From time to time discussing about technology, architecture or data I get a feedback like - “this all makes no sense because mainly it is important to create business value from data…” nice.
How to Measure Business Value
The final goal of every company is creating profit, turnover and cashflow. If you do that you create value. Period. But maybe we have to understand, that knowing this doesn’t help doing it. Let’s understand how value is measured. A very popular and well known framework (for sure not the only one) is the DuPont model showing where Return On Investment (ROI) comes from:
Fig. 1: DuPont Analysis, Source: Wikipedia
This is important to understand how value is measured, but still theoretical if you don’t understand how to support this with data. But it shows you the parameters you can work with. Let’s take profit margin, where you have to consider operating income which is often hard to measure for data, but also operating expenses, what is often not really considered for data. Therefore we have to understand income and expenses and how to influence this by data.
How to Create Business Value
Even in 2024 nothing has changed. We earn value by supporting the value chain. The result is a profit margin, as one part of the DuPont Model. This is why process mining is such a nice thing, because it is about optimizing the value chain, saving money, finding new ways to do things.
Fig. 2: Value Chain, Source: Wikipedia
A focus on support activities supports the primary activities and will lead to efficiency and understanding where to focus leads to effectivity what results in cost optimization.
A focus on the primary activities can have at least three effects:
Getting insights to optimize - means saving money through data
Getting insights for new opportunities - means selling more, exploring new markets
Enhancing the product itself with data and getting part of the value chain - means digital business
The Ansoff Matrix help to understand that.
Fig. 3. Ansoff Matrix, Source: Wikipedia
Data can be a game changer by infusing every part of the matrix:
Market Penetration - Data delievers you the insights about markets, selling and the product along the value chain to enhance quality and lower costs.
Product Development - Connect your product with a digital service like predictive maintenance or a complete digital version of your product in the same market driven by data.
Market Development - Explore and understand new markets with your products by market analysis wit external data and market intelligence. Analysing the feedback from your first steps with the data to steer your success.
Diversification - nothing needs more data but building and understanding yourself (with). Data is still the base for new businesses, internal and external data.
Not every business is the same. But the approaches shown here are still basic principles for nearly every business. Study this and you will understand better how to create value.
Operational Data Value Thinking
Now after this 101 in business administration, what has that all to do with technology or architecture discussions? Like a factory which produces goods, vehicles which transport goods and shops which offer and sell goods you need a data value chain, where technology and architecture is your infrastructure and thing like data catalogs and data marketplaces offer you the data you need in an easy way like a shop. To talk about technology and architecture means to talk about your value chain, as it is deeply connected nowadays. It is the second side of your medaillon.
Fig. 4: The operational “Data Value Chain”
At the end of this Data Value Chain value is not really guaranteed, if you are not really connecting it to the business. This value chain is the operational perspective of data value creation. This is a huge challenge today for many reasons, e. g.:
Data is collected and stored without a clear business case
To collect, store and compute data is more expensive than the value behind
Data teams are not well connected to the business and the process to provide data is slowly or not even done
You process data once valuable but not used anymore
This means data have to be understood in a business context, embedded in the value chain of your company and supporting your product and market strategy as shown above.
How does this work?
Strategic Data Value Thinking
To be connected to the business it is not only about data processing. To support your company right you need the right strategic approach. This means, your data platform has to provide the right capabilities supporting your data architecture. Thinking about data architecture means to understand the data in your organization and the goals you want to reach with.
Fig. 5: Strategic Data Value Creation
Having the best technology capabilities is not helpful, if your organization can’t leaverage it. You should always understand what your data and business teams are able to handle and really need.
Finally to bridge the gap from strategic data value creation to operational data value creation you need the right use cases which can be supported today by a data product approach or at least by continiuous exploration of the best use cases and focus on the value you can create for your company.
Much can be said about how to create value from data. This text was a short trip about important aspects often forgotten, more often not mentioned if people speak about “value”. Please take away this two simple points:
Even in data the creation of value is based on basic business management principles
Without the right technology and architecture you will not be able to leaverage value from data (not even with Excel or Power BI)
While already written, I found this post from Joe Reis and think the comments are an example of this discussion and provides further perspectives.