Dinner parties and data strategies have more in common than you think
By Bo Hamrick, Pereview Software by Saxony Partners
It’s Monday Morning. You’re sitting at your desk. Your CEO walks up and says, “we need to develop a data strategy, and I want you to lead the effort.”
Where do you begin?
Do you Google “data strategy software,” hit the “I’m Feeling Lucky” button, and buy the the first product you find? Do you hop a plane to the next asset management conference and hope that one of the vendors slips you a magic pamphlet that solves all your problems? Are you just wandering the aisles, in the mood for an impulse buy?
I sincerely hope not.
Planning and assembling the elements of a data strategy is a lot like planning a dinner party.
The process begins in a similar way. Instead of Monday morning, imagine it’s Friday afternoon. You get home from work and your spouse tells you that some friends are coming over for dinner. If you’re like me, you take this news as marching orders, because you are the one will be figuring out what to cook and how to cook it.
How do you plan your meal?
I usually start by asking my wife what it is that she wants. But since no one has created a dish called “I don’t care, you pick,” I move on and ask if any of our guests made requests. After polling the dinner party, I start thinking of ideas. I start with the main course – probably meat of some sort – then move on to the sides and desserts.
Once the menu is set, it’s then it’s time to go to the store to pick up the ingredients I need. After returning home, I determine how much time must be allotted to complete and serve the different elements of the meal.
Now, let’s pick up where we left off on your data strategy.
In the same way that I polled our dinner guests, you should try and find out what the people who will use this data want. Be prepared to get the answer my wife gave me before the party: “I don’t know, you pick.”
If that’s the case, then ask them what they kind of functionality they need – and then maybe provide them with some examples. A good data strategy company has examples of some examples (recipes, if you will) that you can try out.
If you’re still not getting the answers you need, then develop some data use cases. These are smaller bit sized projects that can help you with your data strategy. Check out the guide to creating a data use template below.
- Link to strategic goal: Data should always be used in a strategic way, so link the use case to a specific organizational objective.
- Objective and business questions: Define your data-related goal in more detail and identify the questions you need to answer.
- Measures of success (KPIs or KSIs): Define what success looks like for this use cases and how you plan to measure progress.
- Use case owner: Who will be responsible for this use case? If you don’t assign responsibility, the task may never get done.
- Users and data customers: In this case, “customers” refers to the people who’ll be using the data and learning from the insights generated.
- Required data: Drill down into the data that you need for this project. This may encompass structured data, unstructured data, internal data and external data. (In the interests of data diversity, it’s a good idea to combine different data sets to create as rich a picture as possible.You’ll also need to identify whether you already own the data. If not, can you collect the data yourself or access it from third parties?)
- Data governance: This encompasses all the things you need to do to keep data safe, and ensure it’s used appropriately. Governance includes data quality, ethics, privacy, ownership, access rights, and security.
- Data analysis: There are lots of options for data analytics, including text, image, predictive, and many types of business analytics.
- Technology: Any data project will have implications for technology and infrastructure. So here you need to identify what are those implications, challenges and requirements. This means identifying what software and hardware you’ll need to collect and store data, analyze the data and communicate results.
- Skills and capacity: What skills do you need to make this happen? And do you have those data skills and capacities in-house? If not, do you need to train staff, or will you outsource certain tasks? Perhaps you’ll need a hybrid of in-house and external skills.
- Implementation and change management: Every project will encounter implementation challenges. This is your opportunity to identify potential roadblocks and implementation requirements so that your plan doesn’t get derailed.
Repeat this process and fill out a new template for each separate use case that you’ve identified. Once you’ve fleshed out each of your separate data use cases, and prioritized them in order of urgency, you can begin to complete your data strategy.
Once you have completed these questions for each of your data use cases, you can then start to look for commonalities among the use cases and put a plan in place to “cook these recipes.” You now have the menu for the perfect dinner party.
Have questions? Connect with me and let’s talk through the process of planning your data strategy – or your next dinner party.