day. However, this is not achieved by simply choosing the appropriate analytics technology to identify the next strategic opportunity.

Your organization needs to make data-driven decision-making the norm creating a culture that encourages critical thinking and curiosity. People at every level have conversations that start with data and they develop their data skills through practice and application. Foundationally, this requires a self-service model, where people can access the data they need, balanced with security and governance. It also requires proficiency, creating training and development opportunities for employees to learn data skills. Finally, having executive advocacy and a community that supports and makes data-driven decisions will encourage others to do the same.

Establishing these core capabilities will help encourage data-driven decision making across all job levels so business groups will regularly question and investigate information to discover powerful insights that drive action.

Source: (tableau.com)

The trend toward data-driven decision making

As data becomes more important, organizations are responding to this changing business environment by adding new senior roles such as chief data officer or chief analytics officer to the highest level of their leadership teams.

Shopify has a senior leadership position called senior vice president of data and analytics headed by David Lennie who previously was the senior vice president of analytics at LearnVest and director of data science and engineering at Netflix. These three fast-growing businesses make it clear that having a senior leadership role in data is important.

Source: (blog.capterra.com)

Mastering Data-Driven Decision Making

Data-driven decision making is an essential process for any professional to understand, and it is especially valuable to those in data-oriented roles. For novice data analysts who want to take a more active part in the decision-making process at their organization, it is essential to become familiar with what it means to be data-driven.

If you’re looking to take the next step in your data analytics career, consider earning an advanced degree such as Northeastern University’s

Source: (northeastern.edu)

The importance of data-driven decision making

The amount of information collected has never been greater, but it’s also more complex. This makes it difficult for organizations to manage and analyze their data. In fact, NewVantage Partners recently reported that 98.6 percent of executives indicate that their organization aspires to a data-driven culture, while only 32.4 percent report having success. A 2018 IDC study also noted that organizations have invested trillions of dollars to modernize their business, but 70 percent of these initiatives fail because they prioritized technology investments without building a data culture to support it.

In pursuit to be data-driven, many enterprises are developing three core capabilities : data proficiency, analytics agility, and community. Transforming how your company makes decisions is no easy task, but incorporating data and analytics into decision-making cycles is how you will see the most transformative impact on your organization. This level of transformation requires a dedicated approach to developing and refining your analytics program.

Source: (tableau.com)

What Does It Mean to be “Data-Driven”?

Perhaps one of the most common buzzwords today is “big data.” But what is “big data,” really? The term is generally used to describe the magnitude and complexity of information. Even a small amount of content could be considered “big data” if a large amount of information has been extracted from it.

Source: (northeastern.edu)

And yet, in a recent survey , 58 percent of respondents said that their companies base at least half of their regular business decisions on gut feel or intuition instead of data. (northeastern.edu)

Surprisingly, 80 percent of a data analyst’s time is devoted to cleaning and organizing data, and only 20 percent is spent actually performing analysis. (northeastern.edu)

The Advantages of Data-Driven Decision-Making

Tim Stobierski Author Contributors tag Analytics Business Analytics Business Essentials CORe Decision-Making Society has imbued the concept of “intuition” of simply knowing when something is right or wrong with a tremendous amount of prestige, importance, and influence.

In fact, according to some studies, more than half of Americans rely on their “gut” in order to decide what to believe, even when they are confronted with evidence that speaks to the contrary.

The concept of intuition has become so romanticized in modern life that it’s now a part of how many people talk about and understand the “geniuses” of our generation. In science, for example, Albert Einstein is often quoted as saying, “The intuitive mind is a sacred gift,” and in business, Steve Jobs is quoted as saying, “Have the courage to follow your heart and intuition; they somehow already know what you want to become.” Though intuition can be a helpful tool , it would be a mistake to base all decisions around a mere gut feeling.

While intuition can provide a hunch or spark that starts you down a particular path, it’s through data that you verify, understand, and quantify. According to a survey of more than 1,000 senior executives conducted by PwC, highly data-driven organizations are three times more likely to report significant improvements in decision-making compared to those who rely less on data.

Are you interested in learning how data-driven decision-making can enable you to be a more effective entrepreneur or member of your organization? Below is information about the benefits of becoming more data-driven, as well as a number of steps you can take to become more analytical in your processes.

Source: (online.hbs.edu)

1. You’ll Make More Confident Decisions

Once you begin collecting and analyzing data, you’re likely to find that it’s easier to reach a confident decision about virtually any business challenge, whether you’re deciding to launch or discontinue a product, adjust your marketing message, branch into a new market, or something else entirely.

