Recently, I have been obsessively listening to books about AI, Machine Learning, and Data Analytics with an eye toward how it can be applied in marketing and demand management. It's easy to imagine the power of AI systems that take in all manner of data across the business: recent sales and traffic trends, guest satisfaction data, staffing, management turnover, digital advertising, and cell phone tracking as well as external data like weather or macroeconomic conditions. Machine learning algorithms can hunt down patterns that not only help to describe and diagnose issues but also predict future performance and prescribe the best action.
This capability will be an incredible leap forward. And, it is not science fiction. It is all doable today with existing capabilities which will only get better over time. So why aren’t we all doing it yet? The answer lies in “us” not “the technology.” We aren’t ready. Many businesses do not yet have the people, capabilities, data integration or mindset needed to leverage the new technology.
Organizations are going to have to move along multiple maturity curves in order to be ready for this inevitable transformation across the competitive landscape. Here are three key areas that most organizations will need to focus on.
Maturity Curve 1. People
It is not enough to just hire a bunch of data scientists and let them loose. There will be a need from data wranglers - who manage the data, programmers - who build models, visualizers - who can transform data into meaningful business information, and explainers - who can translate from charts into narratives. All of these roles will need to be managed by someone who has a deep business understanding in order to match the data in the right form at the right time to make the right decisions.
Key Question: Do we have the breadth of capabilities in our current workforce or do we need to hire/develop new skills for roles that do not yet exist in the organization?
Maturity Curve 2. Infrastructure
Having a bunch of data is only useful if systems across the business can appropriately talk to each other. Advances in infrastructure that already exist today will make this data integration possible: cloud storage and computing, data management/analytical tools and visualization software will all work together to enable previously impossible learning from increasingly massive, constantly growing data sets. This will only work if the data and systems are set up for a higher level of access and integration than ever required in the past. The “don’t fix it until it’s broken” mentality of putting off infrastructure updates will not suffice in the coming years. Companies that see past infrastructure that “still seems to be working” and build for integration and flexibility will accelerate. Those that do not will end up trying, and quite possibly failing, to catch up.
Key Question: Does our data infrastructure support the speed and agility needed for machine learning?
Maturity Curve 3. Decision Making Processes & Mindset
It isn’t just the people and the technology that will need to change. The whole mindset of the organization needs to be updated. Most decision making today is built around the past: Descriptive Analytics which are all about understanding “what happened?” complemented with Diagnostic Analytics that seek to understand “Why it happened?” The future state will also include Predictive Analytics - “What is going to happen next?” - and Prescriptive Analytics - “What should we do about it?”
Unfortunately, you can’t just skip past the first two on the path to the others. Companies that don’t have their Descriptive and Diagnostic ducks in a row need to make sure that those processes are on a solid footing. Incomprehensible data dumps that force busy decision makers to weed through mountains of unhelpful data to find nuggets of wisdom will no longer work (and never really did.) At the same time, the coming transformation is not going to just turn the keys over to the AI and let it tell us what to do. Business leaders will need to guide the business to avoid the many possible paths that may lead to short term success but won’t meet long term strategic goals.
Key Question: Are there clear processes for business assessment that ensure that the right people have the right information, and only the right information, at the right time to make the right decisions?
What is clear is that the coming transformation is going to bring major changes to the way we conduct and think about business. Getting ready for the changes across all these areas needs to be a top priority.
