Demonstrating Business Impact Of Data Projects
It is still true today that demonstrating tangible business impact from Data projects remains challenging. But why is this and what can you do about it?
One of the most fundamental problems in tracking the ROI from data initiatives is quite simple. Analytics is often brought in at the beginning of a project or a change to help measure the impact. It might be for instance that you model data along the customer journey so then you can better optimise your next marketing campaign.
Data teams are in high demand and no sooner have they finished one project than they have to work on another. It might be months or even a year before the true impact of their work is realised. In this period it is not uncommon for them to fall out of touch in how their work is being used, what the benefits have been for the team etc.
This is why it is so important to set clear timelines for internal reviews. The end of the calendar or financial year often makes sense as a way to go over the requests your data team had, catch up with stakeholders and see the impact. While most of the glory will undoubtedly go to those teams, it is important to remind everyone that it would not be possible without the underlying framework.
The Visibility of Ad-Hoc Work
People often take for granted what is right there in front of them. While end-users may come to rely on dashboards and flags to guide their everyday activity, they may simply overlook all the time and effort that is needed to keep these up-to-date. As such it is the ad-hoc requests and data analysis projects that become more visible to the organisation. While there can be a lot of value from these projects, this can give the wider business a more transactional view of what analytics can deliver. Ultimately the consequence of this is that it can make it more difficult to show the ROI of infrastructure-lead projects which may help to future-proof the organisation.
Data Adoption
The achilles heel for many data projects is in people actually using the solution. If the data solution isn not ultimately used this is a key failure, but at the same time there is a wide gap between using a solution and using it well. A gap that can be very difficult to quantify and track.
If you have a stakeholder that uses a dashboard every day, but then ignores what the data shows, that is not really a success! T
his is why it’s so important for data teams to understand exactly how the business function will be judged and tie into that as closely as possible. Then you can demonstrate the picture before data was adopted, usage of the data solution by the internal team, and the ultimate outcome. Business KPIs should be leveraged by analytics teams to demonstrate their impact.
Assessment Frameworks
When it comes to assessing the impact of any initiative it is important to be as impartial as possible, and the right framework can help. BSC or Balanced scorecard is a popular approach.
The Balanced Scorecard typically includes four key perspectives:
Financial Perspective: Increased revenue, cost savings, return on investment (ROI), and profitability. Demonstrate the direct impact of data/analytics projects on the organisation’s bottom line.
Customer Perspective: Customer satisfaction, retention rates, market share. Demonstrate how data/analytics projects have improved the overall customer experience.
Internal Processes Perspective: Identifying key processes critical to achieving strategic objectives and measuring their performance. Automating tasks. Reducing manual input. Reducing error rate. Reducing processing time.
Learning and Growth Perspective: Employee training, skill development, and the deployment of new technologies. Data/analytics projects may impact this perspective by enhancing the organisation’s analytical capabilities and fostering a data-driven culture.
When applying the Balanced Scorecard methodology it is essential to align specific project outcomes with relevant metrics in each perspective, establish a feedback mechanism to monitor progress and if possible, align performance reviews directly in with the scorecard.
Make Friends With Marketing
Without wishing to stereotype, data people can be a little shy. It is no good if your project delivers a fantastic result and no one knows about it! Analytics teams need to befriend their marketing or internal communication team and ensure that all successes are broadcast to the organisation.
Again, it is important to ensure that any updates are tied back to your business use case. Most people don’t have a reference for how long data modelling takes for example and so it is no use focusing on the tasks you’ve completed but rather what they will allow your internal teams to understand.
Conclusion
In conclusion, demonstrating tangible business impact from data projects is reliant on data teams being closely aligned to other departments, tracking their impact over a longer-term and not being afraid to show off their contribution to larger successes.
Everything we do here at 173tech is aimed to create business value and with clients across many sectors we have a solid understanding of the common data projects which bring maximum value in the shortest time period. Plug our experienced team in and tackle those data problems today!