Data performs multiple roles. On the one hand, it serves to benchmark what currently exists, which allows you to better understand the impact that any decision you make will have on your business.

Beyond this, data is logical and concrete in a way that gut instinct and intuition simply aren’t. By removing the subjective elements from your business decisions, you can instill confidence in yourself and your company as a whole. This confidence allows your organization to commit fully to a particular vision or strategy without being overly concerned that the wrong decision has been made.

Just because a decision is based on data doesn’t mean it will always be correct. While the data might show a particular pattern or suggest a certain outcome, if the data collection process or interpretation is flawed, then any decision based on the data would be inaccurate. This is why the impact of every business decision should be regularly measured and monitored.

3 Examples of Business Analytics in Action

Source: (online.hbs.edu)

2. You’ll Become More Proactive

When you first implement a data-driven decision-making process, it’s likely to be reactionary in nature. The data tells a story, which you and your organization must then react to.

While this is valuable in its own right, it’s not the only role that data and analysis can play within your business. Given enough practice and the right types and quantities of data, it’s possible to leverage it in a more proactive way for example, by identifying business opportunities before your competition does, or by detecting threats before they grow too serious.

Source: (online.hbs.edu)

According to a survey of more than 1,000 senior executives conducted by PwC, highly data-driven organizations are three times more likely to report significant improvements in decision-making compared to those who rely less on data. (online.hbs.edu)

According to a recent survey of Fortune 1,000 executives conducted by NewVantage Partners for the Harvard Business Review, these initiatives vary in their rates of success. (online.hbs.edu)

Of the organizations which began projects designed to decrease expenses, more than 49 percent have seen value from their projects. (online.hbs.edu)

What business decisions can I use data for?

Now you know how you can benefit from data-driven decision-making, the next step is to identify how your organization can use data to make decisions for how to grow your business.

For example, you can use data to find out:

Finance : What’s the most cost-effective way to hire new staff, or the cheapest way to promote a new product?

Growth : What activities can you do to prevent churn ? How do you improve customer loyalty?

Are the new features you’re planning likely to impact your business’ goals?

Source: (superoffice.com)

Instinct Over Data: What You Gain from Data-Driven Decisions

Today, the top companies around the world use data to make decisions about their business. The reason they’re leading the way is that they’ve gained a strategic advantage over their rivals simply by shifting their focus to data rather than relying on business acumen alone.

Fewer top-performing companies (40%) than laggards base the majority of their business decisions on gut feel or experience (70%). In other words, more organizations that make data-driven decisions are at the top of their game than businesses whose decisions are driven by instinct.

Here are just some of the things you stand to gain by becoming a data-driven organization:

Remain competitive among forward-thinking companies that do use data to their advantage

Data-driven companies are more customer focused and enjoy a deeper insight into the customer and their journey

Cost-effective — it can be costly to store large volumes of data, especially if you only use it for compliance purposes

Detect new or missed opportunities, helping your company grow and improve regularly

Become more agile and better able to respond to markets

Source: (sisense.com)

Don’t Let Data Lead You Down the Garden Path

It has to be said that the vast amounts of data at your disposal don’t necessarily add up to improvements in the way you do business.

Data is only as valuable as the insights you can draw from it, and with all the information that’s floating about, it’s easy to find yourself being led astray.

The key to drawing real value from it is identifying which data to use. The metrics you use (what you measure, such as page views or conversions) will determine how successful your data-driven decisions are. The ones you should be looking at are areas of the business that are most crucial to its growth.

These are some of the questions you should be asking:

Where did the data come from, and is it truly representative?

If you’ve made assumptions based on the data, would these assumptions still stand under a different set of results?

Would independent variables change the results?

Could you use a different analytical approach?

Source: (sisense.com)

Techopedia explains Data-Driven Decision Making (DDDM)

The idea of data-driven decision making is that decisions should be extrapolated from key data sets that show their projected efficacy and how they might work out. Businesses generally use a wide range of enterprise tools to get this data, and to present it in ways that back up decisions. This is in stark contrast to the way that decision-making had been done throughout the history of commercial enterprise, where before the presence of new complex technologies, individuals often made decisions on the basis of observation or informed guesswork.

These days, if one wants to know how a given product might perform in a market, what a customer might think of a slogan, or where to deploy business resources, decision support software can help. That has led to a much bigger demand for data-driven decision making solutions. TechTarget cites a study from the MIT Center for Digital Business that shows businesses using data-based decision-making were found to have 4 percent higher productivity and 6 percent more profit on average.

