Transforming Data & Analytics: Addressing Consolidation Challenges in the Age of M& A

One of the items we identified in our Communications and Media 2017 Trend blog post (here) was organization consolidation due to M&A activity.  From AT&T- Time Warner to Discovery – Scripps and the spectre of a Comcast-Verizon (likely) or Tmobile-Sprint (less likely), there seems to be more activity turning 2017 into the year of transformation. For organizations not going through a merger as complicated as those, there is still likely a re-organization effort that has been set in motion as a response to industry evolution.

Business-as-usual has left the building, no big surprise.
What may create a significant surprise is when these new teams of co-workers work to pull together their first consolidated data view of the new organization after the close. If you think a data and analytics program is complicated within an existing business, try doing this with an organization that is redefining its products, services and adding in new (sometimes duplicative) teams of people and vast amounts of data.  This is well beyond walking and chewing gum at the same time.

So, how do you get from 2 unique companies to a consolidated, effective, future-state analytics environment?  You will have to work across data, tools, and users and get a holistic view of how teams need to be reassembled, ensure that tribal knowledge is retained, and metrics are aligned or re-defined to accurately represent the new organization?

Midtown Consulting has done this and can share our expertise.

There are four key areas to consider in a consolidation effort with data and analytics:

Leadership Focus

A strong leader within the organization needs to be involved to steward this effort.  It is guaranteed that there will be a lot of activity and challenges to the priority of assembling data and aligning terms.  This role needs to have their finger on the pulse of the project and blow through any roadblocks at the right levels.  If there is not an Executive associated with this, there is big trouble ahead for the team as their concerns and needs will be trumped by those of the transition team.


Data integration during a process as complex as a merger or acquisition is no small undertaking. Not only is the project massive, but ensuring proper alignment of data can be an extremely complicated process. Prioritize the data you have and what you need to produce core metrics and build a flexible plan for change.  Core metric definitions may shift as the operational, sales and financial teams get integrated and new processes and system changes emerge.  Publicly traded companies have additional challenges of aligning externally shared metrics in a way that does not surprise shareholders.

While challenging, this is also a great opportunity to work through all the data and ensure quality definitions are being produced.  Every project I have been on has had its share of data discoveries – when you get to the root of how a data point is built and find that it has not stayed in line with all business and source system changes.  Reviewing and aligning details when you are building the new standard is good way to approach re-validating the accuracy of data.


Typically, the buying company will align the purchased organization into their software stack, but don’t dismiss alternative technology.  This represents a good time to share experiences across tools – pros and cons that will help shape future platform decisions.  Many organizations seemingly take the Baskin Robbins approach to buying BI tools and want all 31 flavors.  This can be an effective time to execute a Proof of Concept to ensure that you have a  good tool, or complement of tools, for data reporting, visualizations, analytics and advanced analytics. If you aren’t sure why those may be different, let’s talk.


As if the technical aspects weren’t complex enough, events like this create a surplus of talent in a resource-competitive market.  A good approach is to have a strong communication plan to talk with staff and ensure they understand the vision and their roles in completing that vision.  This is also a good time to focus on the details – upskill team members with fresh training – it’s not all about the meat and potatoes of using the tool effectively – do they understand the data, the new business, are key decision points about the new operation and structure being effectively conveyed?  Are they bought in that they are part of the organization and change?

Assembling amazing data and providing top-tier tools will not win the day for your business if the users are not fully bought in to what they can do with those assets. People make data useful, not warehouses or visualizations.


Is your organization reorganizing and redefining itself in 2017 or 2018? We can help. Let’s connect.