Business consultants help businesses improve their performance. They work with clients to identify size, and solve problems, develop strategies, and implement changes. Data analytics is key to that process. Collecting, cleaning, and analyzing data to extract meaningful insights is what makes a point of view into a diagnosis and prescription that will deliver benefits.
Why Data Analytics is Key to Business Consultants
Data analytics is key to business consulting because it provides evidence to support the diagnosis of the issue in a way that is specific to the client. Therefore, it’s a powerful tool to motivate and persuade people to make changes. It also validates the business case for change and enables the measurement of success as the project progresses.
Challenges with Data Analytics
The challenge is gaining quick and easy access to relevant (ideally live) data to do this work without eating up client and consulting resources.
Below we explain why data analytics is so important and talk about how to overcome the data access challenge.
Data Analytics Provides Evidence to Support the Diagnosis of the Issue
Data analytics can be used to collect and analyze data from a variety of sources, such as financial data, customer data, and operational data. This data can be used to identify trends, patterns, and anomalies that can help the consultant to pinpoint the root cause of the issue. For example, a business consultant might be working with a client who is experiencing declining sales. The consultant could use data analytics to analyze sales data from different product categories, regions, and time periods. This analysis might reveal that sales are declining in a particular product category in a particular region. The consultant could then investigate further to identify the reason for the decline, such as a change in customer preferences or increased competition.
A Tool to Motivate and Persuade People to Make Changes
Once the consultant has diagnosed the issue, they need to motivate and persuade the client to make changes. Data analytics can be used to do this by providing evidence of the benefits of the proposed change. For example, if the consultant has identified that sales are declining in a particular product category, they could use data analytics to show the client the impact that this is having on the company’s bottom line. They could also use data analytics to show the client the potential benefits of making changes, such as increased sales and profitability.
In addition, data analytics can be used to create visualizations that can be used to communicate the findings of the analysis in a clear and concise way. This can be helpful for engaging stakeholders and getting them on board with the proposed changes.
Validates the Business Case for Change
Before making any changes, it is important to have a business case that justifies the investment. In this regard, data analytics can be used to validate the business case by quantifying the potential benefits of change. For example, if the consultant is proposing a new marketing campaign, they could use data analytics to estimate the potential increase in sales and revenue that the campaign could generate.
Data analytics can also be used to identify and mitigate any potential risks associated with the proposed changes. For example, if the consultant is proposing a new product launch, they could use data analytics to identify any potential supply chain risks or market risks.
Enables the Measurement of Success as the Project Progresses
Once the changes have been implemented, it is important to measure progress and track success. Data analytics can be used to do this by collecting and analyzing data on the key performance indicators (KPIs) that have been identified. For example, if the consultant has proposed a new marketing campaign, they could track KPIs such as website traffic, lead generation, and sales conversion rates.
Data analytics can also be used to identify any areas where the changes are not having the desired effect. This information can then be used to make adjustments to the plan as needed.
Accessing the Data that is needed.
The first step is to make sure that the client expects the consultant to carry out a data collection/access stage early in the project. Some clients will have excellent access to clean, relevant, current data – one might argue that they will have less need for consultants. If the business problem or opportunity is a challenging one it is often because the data to support the solution design is limited or simply difficult to access.
Next, the degree to which the solution execution will rely on data availability should be estimated from the start. In this digital age there are very few business solutions that are not heavily data dependent. Even a culture change programme will; use data to measure where the culture is now and how it changes, will deliver communications and training digitally, and need to measure if the change is having an impact on customer satisfaction and the bottom line.
A smart tactic is for the consultant to first trawl the client’s reporting suite for information that is already available and can be reused or repurposed for the challenge at hand. The last resort is to develop new data collection and reporting processes where these are required. But sometimes this is necessary.
Finally, the consultant should be familiar with and deploy ‘light touch’ data analytics tools – that use techniques like Virtual Data Layer – to access existing live data assets quickly and easily. These tools enable quick results with minimal need for client IT and analytics resources to be distracted from their day jobs.
Key Takeaways
- Data Analytics can be used to provide evidence to support the diagnosis of an issue, motivate and persuade people to make changes, validate the business case for change, and enable the measurement of success as the project progresses.
- Consultants should prepare their clients to support these data needs and use smart tactics and ‘light touch’ tools to minimize the effort cost to clients.
