Service businesses want to use data to improve productivity and competitiveness but find that many of their staff do not have the necessary skills. Service Leaders from 10 companies explored with Si2’s Nick Frank how to improve this in an SLN Experience Exchange. Here are the takeaways.

On the 18th Feb, we hosted a virtual experience exchange with 10 Service Leaders to discuss their views on how data savvy their teams need to be, and how well-positioned they are to leverage the waves of data emerging from their organizations.  Here are some takeaways:

Introductory Context
For some time we have observed that many companies have their sights on using sophisticated analytics tools and artificial intelligence to strengthen their competitive capacity or improve their operations. But a burning question for us is whether their people have the mindset and skills to support this desire (see our recent article “Are you ready for the data Savvy world”)

This in part has been based on our own experience of running workshops where well over 150 business professionals have looked at how to improve their visualization and data storytelling.  We observed that at a practical level, most simply do not have the data skills that allow them to integrate the sophisticated analytics tools demanded by their management into their working processes.

It also comes from seeing frustration expressed in leading research publications, where observations such as “Only 10% of companies obtain significant financial benefits from artificial intelligence technologies”  are becoming increasingly frequent.

Synopsis of the discussion
Under the over-arching headline “How Data Savvy does your team need to be in today’s digitized world?”, we had lively discussions around 3 topic areas:

  • How do you want to use data?
  • What skills & capabilities do you think you require?
  • What are the skill gaps you see and how are you filling them?

Here is a short summary of what this group of managers observed:

 

  1. How do you want to use data in your organization or team?

Three themes emerged on how these professionals were looking to use data currently, and also in the future with more sophisticated data solutions:

  1. Check and validate the business stories we have been telling ourselves; For example, why customers purchase our brand
  2. Learn from data how to improve operational effectiveness
  3. Use data to identify new opportunities in the area of sales, products & services

 

  1. What skills do you think your team require?
  • Most people recognize that data is an important part of the world today. However, a major failing perceived by many has been communicating to operational staff as to why data and in particular data quality are important.  Examples that were included were the importance of keeping customer master data current or ensuring data is clean and fit for purpose.
  • Although there may be a basic understanding of numbers across organizations, much of the know-how on how to analyze and visualize data resides in small specialist groups. The problem is that many of these specialists (e.g. Data Scientists) do not understand the context of the business. And if the business professional does not understand how to talk to the data scientist there is a significant mismatch.  Both need to move closer to each other. Data Scientists need to experience the context of the business. Business professionals need to know how to describe the business problem they are trying to solve in a way that data scientists can develop their analytics. We discussed that for managers that it is important to clearly define the problem they are trying to solve. An example of how to do this might be summarised in two sentences:
  1. What are the key performance indicators they are trying to influence and the key parameters that drive these indicators? This is the business context and is defined primarily by the organization’s management.
  2. If a particular set of data is collected, and then analyzed, then the business should be able to drive to certain specific outcomes. This is the data hypothesis that allows data scientists to develop the appropriate data solution.
  • Communication skills in particular as they relate to value. This is important as it enables a company to articulate the value proposition of the data solution to:
  1. Customers: so they will buy
  2. Employees: so they will sell and support the selling and delivery processes.
  • A basic understanding of how we as human beings use data and the phases we must move through to become expert users, the objective captured elegantly by the phrase “Simplicity on the other side of complexity”.  There are three phases:
  1. First, we start to learn about our environment through data and experiences, but we have not integrated it enough into how we think to communicate it effectively.
  2. We have integrated data and learning into our way of thinking, but we bring too much complexity into our communication and find it difficult to engage and drive action.
  3. We have discerned the essence of the data story and so can communicate it effectively and generate action

For further information on this approach see “Simplicity on the other side of complexity” by John Kolko

 

What are the skills gaps and how do you fill them?

  • Creating a culture & mindset where data is an intrinsic part of the culture is perhaps the key challenge. Often this starts with senior management who may be used to making decisions based on what they think they know, “instinct” or “gut feel”, rather than data they have available. Obviously, decision-making is far more nuanced and requires an understanding of how and when to use the different approaches. The issue is that the current generation of managers can have too much focus on the former. One participant from a business that had seen a shift to predictive maintenance concepts stated that in order to make this transformation, they had to change the composition of their leadership team.
  • The ability to use data to drive action must be a fundamental capability for all service people. However, it is very ambitious to get everyone in an organization data-savvy, and that a first step is to focus on the organization. In other words, develop dedicated people who can effectively use analytic tools to generate queries and dashboards and help organizations move forward in a digitalized and data-enriched environment. Then any training in how to analyze and visualize data is more effective as the service people can see more clearly see the benefits of using data in decision making, as well as have a natural support network in place to improve their skills.
  • Some observed that the best service managers use data to sell services, for example in particular predictive maintenance and other contracts. They do this by analyzing the data in their systems combining with their knowledge of the process to develop a coherent value-based argument as to why a customer should purchase their service offer. Usually, this is a self-developed analytical process and by its nature very manual. By using IT tools such as Power BI, Tableau, or other business intelligence tools, this process can be automated making this exploration process part of the normal workflow. The opportunity then exists to bring all service managers to similar levels of performance.
  • Using a company’s performance management system to drive a change in how people use and understand data. Interestingly the focus of this discussion was around improving the use of data with the sales and account management professionals. Three examples were mentioned:
  1. Implementation of quality scorecards for sales on how well the installed base is performing in terms of sales and customer satisfaction
  2. Incorporating the results of advanced data analytics into the account management and sales process. For example, looking at prediction of contract churns or identifying what the customer might buy next.
  3. Coaching and training on how to improve the use of data in decision making

 

In conclusion, the discussion shows that people recognize the importance of data, but that if companies are to fully leverage the digital revolution, they need immediate focus on two issues:

  1. Building pockets of expertise that can act as a catalyst for the rest of the organization in creating dashboards and analytics tools that are relevant to the day-to-day work.
  2. To see digital transformation, not as a technology shift, but a change program that is made up of a culture and mindset shift through all levels of the organization.

 

About the Service Leaders Network
The Service Leaders Network (SLN) is currently organizing virtual Experience Exchange events. Our goal is to let experienced service leaders learn and collaborate with each other to improve their own capabilities in their working environment. Participants came from a variety of industries from technology to power and included professionals working in smaller organizations as well as large multinationals.  If you want to know more about the Service Leaders Network, then visit https://serviceinindustry.com/service-leaders-network/

 

Taking a first step: Does everyone in your team understand how to visualize data for action?

Don’t take it for granted that your team are expert in using data. Improve their understanding through a tailored one-day workshop that will help them understand the process of moving from “business problem to data solution”, to better visualize data to create impact and data story-telling to drive action. Contact Nick Frank at nick.frank@si2partners.com for more information.