In order to serve this booming demand, companies have come out with self-service data analytics products — the idea is that self-service products lead to more egalitarian data collection and transfer. In other words, without self-serve tools, only a skilled data scientist can crunch the numbers and come up with the data supporting decisions, where with decision support tools that are self-serve, executives and others who are further from the IT department can do their own analysis and present their own decisions backed up with the data in question.

Source: (techopedia.com)

TechTarget cites a study from the MIT Center for Digital Business that shows businesses using data-based decision-making were found to have 4 percent higher productivity and 6 percent more profit on average. (techopedia.com)

Often data is subject to human error, such as when poorly paid and unmotivated retail clerks perform inventory checks. However, even when the data collection process is automated, there are significant sources of error, such as intermittent power outages in cellphone towers or mistakes in the clearing process for financial transactions. (hbr.org)

Data that is of poor quality or used in the wrong context can be worse than no data at all. In fact, one study found that 65% of a retailer’s inventory data was inaccurate. Another concern, which has become increasingly important since the EU passed stringent GDPR data standards is whether there was proper consent when the data was collected. (hbr.org)

So don’t just assume the data you have is accurate and of good quality. You have to ask where it was sourced from and how it’s been maintained. Increasingly, we need to audit our data transactions with as much care as we do our financial transactions. (hbr.org)

Gartner analyst Nick Heudecker‏ has estimated that as many as 85% of big data projects fail A big part of the problem is that numbers that show up on a computer screen take on a special air of authority. (hbr.org)

The trend toward data-driven decision making

As data becomes more important, organizations are responding to this changing business environment by adding new senior roles such as chief data officer or chief analytics officer to the highest level of their leadership teams.

Shopify has a senior leadership position called senior vice president of data and analytics headed by David Lennie who previously was the senior vice president of analytics at LearnVest and director of data science and engineering at Netflix. These three fast-growing businesses make it clear that having a senior leadership role in data is important.

Source: (blog.capterra.com)

1. Start from the top with data-driven leadership

Start with the obvious: leaders must lead by example. Today’s top managers are sharing insights with their teams and using data to help tell their story.

In the absence of a data-driven leadership team, decisions are often based on the HiPPO “ highest paid person’s opinion .” This is absolutely the antithesis of data-driven culture. We all recognize them when they start talking about their X number of years/decades of experience and start sharing how they used to do things at company Y. While that experience is valuable, it must be combined with current data in order to make good decisions.

This really hit home in a Financial Times article:

HiPPOs can be deadly for businesses, because they base their decisions on ill-understood metrics at best, or on pure guesswork. With no intelligent tools to derive meaning from the full spectrum of customer interactions and evaluate the how, when, where and why behind actions, the HiPPO approach can be crippling for businesses.

Great leaders foster an environment for hypothesis making and testing. This type of culture is the foundation for growth. The use of a simple A/B test or an experiment to share insights will start to drive the right behaviors throughout the organization.

Also, as a leader, don’t forget to celebrate both failures and successes. According to the Harvard Business Review, over 80 to 90% of experiments fail . These failed experiments should be considered learning opportunities that will help shape future key hypotheses.

Source: (blog.capterra.com)

According to the Harvard Business Review, over 80 to 90% of experiments fail . (blog.capterra.com)

According to MIT Sloan Management Review, 40% of the companies they surveyed struggled to find and retain data analytics talent . (blog.capterra.com)

Determine Business Questions or Issues

What does the company want to accomplish? Identify the areas most important to achieving its overall strategy. Is the company trying to assess an opportunity or diagnose a problem?

Source: (onlinemasters.ohio.edu)

Strategize and Identify Goals

Determine what you can realistically accomplish with data. It’s essential to have a clear analytical objective. Who will oversee the collection and analysis? What personnel will you need for the project? Can in-house employees do the analysis, or will you hire consultants?

Source: (onlinemasters.ohio.edu)

‘Ability to harness data without negating human intelligence to provide winning edge in use of AI’ — ETCIO.com (cio.economictimes.indiatimes.com)

Summary:

  • Speaking at a RAISE 2020 event, IBM India and South Asia Managing Director Sandip Patel said the world is at a critical inflection point and there will be use of AI at scale, given the extreme digital acceleration seen amid the COVID-19 pandemic.
  • “So, the important element and challenge is to harness the data, curate it and put it in context of enabling faster decision making .
  • Manish Gupta has been appointed as the Group CIO of the conglomerate.