Problem: fragmented data
First up, the problem itself. The company manufactures and sells industrial machinery. This particular data problem was born once an item (i.e. a machine) left the assembly line. At this point, the machine is given a supposedly unique identification number. This kind of number is often referred to as a serial number. The problem was that machines were manufactured in many factories across the globe. Many of the factories had been acquired over the years, and no long-term strategy had existed to align systems, processes and data.
This meant a couple of things. First, the way serial numbers were generated looked very different between different factories, which also meant that it was, in principle, hard to guarantee that it was unique. Second, there existed no central database of serial numbers, which meant that any attempt to use serial numbers globally was impossible. The essence of the problem is fragmented and inconsistent data, brought on by a siloed organization and a fragmented system landscape.
Solution: empowering people
So, what would a solution have looked like? There are probably several ways to tackle it in terms of IT systems. Maybe some master data hub that collects, cleans and disseminates serial numbers through an API for others to use. What I want to focus on here is business ownership. Regardless of the IT solution, the business must define, own and maintain its processes and its data entities. And the trick to bridging the silo-effect is to appoint and empower people to take on that responsibility outside the allegiance to one of the silos.
People who understand the current and future business needs (including driving innovative and disruptive digitalization) must work long-term with these issues and be able to get funding, resources and buy-in for implementing and maintaining whatever IT systems are needed, and also to have the resources to train and support people across the silos to change the way they work (if that’s necessary, and it usually is). This means shifting some of the power from silos to cross-corporate functions and is ultimately a management issue. Prepare for political shenanigans!
What could you achieve?
Let’s say the company fixes this problem. It would, at a minimum, mean that they have a reliable, central record of each machine they’ve sold (identified by a unique serial number), what product type and model it is, when it was sold, at what price, to whom, where it it’s located, where it was manufactured and so on. In the spirit of digital business transformation, what could they do? Let’s toss up a few ideas, from the more traditional to some a bit more fanciful.
- Enhanced customer support
When customers called in to the company’s central help-desk, the bad data quality prevented the support staff from giving accurate answers. It also prevented them from suggesting relevant added services. With the new high-quality data, accurate answers and relevant and timely offers could be provided, enhancing the customer experience and generating a stronger revenue stream.
- Proactive maintenance services
In the past, each acquired company conducted their own way of providing maintenance services. They probably had their own staff of service engineers and ways to interface with their customers. Given the new reliable data, global business development could start creating added value to their customers by offering proactive maintenance services, meaning that the customer would automatically be contacted for scheduled maintenance activities (at a healthy service fee of course).
By having access to harmonized data, global offerings could be devised and rolled out. By standardizing offerings and processes, economy of scale could be realized.
- Outsourcing the maintenance services
Once the company has this reliable data, it could outsource all or parts of the maintenance service work. They could provide a global supplier interface where local service companies could be assigned service work. This could increase the availability of service capacity and help bring down cost by subjecting the suppliers to competition.
- Predictive maintenance
Let’s say this company wanted to go seriously digital. For example, maybe they wanted to add sensors to the machines so they could predict when a component needed service or replacement (instead of scheduled proactive maintenance), thereby optimizing on-site service visits and spare part consumption. If this sensor data can’t be reliably associated with the correct data about the machine (because the serial number is unreliable), the whole idea will be dead on arrival.
Take responsibility for the whole
We’ve just scratched the surface of what’s possible if you have control over your data management. The purpose here was simply to show the direct link between high-quality data and business transformation opportunities. The key take-away is that the business took responsibility of a business entity (in this case the individual machine), making sure company-wide processes and ownership were in place. This enabled all sorts of business transformation, leading to stronger revenue, higher margins and increased customer satisfaction. IT is only the intermediary, providing technical craftsmanship – the business needs to be in the driver’s seat.
In the future, those who manage their data in this holistic fashion will be the winners. Crappy data is increasingly a severe liability that will hamper healthy business development and growth.