If most customer data initiatives are risky, have low adoption, and often don’t meet their goals, what steps can we take to improve success rates?
What we’ve learned at Juice over 10 years and hundreds of implementations is that customer-facing data initiatives succeed when you deliver a product, not a project. You need a product mindset to reduce risks, make customers happy, and deliver revenue. Having a product mindset means:
Acting like you are delivering a game release to millions of gamers for a midnight deadline.
Treating every deadline as a missed product launch (with lost revenue).
Recognizing that disappointing users will hurt your organization’s reputation.
Here is an illustration of how a new way of designing and delivering data products looks compared to the traditional IT BI project.
Here are three things you need to do to improve your odds for your external data initiative, i.e. customer reporting, embedded analytics, customer-facing machine learning product, etc.
1. Set a product launch date
With a product mindset you have a product launch and not a project plan. Product launches involve more stakeholders, like marketing and sale so accountability is extended beyond the project manager. With many teams committed to an on-time date and increased executive visibility, there are lots of folks with skin in the game.
Products (not projects) have a revenue commitment. As a general rule, you won’t get any of marketing or sales time if there isn’t revenue attached to the initiative. One agile process we love to get the organization bought into the initiative are release readiness meetings. If facilitated well, each team actively participates and has a stake in go/no go decisions. This force stakeholders to make commitments and take interest in the outcome.
Missing dates isn’t the real issue; it’s the consequences of missed dates which dramatically affect your data product initiative. Missed dates makes additional funding more challenging as executives question the initiative’s (and team’s) ability to meet goals. It affects your reputation with customers and their confidence in you to deliver. Note the diagram above. As soon as the launch date is missed there is lost revenue and that gets noticed more than a missed project date.
2. Plan for 2.0 version from Day One
When you have a product and agile mindset, it's all about getting a small, valued first release into the market because you know there will be a 2.0 version. With a 2.0 of your data application, you’re not trying for the perfect data product, but one the market will use. This changes the way you gather requirements and prioritize features. When it's only a one-time project, it is easy to go overboard, taking weeks to define your requirements. Here’s a good article describing an MVP product’s functionality and their illustration of how to prioritize features for your initial product.
Talk about 2.0 often, particularly with executives, to set their expectation that funding the initiative is an on-going endeavor and not just a single capital or funding request. When executives and customers know there is a 2.0, then every feature doesn’t have to be in the first release, helping reduce product complexity and likelihood of missed dates. Success improves if you build and share prototypes and explicitly deliver an MVP.
3. Talk about apps, not reports
We’ve touched on this point before, but it bears repeating. When you think of your solution as an application, it forces you to solve a problem. With a product mindset you spend more time on understanding the problem you want to solve vs. capturing feature wish-lists. As a data product manager, your new product mindset and focus on a series of apps vs. one large data project forces you to segment your audiences. You can now target each audience’s specific needs. Now that you’re delivering an app, your users will be more inclined to know when and how to use it. Apps, by their nature, have training and support built-in, reducing risks in implementation and adoption.
There are some challenges that will arise with an "app focus”. When delivering data apps, you’re creating a more prescriptive experience for your users. Those users or customers wanting to explore insights and define their own solutions could be disappointed. The right way to address this challenge is to view these data explorers as a unique audience with their own application needs since exploring data and presenting results are different problems.
Sure, we’ve now taken your single data initiative and made it into numerous projects. While it might be scary at first, it is most likely the reality of what your customers expect anyway. You didn’t expect to be able to meet the needs of all customers with a single offering did you? With your new found perspective you’re ready to think about your data initiative not as a single project, but eventually as a portal or app store to deliver many new products.
The Product Mindset
The product mindset is rooted in adopting agile methodology. The big IT project mentality hurts your customer data initiative and adds more risk. There are many excuses as to why folks don’t want to adopt a product mindset or agile for BI projects. We’ve heard them all; however if you feel like your organization wants to be part of the data economy, then building and launching data products is in your future.
Want to learn more about our formula for successful customer data initiatives and see what a successful data product looks like then schedule a minute discussion below.