The Importance of Planning in a Data Collection Project

(Image: https://blog.vectracs.com.br/estagios-da-transformacao-digital/)

Digital transformation is the hot topic of the moment, as data is increasingly becoming one of a company’s greatest assets. However, whether structuring a solution from the very beginning, or restructuring an existing solution, it can be a big challenge. Later on we are going to talk about how important the planning phase is and how it can contribute to project performance, a better end result and a reduction in the time it takes to implement a solution.

Where do you start your planning?

To choose the best route, the most important thing is to know exactly where you want to go. Therefore, we recommend that in the initial phase you diagnose the problems and understand your business needs. For this, all project-related areas need to be mapped, from the technical areas that have knowledge of the infrastructure, to the areas that will consume the data at the end, and the teams that will be responsible for the implementation of the solution.

You must make sure that the main focal points are aligned with the project’s existence and purpose, and take the opportunity to interview and gather as much information about your day-to-day operations and needs such as: business challenges, data needs, technical limitations, current projects that be conflict with the planned one, the management system of each team, consideration of deadlines and sprints etc. You should concern yourself with getting both the managerial and operational vision of these aspects right. At this time, you will also have the opportunity to emphasize to each team the relevance of the project and its impacts for the company, thus promoting greater engagement.

Developing a set list of questions can streamline the information-gathering process. Don’t forget to document all this valuable material!

This initial mapping will never be wasted, as it will assist in building a solution that meets all the needs of the company as a whole, while at the same time, it will be technically viable. Note that a project of this size may take some time. Starting collection in an unstructured manner may result in improperly prioritizing fronts and lead to avoidable work at the implementation stage, as you encounter unanticipated needs during the project.

Solution Proposal

With all the information collected from the various areas, it is time to do some analysis and start to design the proposed solution. To do this, it is recommended that you rely on the three fundamental pillars: People, processes and technologies. You need people who are aligned with the objectives and are able to execute the processes and operate the tools. You need processes that promote documentation and information sharing, as well as increased productivity performance. Finally, you need technologies that favor the communication, organization and operation of the proposed fronts.

At this stage it is already possible to plan which metrics and dimensions should be collected in order to respond to business needs. The first step in this process is to define what the main macro objectives of the company are, as well as the strategies and tactics designed by the areas that will use the data to achieve these goals.

With these items well defined, it is easier to understand which KPIs will guide decisions and measure the results of such tactics. From this material, it will also be possible to define the dimensions and metrics that should be collected to direct the business.

All too often companies want to collect all possible data in all environments. Do not give in to this temptation! This practice will require much greater effort and will result in unnecessary data accumulation, data which will not generate any insight or value for the company and will only result in additional storage costs. Defining the KPIs and structuring a result measurement model will help in this process of prioritizing what should actually be collected and how this data will contribute to the direction of the company’s strategic decisions.

There are several methodologies for creating a results measurement model. This topic would result in a long post on its own. In this post by Avinash Kaushik, you’ll find some references and directions if you wish to delve into the subject.

Tool Architecture

Each data collection ecosystem requires the use of different tools, which will most often be used by different areas for various purposes. When defining the architecture of the tools and the data governance framework, that early phase of understanding your business needs will start to show their value. Keep in mind that the time spent revising the tools account structure and adapting the collection to this may be far greater than the time spent on previous phases.

More than ever, you should focus on documenting the defined standards and sharing them with others involved in the project. Remember that a data collection project serves the entire company, not just the area involved in its execution, so it is important to validate and make sure that the proposed solution caters for everyone and allows for economy of scale, in accordance with the growth of the company.

Chronogram

Now that you know where you want to go with the collection and what the main needs of the company are, it is time to prioritize the fronts and design the implementation schedule. It’s not uncommon for companies to have grandiose goals far removed from today’s reality, but remember, if you’ve only started training today, there’s no point in trying to complete a marathon tomorrow. Prioritizing in a realistic and actionable manner will help you to achieve short-term results, always moving towards your ultimate goal.

Having a set schedule will help the alignment of the teams involved, how the operation will be carried out, in addition to bringing greater focus, productivity and help with task management. Take advantage of deadlines and communicate with the areas that will consume the data delivered at each step, thus ensuring an alignment of expectations.

Data-driven areas are very dynamic, and business needs to change all the time. The biggest challenge of setting a schedule will be to ensure that it is always up to date with changes in business strategies. Therefore, it is very important that there is a focal point for the project, with the objective of interacting with all areas and performing frequent follow-ups. Without this communication, all initial planning may become obsolete in a few months.

Another frequent challenge is dealing with emergency needs that are present on many fronts. Quite frequently, there are so many priorities that we hardly know where to start. When in doubt, always look at the company’s main goals for the year. Will the incoming demand impact that goal? If not, rethink your prioritization.

Even with all this, we know that there are emergency needs that may not have such a direct impact, but which are quite relevant and need to be developed within a specific time frame anyway. A frequent example is the demand from the media area, where it is necessary to measure campaigns dynamically, but the same can happen in several other cases. When faced with this scenario, think of methodologies that allow these demands to be met, but try to do it without interrupting the advance of the schedule planned at the beginning. A commonly used method is the distribution of the effort dedicated to each front in a percentage compatible with the needs. For example, allocating 20% of the effort to the media-focused collection activity, following the previous case, and 80% dedicated to the original project schedule. This way we can guarantee that neither front will stop evolving.

Wow! It seems like a lot to think about and structure before taking the first steps in collecting data. However, as we have seen, each step has several benefits that will assist in the planning of allocated resources, structuring of internal communication methodology, proper prioritization of business needs, alignment of deadlines and expectations with those involved, maintaining the initial scope of the project and keeping quality standards high. If your business wants a robust solution that meets all areas and allows for scale, defend your planning every time that anxiety arises.

Profile of the author: Iris Grillo | Graduated in Foreign Trade, currently working in Digital Analytics at DP6.