{"id":21132,"date":"2019-02-12T11:50:14","date_gmt":"2019-02-12T17:50:14","guid":{"rendered":"https:\/\/blog.planview.com\/seeing-the-full-picture-identifying-each-customer-request-that-goes-into-a-product-release\/"},"modified":"2019-02-12T11:50:14","modified_gmt":"2019-02-12T17:50:14","slug":"seeing-the-full-picture-identifying-each-customer-request-that-goes-into-a-product-release","status":"publish","type":"post","link":"https:\/\/blog.planview.com\/seeing-the-full-picture-identifying-each-customer-request-that-goes-into-a-product-release\/","title":{"rendered":"Seeing the Full Picture: Identifying each customer request that goes into a product release"},"content":{"rendered":"
\n
\"Seeing<\/div>\n<\/figure>\n

It was October, and we’d just wrapped up another release of our product.  Whenever a release goes out the door, our Product team works to make sure that our Account Managers understand which of their customers’ requests made it into the product, enabling them to close the loop and notify their customers of the great news.  Because what’s the point of implementing a customer’s request if the customer never hears about it?<\/span><\/p>\n

The problem was that we stored our customer requests in one tool (Salesforce), our feature backlog in another tool (Targetprocess), and the Epics that contain the actual work that got coded into each release in yet <\/span>another<\/span><\/i> tool (Jira).<\/span><\/p>\n

This disconnect made it extremely time-consuming to gather the necessary information about the release – a task that seemed like it shouldn’t be that complicated!  And, unfortunately, that work landed on me. <\/span><\/p>\n

I had to query for each Epic in Jira that made it into the release, and then individually trace that information back to Targetprocess and then to Salesforce to determine which, if any customers, were associated with that feature.  Then I had to figure out which Tasktop employees worked directly with those customers, another difficult feat. Finally, once I’d gathered the data, I manually entered it into a table on our internal wiki. The work was arduous, error-prone, and frankly, a waste of my time.  <\/span><\/p>\n

I tried adding links to my table to illustrate which features I was referencing, often to be met with access issues from our Account Managers, who received an error message when trying to open my Targetprocess links.  Our Product team’s time, which should have been spent prioritizing and designing the cool features we wanted to add to our product, was instead spent on a mess of administrative, bureaucratic busy work.<\/span><\/p>\n

Our Old Process<\/strong> There had to be a better way.<\/span><\/p>\n

Suddenly it dawned on us.  We work for a company that focuses on <\/span>eliminating barriers between siloed teams<\/span>.  Why weren’t we using our own tool to make this process easier and more efficient?<\/b>  We got to work.  We already had an integration in place to create traceability between the originating business requests and the implementation artifacts.  This solution broke down silos, enhanced communication, reduced data entry, and allowed us to measure <\/span>lead time and flow time<\/span><\/a> to identify and eliminate bottlenecks in delivery.<\/span><\/p>\n

But there was more we could do.<\/span><\/p>\n

The missing piece here was that our customer-facing teams only cared about the original customer request, which didn’t always have a one-to-one relationship with the features that our Engineers were building.  Sometimes multiple customers requested the same thing. Sometimes they requested something which spanned numerous features. We needed a way to take these complex relationships and to flow one crucial piece of information – the <\/span>release<\/span> that contained the feature – to each associated customer request, which lived in a separate tool.<\/span><\/p>\n

<\/p>\n

By adding some minimal changes to our Tasktop configuration, we were able to automatically flow ‘Release implemented’ information straight from Jira (the tool that tracked our Engineering work) to the original customer requests, stored in Salesforce.  Now our Account Managers could view an automated report showing them the individual customer requests that had been added to the product each release. Since we generated the report in Salesforce, they could easily navigate to customer history and contact information, enabling them to reach out to share the great news directly with customers.<\/span><\/p>\n

<\/p>\n

By connecting these tools and automatically flowing the required data from Jira to Targetprocess and finally back to the original customer request in Salesforce, we made sure that the right people had the right information at the right time.  And we can help you do the same. Reach out to us for a highly-personalized demo to experience how integration can eliminate all those unnecessary and cumbersome tasks that slow your teams down and distracts from the work they love to do.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

It was October, and we’d just wrapped up another release of our product.  Whenever a release goes out the door, our Product team works to make sure that our Account Managers understand which of their customers’ requests made it into the product, enabling them to close the loop and notify their customers of the great…<\/p>\n","protected":false},"author":233,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_editorskit_title_hidden":false,"_editorskit_reading_time":0,"_editorskit_is_block_options_detached":false,"_editorskit_block_options_position":"{}","footnotes":""},"categories":[478,9543],"tags":[],"class_list":["post-21132","post","type-post","status-publish","format-standard","hentry","category-products","category-value-stream-management"],"acf":[],"yoast_head":"\nSeeing the Full Picture: Identifying each customer request that goes into a product release | Tasktop Blog<\/title>\n<meta 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