Every organization needs a data strategy with these building blocks:
- Business Intelligence
- Data Management
Your top priority is linking your data to company strategy. Here are the steps you need to take:
- Identify strategic goals - i.e. data projects that will help you reach long-term company objectives. Try to pick data projects that will be quick wins. In other words, look for a project that will show maximum value for a minimum of effort. In the beginning, it’s especially important to prove the value of the overall project and to get (and keep) people motivated.
- Break the strategic goal down into objectives. Assign a stakeholder to each objective as the driver/owner of that objective.
- Define initiatives that fall under each objective.
- Create a project work group that includes IT, end-users and information consumers. This small work group will start the project(s) that contribute to the larger initiative.
- Translate projects into solutions. The cross-functional team will work together to address challenges from multiple angles and translate business requirements into actual solutions.
For example, let’s say that the company’s goal is €25M in new sales through up- and cross-selling; our objective is to improve customer experience to help reach that sales goal.
First, we need to achieve a single point-of-view on the customer (360° customer view), i.e. know your customer. So, our initiative is: Targeted marketing and marketing automation.
The projects kicked off by the initiative will include: Data integration; data quality; data enrichment; KPI’s; segmentation; scoring.
The projects translate into the following solutions: self-service and governed data management; data visualization; self-service and governed reporting; approachable analytics (to build analytical expertise); data mining; advanced and big analytics (later stadium).
This is a comprehensive example that covers a lot of territory, but you can define some quick wins as well. Here are a few examples, by industry:
-
Logistics
Get a fuel tax refund from the government by creating a report that combines data from the trucks and fuelling stations instead of using data entered manually by the truck drivers. This will avoid human error, save work for the drivers and save you time and money. -
Retail
Quickly detect your most (and least) profitable products to help you make pricing updates. Monitor demand and adjust your stock and production in order to guarantee delivery times. -
Manufacturing
Negotiate more effectively by creating an overview of key production materials. Or create a network diagram to see the impact of vendor price changes on finished goods. -
Finance
Visualize actuals versus budget to quickly see if expenses are in line with expectations. Forecast expenses to see where you’ll finish at the end of the fiscal year, or see how expenses are evolving over time to make a more precise budget for the next year.
Many other quick wins are possible, but these are just a few examples.
One final, important suggestion:
Assign ownership of the data strategy to someone (Data Strategist, CIO, etc.) who will actively guide it to success. He or she will have to monitor everything closely to detect overlap between initiatives, projects, software and tools when working in parallel. Doing so will save time when actions can be shared or reused for different initiatives, will reduce waste of IT resources (i.e. no overlap between software in the IT landscape – more on this in my next post).
Conclusion
Ensure that your data is linked to your organization’s strategy and that ownership for that is taken at all levels (goals, objectives, initiatives and projects). Make sure that business and IT are well aligned to come to a solution that works for everyone. Communication between teams is key.
What’s challenging for your business? Have you detected quick wins that you could share? Please reach out if you want to discuss anything related your data strategy or if you want to look for quick wins. Feedback and ideas are welcome as always.
I will go into more detail about the three data domains in my next post, so stay tuned.
Blog series Data Strategy by Natan Meekers
- The Hell of Excel, or why you need to future proof your data strategy
- How to future proof your data strategy