Back in 1995 I had the opportunity to have lunch with one of my mentors who was leading Freddie Mac’s digital transformation strategy. Over ice tea, I watched as Eric explained his simple but powerful methodology for moving organizations from little knowledge of digital to full on active engagement.
Back in 1995 I had the opportunity to have lunch with one of my mentors who was leading Freddie Mac’s digital transformation strategy. Over ice tea, I watched as Eric explained his simple but powerful methodology for moving organizations from little knowledge of digital to full on active engagement. I find that methodology as valid today as it was 20 years ago.
So the model is pretty simple. It’s a pyramid with 3 building blocks that sit on a 4th foundational block.
At the base is data. Like strong concrete foundations are to buildings, good data and data management is core to the success of an organization’s digital strategy. That means you must have good data – varied, frequently updated, error free, easily accessible. It also means that data sources are well documented, stored and secured properly.
It’s been my experience that companies with weak data management practices tend to have more project over-runs and are slower to capitalize on market opportunities. It’s because they lack a good data strategy (cloud) that will allow them to quickly pull in, process and analyze new data.
Building off of good data, the second foundational block is Analytics. Back in 1995, analytics was done by coders generating management reports with software like SQL, SAS or Excel. The reports were slow to generate, required multiple reviews for data errors and were logistically difficult to drill down into.
Fast forward to today and products like Tableau, MicroStrategies and PowerBI are providing self-service reporting for non-technical folks. This is only possible because of the existence of quality data management infrastructures AND that people are actively engaged in understanding how the underlying data can be leveraged. Quick, reliable reporting; metrics plus visualization to draw insights; all without a ton of coding. A win for analytics development and having a good data strategy.
So you have great data. your analytics is giving performance insights but you now want to predict behavior, accurately forecast or be notified when processes are at risk of being out of control. Whatever the case, this is where modeling, the 3rd block on the pyramid, comes in.
In finance and banking we’ve been using big data to forecast and in scenario generation for a long time. I was using huge datasets in conjunction with neural nets and early machine learning tools to predict US housing foreclosures back in 1997. However, coding the logic was complex, we constantly struggled to get sufficient data and lacked computing power to develop highly effective models.
With the advent of cloud computing and storage, that all changed. Companies today have the means to develop faster predictive models with a higher degree of accuracy given the resources of the net. Microsoft, IBM, Amazon and Google have developed standardized, modular libraries that engineers can leverage to build their predictive models. Couple that with big data, insight analytics and the speed of cloud compute services and companies have powerful capabilities to do everything from predicting what brand of coffee a consumer will likely buy next to when a plane’s tire assembly needs to be replaced.
Models are the keys to unlocking effective decision making – the cap stone of the digital transformation pyramid. Traditionally, leaders spent a fair amount of time identifying/monitoring KPI’s, drawing insights from the analytics and forecasting what might occur over the next few cycles. If they didn’t have all of that, they could spend their time on high-value tasks such as driving strategy and seeking out new business.
In today’s digital transformation world, understanding the underlying data, analytics and forecasting is important, however what leaders really want is to integrate those activities into their decision making processes. For instance, we’ve all heard of automated Wall Street trading platforms. These algorithmic systems allow traders to establish specific rules and to automatically buy/sell stocks when certain conditions have been met. The pro of such tools is the disciplined trading approach and ability to back test – two things that are highly valued as they remove human emotion from the trading equation (albeit there are risks such as the potential for a bad model being implemented and losing the firm millions of dollars).
‘Tools’ integrated with Artificial intelligence and machine learning today allow leaders to delegate decision making tasks down into their business units. Unit leaders are using modeling such as robotic process automation or RPA to make their teams more efficient and the teams themselves are using data, analysis and modeling to make better products, services and consumer experiences.
Some Take Away Thoughts:
There are lots of moving parts in being digitally savvy. One suggestion I have is as you listen to your leaders talk about digital transformation, you ask yourself: Are we developing the tools that make us more nimble and savvy in these 4 digital areas? Are we we taking a bottom up approach by focusing first on quality data, then understanding it, modeling it and then building decision management tools to support driving our P&L? My point here is to avoid the excited of bringing in technology like artificial intelligence when you’re not even close to being prepared. If you don’t have a good balanced foundational approach, the chances of systemic failure are astronomical.
So with that, I’m currently recommending both start-up and legacy companies assess their digital strategies on these 4 building blocks and set up a balanced development program to include funding in proportion to the importance of data, analytics, modeling and management decision tools. You don’t have to ignore decision tools until you have your other foundations set, you just have to be mindful of what is feasible with what you have.
~Most days you can catch me helping people find great solutions to transform their lives and businesses for the better.
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