Prodago helps C-level executives and their teams design and deploy effective, operational, adaptive and dependable Data and Analytics Governance programs. This is the backstory.
Mario Cantin has been involved in data management for 30 years, elaborating solutions from data warehouses to data governance strategies, in roles ranging from developer, project manager and strategic advisor. Twelve years ago, he was consulting for the National Bank of Canada, one of Canada's major banks, and he realized that while data governance as a discipline held honourable objectives, something was missing to bridge the theory with real business impact. Organizations had a lot of frameworks and solutions to choose from, but it seemed that the only tangible deliverable these data governance efforts were producing were business glossaries. We had definitions, but the lineage to data quality, trust and business results were still elusive.
So seven years ago, Mario decided to launch Prodago. The premise was to be two-fold. First, he was going to disrupt the traditional, top-down data governance approach involving committees, glossaries, stewards and the likes and start where requirements are typically recorded - at the project level. What came from it was something called lean data governance. The concept was to start from the data itself, and further dig into what else was required for it to be trusted. If some data quality procedures were not applied consistently, what was the business value at risk? This lean data governance framework allowed any data-centric project to clarify and connect with real, specific and actionable governance requirements and be agile at doing so. Of course, Prodago is also a software company, but Mario who has been thinking about this longer than most, says that the real innovation of Prodago is this framework, his brainchild. The software only operationalizes the framework.
Maybe Mario is being modest. Three years ago already, Gartner named Prodago one of its yearly COOL VENDORS. Enabling data projects to document all the connections between data, procedures, target regulations or policies is a considerable addition of value, to be sure. The documentation remains live as it can also connect to external tools (data profiling, glossaries, catalogues, etc.) and permits incremental definition over time, agile-style. Prodago is more than a documentation tool, however. Not only does it bridge the link between policies and the data itself, but it also generates reports about risk, about tasks that require completion and helps create a roadmap of how to get there.
Prodago is a SaaS offering. It works on Azure and boasts of a robust security architecture. The organization cares a lot about its clients' success. It has, therefore, invested in growing its consulting division, which not only offers professional services to get a client started but also management consulting to make sure the framework is adapted for the client's context to provide maximum value. Mario gave two examples of recent implementations that speak to the true potential of the platform. The first was a Project Data Governance mandate with a Government department, which began by identifying and documenting all internal regulations, guidelines and directives surrounding data. They then went on to link analytics delivery, the main goal of the project, to the metrics and data management procedures required to comply with the regulations and prove trust. Not only that, they were able to generate a Roadmap and track a task list with responsibility assignments so that they would know at any moment whether data quality, security, ethics, privacy or bias could cause potential risks. Data governance can now be a force for getting things done rather than an annoying compliance roadblock. Deliver data value, which everyone is interested in doing, without accepting risks but having a way to manage them proactively. Another example that Chief Data Officers would appreciate was an AI Readiness Assessment. In this case, Prodago worked with renowned data scientists and AI experts to document not rules and regulations but capabilities, skills, culture, business case identification, data availability, etc. The same way they could link to the compliance of data governance rules and policies, they could map assessment questions to how closely the client fulfilled the capabilities required to be "AI-ready." In the same way, through its professional services, Prodago was able to leverage the software and document risks, priorities and an Actionable Roadmap to become AI-ready. When Prodago Professional Services leave, the client uses to software to track and execute the tasks and then govern to make sure they remain compliant and don't deviate. Mario pointed me to a research article by Saul Judah of Gartner about the 7 Must-Have Foundations for Modern Data and Analytics Governance; Prodago has addressed all seven.
More than Data Governance: Analytics Governance
Project Data Governance and AI Readiness Assessment are two "topics" for which Prodago has already developed accelerators (programmed the set of rules and operating practices). Like all tech entrepreneurs, Mario read Crossing the Chasm by Geoffrey Moore, a classic book about bringing technology products to market, and admits that he feels the platform can be generalized to assess, act to fill the gaps and then govern any topic in this way. Still, he had to choose a domain to prove the technology and value to the market - what Moore calls a "beachhead." He says that this is why his consulting division is so essential to demonstrate success and leave nothing to chance. The area he has chosen is ANALYTICS, because of his vast experience in the domain and, let's face it, how popular it is and how much it intensifies the need for Data Governance in general. In the next 12-18 months, Mario wants Prodago to become the de-facto go-to platform to build Analytics Trust and Data Compliance. He says there is a confirmed need in the market to do this, not just for the topics named above, but any area of organizational transformation for which we can define the target as a set of rules and operating practices. Prodago is working to develop a network of partners who will build new accelerators on the platform, around topics in which they are experts; this is the growth strategy beyond the 18-month mark.
This blog post is the result of an interview with Mario Cantin, CEO of Prodago, a Canadian startup in the modern data management space. Reproduced with permission from Modern Data Analytics. Date: February 19, 2020