The same survey data is used in a great piece of McKinsey analysis – Breaking away: The secrets to scaling analytics
“Senior executives tell [McKinsey] that their companies are struggling to capture real value. The reason: while they’re eking out small gains from a few use cases, they’re failing to embed analytics into all areas of the organization.”
The McKinsey team identify three key challenges to be overcome to help capture the full potential of advanced analytics :
- Aligning on strategy
- Building the right foundations of data, technologies, and people
- Conquering the last mile by embedding analytics into decision making and processes
You should read the whole article – it’s full of good advice – but I want to draw your attention to some specific ways in which decision management and our DecisionsFirst approach can help you break away as McKinsey describe:
When it comes to Aligning on strategy, one of the key ways in which breakaway companies are different is that they have increased analytic investment with a focus on the last mile.
“Most important, breakaway companies target much of this spending toward the biggest challenge companies face in extracting value from analytics—the last mile, or embedding analytics into the core of all workflows and decision-making processes (more on this later). Nearly 90 percent of breakaway organizations devote more than half of their analytics budgets to this effort, versus only 23 percent of all other organizations that do so.”
See that? Breakaway companies spend nearly half their budget not on building the analytics they need, but on making sure those analytics get into the front line. Decision management is the best way to embed advanced analytics into your front-line systems and processes. Building decision services that encapsulate not just your analytic insight but the business rules and decision structure that turn predictions in recommendations and actions is a proven way to push analytics out into your organization.
Moving on to Building the right foundations of data, technologies, and people, I was struck by the fact that breakaway analytics leaders were 2.5x more likely to have a clear methodology! And in particular that “companies with leading analytics programs not only focus on model development through their methodologies but also work to continuously maintain and upgrade models as part of a sophisticated model-management function”. Our DecisionsFirst methodology, which we use on all our projects and license to our customers, explicitly includes decision analysis and continuous improvement in every solution. Not only thinking about analytic model management, but putting that model management into a context of decision performance management so you can improve your decision making and your business results.
Finally, the big one: Conquering the last mile by embedding analytics into decision making and processes. We have seen again and again that if you don’t complete the last mile, analytics investments can go to waste. We believe that companies should begin by identifying the decisions that make a difference to their business and then figure out how to use analytics to improve them. And McKinsey’s analysis supports this approach. In fact,
“Breakaway companies are almost twice as likely to have identified and prioritized the top ten to 15 decision-making processes in which to embed analytics.”
This is the first step in our DecisionsFirst approach – what we call “decisions first design thinking” – where we identify the critical decisions and develop a model of how the company would like to make that decision. This frames the requirements for analytics, ensuring that you build the right analytic models, know how you will use those analytics, and will be ready to get them into the last mile.
This is the final, critical recommendation from McKinsey as it is from me – begin with the decision in mind and put DecisionsFirst:
“Most companies start their analytics journey with data; they determine what they have and figure out where it can be applied. Almost by definition, that approach will limit analytics’ impact. To achieve analytics at scale, companies should work in the opposite direction. They should start by identifying the decision-making processes they could improve to generate additional value in the context of the company’s business strategy and then work backward to determine what type of data insights are required to influence these decisions and how the company can supply them. In other words, the last mile should be the starting point of the analytics journey.”