5 key problems faced by companies on using analytics

Analytics is not as simple as using a tool that can give us one “golden metric” which will answer all of our questions.

Companies struggle with analytics for various reasons. Many times they have a hard time pointing out such reasons and end up giving up on pushing forward with analytics solutions – staying with a very basic setup. Problems with analytics can be partially related to limitations of the analytics providers and the setup of the analytics data flow in the organization, but they will likely go beyond technical aspects alone. Let’s look together into 5 common problems related to analytics, so we can build a better critical view of the situation within our organization and/or with clients that we work with:

  1. Data gathering & digitization
  2. Data storage, integration & analytics data flow
  3. Process structuring & integration
  4. Team integration
  5. Goals & strategy integration

As you have surely noticed, the term “integration” is present everywhere in our list. The key is indeed to integrate different aspects of our structure and workflow. Let’s take a better look into more details of how to do that.

1. Data gathering & digitization

The first step in every analytics process is to identify what we wish to measure and what we can measure. It can happen many times that we will not have access to all of the data we would like to have. In some cases, the lack of data can be something that our organization can work on and in time prepare a better structure for data collecting.

Especially when working with many offline sources of information, a company may have trouble to bring all of that information into the digital world. This is the case with retail, paper press, physical events and shows, and such businesses. There are ready-made solutions that will help bring more data from the physical into the digital world. It is however somewhat of an ongoing challenge for companies that have a lot going on offline.

Then there is the need to be sure that enough of the digital data is being gathered, and that what needs to be tracked is being tracked. Some platforms such as Hubspot make a business out of the offering of this “fully trackable” digital environment for companies. It is also possible for a company to track everything without the use of such ready-made services, so the choice will come down to the company being willing or not to spend on such ready-made platforms.

But even with ready-made solutions, many data points will not be immediately available. It can be the case with social media data, for example, or other business metrics such as sales and customer support tickets. It is likely, therefore, that a company will need to bring dedicated services together to be able to track everything that is going on around their channels.

On minute 18:10 of the video within the following link, I address a few quick points into choosing a modular and dedicated analytics setup: https://www.analyst.life/blog/2018/02/15/social-media-analytics-strategy-book-launch-video/

The next step after being able to securely and continuously gather everything will be to bring everything together and integrate the views and workflows

2. Data storage, integration & analytics data flow

Once the data is there, the next step and next problem on our list is to safely store it and enable access to everyone that will benefit from it.

Data storage is many times a highly overlooked piece of the puzzle. Especially when departments do not integrate processes, and goals are not properly aligned throughout the organization, no one takes responsibility of the task of storing data. In companies with an internal IT department the responsibility is more directly assigned, but even then there can be gaps and missing data if departments don’t integrate their requirements and plans for the long term. It is crucial that a global map is made of all of the data flowing within the organization, and even around external assets that may not be connected into the main system yet.

3. Process structuring & integration

With the data well stored, integrated and flowing within the company, the step of dealing with processes starts.

Relating to analytics, these are processes that will be directly connected and aligned with the goals behind having analytics tools in place. What a company will be doing here is shaping the steps to establish and uncover main KPIs that will consistently drive it into actionable insights.

There can be also some level of experimental analysis going on, where there is not a very clear and precise goal tied to specific metrics, but an open research into certain areas of the data in the hopes that unexpected insights will show. This kind of analysis is usually put in the hands of the most experienced analysts on the given subject or area of the company.

By “analyst,” in this case, we can also consider anyone with the necessary “analyst mindset” and enough experience to be able to make the best possible connections between insights from the data and all other areas of strategic relevance to the work. So, in a simple example, the experience of a marketing director in retail can give him or her an edge when interpreting data from user behavior within retail physical spaces.

It is interesting to bring up also that certain technical analysts can run processes around machine learning and such to uncover very unexpected and interesting results.

Back to the processes, this stage and problem faced by companies will involve the definition of tasks, roles, accesses, responsibilities and a full check on each part of the “bigger puzzle.”

4. Team integration

This can be the greatest problem many companies face regarding analytics. The problem is not on the quality of the individual professionals, but mainly on the fact that analytics will not be the highest priority for everyone involved. Nevertheless their participation is key to build a structure around the successful use of analytics. But if people involved don’t have time to dedicate to learning, interpreting and implementing insights from analytics, the entire strategy becomes stuck and consistent results are never reached, much less an improvement cycle.

On top of individuals giving a bit of their time to analytics, comes the need for integration between different teams. Different teams will have different demands that must be tied to a global strategy and many times will depend upon the completion of tasks from another team to be able to be fulfilled. Hence the need for integration within teams and among different teams.

5. Goals & strategy integration

The closing point is somewhat the “tip of the pyramid” for us in this article. It is about aligning the entire company around its main goals and the strategy to get there. To do that, minor goals will likely need to be met along the way and make sense into the bigger picture. Marketing, sales, HR, product, operations, alignment of internal reporting cycles… and all of it ultimately aligned with the effort to change what happens to be in need of improvement, or innovate when things are working but the company is still not gaining the desired growth.

In Conclusion:

No matter what size company, these challenges will likely be there. They might even happen again and again after the company has reached a certain alignment during a period. The market changes, the team changes, the systems in use also change. Many factors can get in the way of setting up and using analytics in a truly effective way.

The aim of this article is only to spark our interest in pursuing details around these 5 points within our organizations. There are of course an array of issues associated with tracking, measuring and analyzing what we are doing, but as long as we keep a clear view on what must be done, we will be able to build an effective structure to enable data-based decisions leading to growth.


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