International Institute for Analytics

Inquiry:

As part of our strategy for BI and self-service, we’re planning an enterprise-wide Tableau rollout to 2500 users initially. What are best practices we should be aware of to ensure and measure success?

Organizations today face an increasingly challenging business environment. Across industries, new companies and nimble competitors are taking advantage of analytics and leveraging the full potential of the internet, disrupting traditional business models and markets.

Cloud computing and open source have caused fundamental changes in analytics infrastructure, enabling the introduction of new technologies such as artificial intelligence and machine learning. The most nimble, innovative companies have quickly taken advantage of these new technologies — and the analytics they enable — to gain a competitive advantage.

Traditional companies are struggling to deal with this complexity and effectively compete on analytics. Though many top executives realize that high-quality data, analytics and AI are critical to the future success of their companies, up to 70 percent of analytics initiatives and projects fail to meet their objectives.

Since the dawn of Wall Street, investors have sought an edge: an advantage they can leverage to beat the market. Gaining some type of edge is the only way to win in the brutally competitive, zero-sum game of capital markets.

Today, that edge can come from insights gleaned from information found in the exabytes of data created in the real world — on websites, from smartphones and sensors, through supply chains, and from countless other types of real-world data. Collectively, these sources of unstructured and large nontraditional data are called “alternative data.”

Inquiry:

We’re just getting started with HR analytics, and we’re struggling with building a baseline reporting capability. There is an HRIS team; should HRIS own the analytics? Where should we start with our initial HR analytics projects? We use Workday for human capital management; can we use it for analytics too?

Inquiry:

I’m rebuilding my analytics teams after layoffs. Going forward, I would like a documentation process in place to retain knowledge in case of future resource talent loss. What should my priorities be?

The life expectancy of large companies is declining more quickly today than ever. The leading reason for this diminished lifespan is in their persistence to combat challenges that do not alter the company’s success or failure — they are tilting at windmills in a way not too dissimilar to Don Quixote fighting imaginary giants. An incredible amount of resource can be wasted fighting the wrong problem; instead, I propose that large companies methodically chase innovation and move to new business models to survive and succeed.

We co-founded the International Institute for Analytics in 2010. Since it’s now 2020, our sophisticated math skills tell us that IIA has been around for about a decade—although our first full year of operation was in 2011. We thought it might be interesting to reflect on the state of the field that IIA addresses and how it has changed over time.

Inquiry:

We’re a consumer products multinational, and we need to expand our supply chain analytics efforts. What should we be thinking about?

Response:

Each year, the International Institute for Analytics ends the year with a look at the latest analytics trends and the most pressing analytics challenges currently facing organizations. Our predictions are based upon our day-to-day work supporting and advising analytics leaders and organizations. We take advantage of the breadth of expertise and cross-industry perspectives we encounter every day from our clients, partners, and members of the IIA expert network. This is our 10th annual look toward the upcoming year, and our annual Predictions and Priority research brief and the associated webinar have become among IIA’s most popular content of the year. This year, we’ve stuck with our approach of augmenting each of our predictions with a specific priority for leaders to focus on as they attempt to address that prediction. As a result, each priority provides specific guidance as to how to best prepare for, and adapt to, its corresponding prediction.

Open-source software (OSS) is inevitable. For most corporations it’s not a question of “will we use OSS?” The right question is “how much OSS do we already have in production?” More than 90% of IT organizations have OSS in their mission-critical systems. Many commercial software products — from vendors such as IBM and Microsoft — also contain open source software.
Herein we explore these major OSS subjects:

1. OSS history and concepts
2. Quick tour of OSS analytics
3. What does OSS really cost?
4. Positives and negatives of OSS analytics
5. Guidance