Pyramid 2019 “Year in Review” - Pyramid Analytics

As we transition to 2020, it's important to reflect on an incredible year in analytics and data. Analytics and data topics dominated the business world, with organizations across industries striving to stay ahead of the ongoing digital transformation. According to research, 94% of enterprises say data and analytics are vital to their business growth and transformation.

Data and analytics are key to driving innovation, but executing an effective strategy requires both traditional analytics (data extraction, cleansing, blending, modeling, dashboards, and reports) and advanced analytics (machine learning, AI, augmented analytics, etc.).

In conversations with analysts, partners, prospects, and customers over the last year, two key challenges emerged:

1. 1.How can organizations scale traditional analytics capabilities within their organizations?
2. 2.How can organizations implement and operationalize advanced analytics capabilities within everyday business scenarios?

For both, analytics culture is a key component.

Challenge 1: How can we scale traditional analytics?

Many companies have hired a chief data officer, established a data strategy, and selected a BI platform. However, organizations often struggle to implement analytics across the last mile of the implementation—when data has been piped in, modeled, and transformed into visualizations or dashboards. This is the point where decisions can be made, but the process must be iterative and involve participants from across the business to truly scale.

Scaling analytics is difficult, often due to cultural issues. According to NewVantage Partners’ annual Big Data and AI Executive Survey 2019, while 48% of respondents said their organization competes on data and analytics, only 31% had a “data-driven organization,” and just 28% possessed a true “data culture.”

Collaboration often suffers because data is siloed. "Data fiefdoms"—where data is trapped at the individual or departmental level—are common, and users may have access to multiple, sometimes competing, analytics tools. This internal friction makes scaling difficult.

Successful organizations establish solid data governance protocols, promote data stewardship, collaborate across departments using shared tools, focus on analytics training and literacy, and set transparent KPIs and targets. Analytics tools must focus on user experience to encourage collaboration and scale analytics culture.

Enthusiasm and collaboration are crucial, though often overlooked. Until BI platforms focus on user experience for all users, organizations will continue to struggle to scale analytics.

Challenge 2: How can we operationalize AI/ML/augmented analytics?

Integrating advanced analytics into everyday business practices is another key challenge. Companies that compete and win on analytics innovate more quickly than their competitors. Innovation now requires incorporating advanced data analytics technologies—such as machine learning, AI, and augmented analytics—into regular business operations.

These techniques are often difficult to implement and scale in traditional production environments. Success requires more than just investing in ML and AI initiatives; it requires strategic direction and a roadmap that builds consistency and accountability.

According to Spiceworks, business adoption of AI technology is expected to nearly triple. However, many organizations struggle to gain traction. A VentureBeat article cited a failure rate of 87% for advanced analytics projects, with 77% of respondents saying business adoption of AI initiatives is a challenge.

Advice on operationalizing advanced analytics is abundant. Chris Brahm of Bain’s global Advanced Analytics practice emphasizes aligning investments with strategic and organizational needs and designing analytics with the last mile of adoption in mind. The best solutions emerge when data scientists and business stakeholders work together, set success requirements early, and keep end users central to decisions.

AI and ML initiatives require more than tools, people, and processes—they require a collaborative culture. Collaboration between data scientists and citizen data scientists is a net positive, increasing the pool of analytics-minded professionals and advancing an analytics mindset.

For this collaborative mindset to flourish, the right technology investments are essential. Today, there are fewer barriers to accessing advanced analytics toolsets, and the most favorable path for adoption is one where the greatest number of people are confident using their platforms. At Pyramid, the goal is to create a codeless experience where any user can perform advanced analytic techniques and make better decisions with data.

Pyramid in 2019

In 2019, organizations struggled to implement and scale traditional and advanced analytic technologies, amid significant market consolidation in the business intelligence space. The acquisition of Tableau by Salesforce and Looker by Google introduced uncertainty into organizations’ strategic analytics and data initiatives.

Despite the tumult in the BI market, Pyramid focused on developing customer-focused analytics software. In October, Pyramid launched Pyramid v2020, introducing over 150 new enterprise-grade features and capabilities to improve data-driven decision-making. The focus was on creating an adaptive analytics application centered on customer experience.

Pyramid also worked to build relationships with partners, vendors, customers, and prospects globally, attending events and hosting its first-ever user conference, ANALYTICON, outside of London. The enthusiasm and energy from the event reinforced Pyramid's commitment to being a go-to analytics resource.

What’s next in 2020?

Pyramid is more committed than ever to its customers. In 2020, the company plans to exhibit at global events, produce educational webinars, and host user conferences and training workshops across multiple continents. The product roadmap will continue to put customers at the center of everything Pyramid does.

Pyramid recognizes that organizations have many choices in the crowded BI market and that user experience is a key differentiator. The company is dedicated to providing the best user experience possible for customers and partners in 2020 and beyond.

That's the singular focus, with many exciting plans ahead for 2020.