Dr Corine van Erkom Schurink, Analytics Team Lead at PBT Group
In today’s digital environment, organisations must combine both structured and unstructured data and extract meaningful insights from it, which implies costly infrastructure and cutting-edge know-how. This has resulted in the emergence of insights-as-a-service that provides decision-makers with a platform to leverage data for competitive advantage.
Underpinning this approach is the need for an effective analytics programme. Unfortunately, few organisations have a clear vision of what this should entail. And, given the pressure to continually evolve to keep pace with change, organisations are turning to on-demand outsourcing for either their entire analytics function or parts of it. Going this route enables organisations to scale according to the associated demand within the organisation. It also means they can remain focused on meeting their strategic objectives while the service provider takes care of the analytical components.
Combining this outsourced approach with an insights-as-a-service model, sees the service provider preparing the organisational data for analysis, building and tweaking machine-learning models, and delivering valuable insights back to the organisation. Even though these insights might still be in a raw format, organisations can use them to tell a story through visualisations. Based on this, they will get clarity on how to shape their priorities.
Some might question the merits of giving external partners access to mission-critical data. In a perfect world, every organisation will employ at least one data scientist and analyst. The reality is that these skills are still very niche. And in South Africa where data science is still a burgeoning field, they are virtually impossible to get and retain.
Any decision-maker who has attempted to generate insights from data understands how difficult it is. Data scientists and analysts rely on several skills that can combine everything from economics, science, mathematics to technology, market analysis, and business acumen. To resource an end-to-end analytics capability, companies have to employ several data scientists, each holding a piece of the complex and varied expertise required.
Using an outsourced insights-as-a-service provider means the organisation has access to a comprehensive solution that combines all these elements. Not only is this more cost-effective, but it significantly speeds up the entire process.
Looking beyond the skills challenge, another stumbling block to implementing an effective in-house analytics programme is overcoming the gap that exists between the IT department and the organisation users.
Far too often, analytics gets positioned as a technology solution. Yet, it is something that must be owned by the organisation with the support of senior management – including at board level. In this instance, IT is used as an enabler.
Organisations must also have an intrinsic understanding of their needs, vision and roadmap, as well as of their present maturity level and the type of analytics they require. These can include anything from descriptive reporting, predictive models, prescriptive recommendations, or semantic analysis.
Even with all of this completed, the organisation must still have clarity on how it will use these insights and turn them into action points for a return on investment (ROI).
Insights-as-a-service has the potential to significantly change the business landscape. However, there needs to be a willingness to embrace a different way of using and analysing back-end data. Still, the competitive advantage this will provide, could make it an essential business tool.