An evaluation of the utility of the Data Value Map (Nagle and Sammon, 2017) as a framework for developing a shared understanding on data initiatives.

 Introduction

First of all, for context, it is vital to start this answer it is important to quickly describe what the six boxes in the above framework are. The four main drivers of this framework are people, processes technology and most recently data. While the main steps to managing data successfully according to the model are as followed. The paper written by the authors states that the framework should be used as a medium for conversation about data using the question words of why, who, when, where, what and how. It is these discussions under the six primary headings or building blocks of the framework that help create a shared understanding of data initives. 

 

6 Pillars

Business Value refers to what activities the organisation could do to better manage its data. Also, what it could start and stop doing to achieve the same goal. 

Data behaviours/Governance: What data needs to be anticipated by a firm about their data and how does the data need to be stored and contained. 

Acquisition: This refers to the acquiring of data into the firm. This could internal or external data and tends to be primarily internal. 

Integration: The integration of data from different systems into one centralised body of data. 

Analysis: The analysis and interpretation of collected data. 

Delivery:  Presentation of data to users. This could on screen or in the format of a presentation. 

 

Why a shared understanding of data  initiatives is important

Having a shared understanding is important for a number of reasons. The first of these is having a=shared understanding of what business value we are trying to create. For example, if a company was spending a lot of money on fixing data, improving data quality should be a concern of every employee. One business unit should not be doing something else like add new forms of data when the existing data is not getting collected properly. The two operations could be in complete conflict with one another. 

 

A lack of understanding of data can also lead to issues around how and where data is stored and why. This could lead to issues like data silos and firms having trouble figuring out what the latest version is a dataset is. Much more could be said on this but now that why a data initiative is vital has been quicckly established, this answer will look at the framework’s ability to may this out. 

 

How does the framework create a shared understanding?

The framework itself is an excellent way of developing a shared understanding as it leans on the concept of the six serving men and the 6 or 12 qeustions that come with the concept. Each question examines the business in a different way and by design asks different questions of the stakeholders. This brings stakeholders together and gets them to look at a problem from different perspectives and to listen to the views of other employees or stakeholders. This would open the eyes of many if not all the employees taking part in a manner similar to Osterwalder’s Business Model Canvas. If all six questions are rigorously applied to six parts eg data acquisition of the Data Value Chain then a total or 36 questions can be asked. This is a great garner of conversation that could lead to a stronger stared understanding of a data problem. 

 

How the framework might work in practice?

As mentioned employees will come from different backgrounds, this means they will bring their own skills and more importantly perspectives. Each employee type will have an element of tunnel vision and will struggle to see it from the point of view of another employee types unless such data issues are discussed. 

 

If we were to take supply chain management for a food’s company as an example. This is of course the management of the supply and demand of food and beverages. A company like Pepsi sells many products around the world to many different businesses. Even if we focus on their primary product Pepsi, it is sold is supermarkets, aircrafts, restaurants, café’s and even at street food stands. Where all these products are, how much each buyer has, what they had in the past and what they will need in the future is a huge and complicated undertaking. The marketing team will only be concerned with using target to target key audiences. The finance team will look to way to save money and the IS team will be worried about keeping all the data up to date. The framework brings there people together and helps garner a better understanding. This stops for example, the finance team getting frustrated behind closed doors as they don’t understand the need for giving out free products. But with this model the marketing team can explain the data that shows how important a factor such as brand loyalty and awareness are to making sales. 

 

Keeping the six pillars in mind. If we take the analysis stage. Some of the question might look like this; 

 

1.     What analysis do we currently do that could help with delivering just on time products to buyers?

2.     Why do we need so much data to implement just in time shipping?

3.     When/How often is our data analysed?

4.     How do we analyse our data at the moment?

5.     Where are the people who analyse our data based?

6.     Who analyses our data at the moment?

 

Now, question 1 might come from the finance team as they want to reduce costs, while the shipping team might ask question two. The CIO of the organisation might be concerned with question 5 and 6. Just the fact that all these kinds of people will be in the room, will get others thinking about data in different ways and this will help developed an overall shared understanding. The opportunity might also be taken to create a shared understanding of language of a firm. For example, what does “just in time” mean? Does it mean that a plastic bottle only comes to a pepsi factory minutes before it will be filled or does it mean that products will arrive once in the working. Will Pepsi supply its customers just before the last Pepsi is sold or will the use analytics to predict when they will all be sold out? 

 

Summary

If done right the framework should create a shared understanding of data initiatives. The framework and its writers recognise that there is a lack of understanding at organisations of how to optimise the data they have and how to conduct the six pillars to the best of their abilities to gain a competitive advantage. The framework should clear up these steps and create a dialog of shared language within a firm. Each person’s role should be understood better by others and the role they play in optimization a shared understanding of date. 

 

This answer has explained the concept of the model and the pillars that make it up, it has laid out why a shared understanding is vital and how it aims to do it. Finally it has done this is the context of a company like Pepsi trying to gain a vetter understanding of its data.