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Transition focus from tech to the customer

 

Today’s projects are all about getting business results and today’s business results mean creating smart and meaningful customer experiences.  Many BAs were formerly business SMEs (subject matter experts) or Programmer Analysts before the Business Analyst role/title became the norm.  Both these previous roles had very detailed knowledge about the systems that supported the user workflows, and this served many BAs well in a role transition. Transitioning to a high-performing BA means letting go of these same technical details that helped us make the transition, and this is SO hard for many BAs to do!  Why is this important?  It is important because the BA role is all about getting value to the users and customers and the detailed knowledge is a tiny part of getting there.  A tiny part that other roles (technical and business SMEs) bring to the table, whereas then the BA role can focus on the analysis, options, alternatives, and various scenarios.  It can be hard to switch focus, but absolutely imperative that this happens for successful analysis.   The BA role is often the only role looking out for the integrated customer journey, others are there to look after all the technical details.  The trick is to reset the lens in which you look at the solution into a customer action, goals and, scenarios thinking engine, rather than the technical details. Realize that no one else is looking at it from this lens, it is NOW your job!

 

Integrate data into your customer focus

Data is all the rage, but where do we focus?

Here are a few ideas:

  • Answering key questions about customer behavior, data insights – This entails working with technical and data teams to incorporate data tracking and reporting to give you information about user behavior on an ongoing basis or ad hoc as you develop curiosity and questions about user behavior to help prioritize and solve for their needs.
  • Understanding data flow to analyze what will potentially provide the customer a better experience – This entails understanding the eco-system of the product, how and when data flows from system to system, understanding how this data impacts what the user sees and what the user can do.
  • Using data to predict things for users – This entails leveraging things like artificial intelligence and machine learning to predict user actions making the product ultimately easier for the user to get their work done.

 

Think in terms of experiments and hypothesis

 

Yes, that’s right, back to junior high science class.  What is your hypothesis and what experiments can be done to learn more?  Today’s age of technology, change, and customer focus require this mindset and these techniques to be used.  Too many changes too fast means too many unknowns, and too many unknowns means we can’t possibly have all the requirements and answers upfront.  So, teams need to work differently asking themselves “what is the smallest thing we can do to see if we are on the right track?”  And hypothesis and experiments can help teams develop a shared understanding to get to “the smallest thing” options to consider.

Level up your collaboration skills

 

Hand-offs and dependencies are the impediments to speed, agility, and delivering high-quality products that truly deliver value.  In order to reduce hand-offs and dependencies, we need to collaborate differently!  Turn your meetings into working meetings rather than reviewing documents.  Working meetings means brainstorming, prioritizing, discussing options and alternatives, scenario dialog for shared understanding…yes co-creating, co-working getting stuff done together rather than handing off documents to others.  So, think about all the times you think “oh, I’ll write that down and send it to you.”, or someone else asks you to just “write it down and send it to me”.  Ask yourself if a conversation might be more effective.   Our work is complex and sometimes dialog brings out deeper conversation and thinking that can get to better results than documenting and handing off.  Getting work done together vs. handing off is an adjustment and feels different.  It is a highly collaborative way of working that might seem like it takes longer, but many teams find it speeds up the results and with higher quality results.