Creating a Data-Driven Organization in the Era of AI

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Creating a Data-Driven Organization in the Era of AI

Transcript Of Creating a Data-Driven Organization in the Era of AI

Creating a Data-Driven Organization in the Era of AI


For years, organizations have strived to be data-driven. This eBook explains the opportunities and strategies to overcome challenges with creating a data-driven organization in the current era of AI-driven business intelligence and analytics.

Table of Contents

The Opportunity in Becoming Data-Driven


1. Foster Inquisitiveness


2. Focus on Data Quality


3. Break Down Data Silos


4. Deploy Augmented Analytics


5. Expand Self-Service Analytics to New Heights 18

6. Level Up the Workforce


7. Accelerate Small Wins and Scale


8. Defeat Data Bias


9. Build Trust and Transparency in AI


10. Evolve Your Analytics Center of Excellence


The Final Word


The Opportunity in Becoming Data-Driven

Why be data-driven?
“Highly data-driven organizations are 3X more likely to report significant improvement in decision-making.”
A data-driven company is an enterprise that cultivates the culture of continually using data and business intelligence to make all decisions. All the departments and employees in the company would have access to the data and insights to improve decision making, where the company would encourage everyone to embrace, explore, and examine data in their day-to-day business activities.
The goal of the data-driven organizations should be to reach a stage where the company requires approaching each decision by analyzing relevant data, and the usage of data becomes a natural part of the workflow of all the employees and departments.
A data-driven culture can take the guesswork out of building new products and services. It improves situational awareness and drives performance at individual, team, and department level. It can uncover the right audience, drive down expenses and gives you an edge in even the most competitive of environments.
In short, a culture of being data-driven provides a full 360-degree view of people, processes, technology, and governance.
Creating a Data-Driven Organization in the Era of AI

“Data-driven” organizations are 23 times more likely to acquire new customers, six times more likely to retain them and 19 times more likely to be highly profitable.
- McKinsey & Company

Of the Fortune 1,000 companies that use big data, the majority employ it (and see value in its ability) to decrease expenses.
- Harvard Business Review

20% - 30%
Data-driven organizations are seeing upwards of 20%
to 30% improvements in EBITDA due to unlocked
efficiencies and more granular financial insight.

76% of executives from topperforming organizations cited
data collection as essential, compared with only 42% from companies that fall behind their
peers in performance.
- The Economist



The Rise of AI
We are in the midst of hyper technology change when it comes data, automation, and AI, putting BI and analytics at yet another inflection point.
By 2020, 1.7 megabytes of data will be created every second, for every person on earth. - IDC
Data is being generated and collected at a rate we have never before seen. From IOT, mobile, and personal devices, and even in the enterprise, with every department seemingly having use for data coming from multiple business applications as well as external sources, the movement we used called “big data” several years ago is simply a reality for all businesses.

About three out of five people in leadership roles say a failure to get on board with big
data could lead to obsolescence.
- CIO Insight

Automation and AI has successfully invaded the home – through smart devices such as Alexa, Google Home, and Siri, that that you can talk to, automation that continuously connects to you to your home such as Nest and Arlo, and intelligent applications such as Amazon and Netflix that anticipate your needs, acting upon, and serving recommendations that you did not explicitly ask for.
Not to be outdone, we are in the midst of what industry analysts have called the third wave of BI, one of augmented analytics and machinedriven intelligence. This generation—which follows on the heels of ad hoc reporting (first generation) and self-service analytics (second generation)—promises to greatly simplify the use of analytics and hence rapidly increase levels of adoption, insight, and fact-driven behavior.

Creating a Data-Driven Organization in the Era of AI



Challenges to becoming data-driven


“40% of the insight delivered by customer intelligence teams are not actionable.”
- Forrester

The benefits of AI-driven business intelligence can only be fully realized if organizations recognize and tackle the challenges in their path to becoming data-driven.

Limited access to data
Data is often locked away in silos or protected by individual departments. This is the antithesis to what a data-driven organization should be – which is entirely open and collaborative. Employees shouldn’t be concerned about gatekeepers to data – there must be a move towards working together – department with department.
Over-reliance on data specialists
Some organizations heavily rely on analysts, who in turn, are drowning in a sea of report requests that are backlogged – causing delays to what could be time-critical decisions.
A deepening talent crisis
Data scientists are in high demand, but are in short supply data science skills shortages are present in almost every large U.S. city - McKinsey.
Low adoption of BI
There remains a lowly 20% adoption of self-service tools – behind which is a perception that these tools are difficult to use, and that they lack enough depth for many users.
A prevalent cultural bias
In some organizations, business leaders, managers, and employees alike have, for years, endured in their position by leaning on their experience and relying on intuition. The shift from intuition to being data-led can seem like a monumental task. There can be data trepidation at best, and mistrust at worst.
Black box AI
Misunderstandings around how AI works leads to widespread mistrust of algorithms. Compounding this issue is the lack of transparency and explainability that users face when they seek to understand recommended business decisions that are automatically generated.

Creating a Data-Driven Organization in the Era of AI



The opportunity
The huge leaps and bounds that can be made by AI revolve around one simple, fundamental strength of AI – it can bridge the previously vast gap between the data and insights, with those who need to understand it.
Users can analyze more data, faster – speeding up discovery of insights and, consequently, the business decisions made from those insights.
Data democratization can take hold, whereby anyone can ask questions in natural language – where once they would have had to deal with cumbersome reports and clunky processes. Findings can be presented automatically (no longer will monthly meetings be based on out-of-date (and often irrelevant) data.
AI-driven BI platforms go hand-in-hand with flourishing data literacy, and users who become increasingly adept at consuming data through natural language generation.

In this eBook, we explore the ten steps towards advancing a data-driven organization through their analytics journey. Along the way, we’ll be sharing forward-facing insight into how AI-driven analytics could and should help you create a deep-seated data-driven culture.

Creating a Data-Driven Organization in the Era of AI



1. Foster Inquisitiveness

The data-driven organization thrives on people asking questions and exploring new ways for sometimes age-old processes and problems. This culture needs to be not only top-down, but also bottom-up, so it’s not just execs demanding data, but also individual contributors asking about performance in order to determine ways to improve. It’s imperative that objectivity is corporation-wide. Everyone must move beyond asking only the questions that they know, or expect to know, the answer to. It’s a human infliction to be biased (and sound correct all the time), which leads to people seeking out the data that will support what they expect to be the correct conclusion.
Inquisitiveness The hallmark of a data-driven
Creating a Data-Driven Organization in the Era of AI

“The important thing is to not stop questioning. Curiosity has its own reason for existing.”
- Albert Einstein

Humans are naturally inquisitive. The very first online search engine launched in 1990, and it was positively archaic, but it was in such demand that it couldn’t be used during the day. Few could have predicted just how many questions people wanted answers to. Fast forward to today, and we now live in a time of 40,000 Google search queries every single second.
Analytics leaders are taking active steps to support their organizational inquisitiveness.
It’s no longer acceptable that a meaningful, relevant question is met with the response of:
“Don’t ask that question.” “We don’t have the data.” “That’d be impossible to figure out.”
The Need for BI Search
In the age of AI, leaders must now wholeheartedly embrace newer and easier ways for people to interact with data. They must create the foundation for inquisitiveness. By adopting BI search combined with natural language query, everyone can tap into a Google-like search experience – receiving equally fast answers and data visualizations far easier than in generations past. AIdriven BI smashes through the barrier that previously stood in the way of understanding data to get the answers people seek.