By Donald Farmer, Principal at Treehive Strategy
Having worked in the data and analytics space for over 30 years, people expect me to hold strong and informed opinions about the next big thing. I do. But, before we look to what comes next, let’s reflect on where we find ourselves today. In this field, things are pretty good.
For example, if you use BI tools, I expect you know how to build a dashboard. With new self-service features, that’s a simple task. You can probably track KPIs, visualise your trends and deploy these insights to the cloud or a mobile device. If you need to bring data together, that’s not too difficult either. But you have a ton of data? No real problem, with today’s elastic technologies.
The more challenging question is: do you make a difference? When tools and skills are commonplace, when once-insightful metrics and reports are familiar in every business, what can you do better?
This anxiety lurks behind so many conversations I have. People ask, what comes next? But they really wonder, how do we add value as a team, when BI is just a commodity? How can I – personally – lead and influence when so much that was once difficult now seems easy?
The problem often lies in the very familiarity of our tools: we quickly hit their limits. Perhaps we can go further with coding and scripting, but BI has succeeded mainly because it has reached out to business users not developers.
We may hand over advanced problems to a data science team; in-house if we have the resources. But data science is a highly competitive profession just now. So, we often outsource, even off-shore our next-generation requirements.
Outsourcing may tempt us economically, but rarely proves efficient in a practice such as machine learning where progress comes through many experimental iterations. We discover the pain points too late; nothing feels straightforward; integration is difficult and results come slowly.
What is to be done? First, we need to work with our current BI users, not new teams, enabling these colleagues to extend their skills beyond the limits of the current toolset. In other words, we do need machine learning and AI, but for most businesses we also need those new techniques to work within our existing analytic practice, improving our current decision-making with new intelligence.
This possibly sounds like the augmented analytics which BI vendors have plugged-in over recent years. However, that approach is inherently limited by their need to support expected legacy features. Other, newer, BI vendors want to replace existing BI capabilities with augmented or automated approaches. But they too hit limits, because, ironically, before they can take you further, they must address those already familiar use cases, mastered by traditional BI.
What few of these vendors recognise – or want to admit – is that modern business builds on a portfolio of tools. No one application needs to, or should try to, do it all. We should balance the power of machine learning with simplicity. That’s not to say applications should be superficially easy. Rather, applications that take business users on this new journey, should focus on their advanced capabilities, but with a workflow that clarifies, rather than over-simplifies.
Above all, the business user must feel they can iterate and increment, to answer their questions and question their answers, again and again. This is what a data scientist would do with their specialised tools, scripts and notebooks. The BI user, stepping into more advanced work, should have their own practice that matches their needs and experiences.
This attention to working practice is one reason I like the Tellius decision intelligence platform. The user experience feels neither over-simplified or daunting; the on-boarding is similarly straightforward. Results, therefore, come quickly. But, remembering that all machine learning is incremental, better results come confidently.
It’s invigorating – cool, even – to reach beyond the limits of augmented analytics into a new space we could call decision intelligence. The down-to-earth benefit is that you use a remarkably straightforward deployment and a set of tools to complement, rather than disrupt, your existing practice.
Worth looking at.
Donald Farmer
If you are interested in learning how to break out beyond BI, I invite you to the next Tellius webinar on Wednesday July 14, 2021. I look forward to seeing you there.
Written by: admin,
at Tellius
