Today I’d like to address a very important topic: The skillset needed for process intelligence projects. Contrary to what you might think, the important skill is not data science, because KYP.ai delivers the relevant data, but subject matter expertise with some skills to understand the analysis and to recommend appropriate actions.
Data can bring you remarkable insights – however it is worthless if you cannot understand it and use it to make informed decisions. With the right digital transformation skills you can interpret the business implications of what the data is telling you, implement change and review the results in a feedback loop for continuous improvement with P&L impact. The resulting benefits can be great and well worth the investment.
Contrary to what you might think, the important skill is not data science, because KYP.ai delivers the relevant data, but subject matter expertise with some skills to understand the analysis and to recommend appropriate actions.
Here is my take on what you need to excel in process intelligence projects.
Ability to contextualize data
Seeing the data is only part of it. The other and more important part is the ability to understand and contextualize it in terms of processes and business objectives. Analysts with an understanding of the business should be able to relate the key information that KYP.ai captures from the massive pools of operational data to business operations such as process flows, and to be able to explain the findings to management and stakeholders in order to derive the most important and impactful actions. These are not necessarily the most obvious ones.
Let the data do the talking
Often the data reality is different from the pictures that managers have in their heads on how processes are undertaken in the organisation. Understanding the reality can help you mitigate risks and improve operations. Furthermore, the data can find you new insights about aspects of operations that you had never thought of before but that can play a key role in efficiency. The data can be compelling and should help you persuade decision makers in your organization to give you the support and the funding that you need to implement change.
A pragmatic approach to keep a common thread going from the beginning to the end
The ultimate target of a transformation program is to see the results in the P&L – be it cost savings and efficiency, or revenue increase. As our customer you can derive insights with KYP.ai very quickly and in most cases, the opportunity to derive high returns can be rapidly identified – depending on the scope selected. But then, when it comes to execution and implementation analytics skills only are not sufficient to keep the momentum going with stakeholders and implementation teams.
It is important that you keep the people responsible end-to-end, from the questions that triggered the project in the first place to showing success at the end of the implementation. Otherwise the driver for the project and the issues that need addressing might get lost in other requirements and the project will lose momentum. To mitigate this, three things are important:
- Set realistic and measurable targets.
- Capture intelligence broadly to see the full picture but always keeping a thread going to help you answer the questions that you started out with along the journey of discovery, from the data lake to implemented actions, through to the results.
- Use your financial acumen to identify the measured impact in the P&L.
The ultimate target of a transformation program is to see the results in the P&L – be it cost savings and efficiency, or revenue increase.
Being tech savvy
A process intelligence tool like KYP.ai also needs some tech savvy people who are rapidly trained attending KYP-Academy enabling them to maintain the data, expand configurations and also understand how the data is collected and collated. You may well ask why is this important? It is “out of the box tech”, right? Well, according to our customers data is very interesting to a lot of stakeholders. To avoid scope creep and to manage expectations, it is important for analysts to be able to explain what is possible and what is not – or to be clear for which requirement you need to tap additional data pools.
The elephant in the room is that the skills market is strained. Where do you find these skilled employees? The answer is in your own organization. We are not talking about hard-to-find and expensive data scientists but people with experience of the business with analytical minds. For too long the emphasis in recruitment campaigns has been on “specialists”. For a transformation team there are many different perspectives, and you should consider helping existing employees develop their skills as well. Think beyond mathematical ability and the need to understand the business and the processes associated with it. Look for the people in your organisation who are eager to learn, have some analytical skills and who would enjoy the challenge of presenting and contextualising the insights for your business.
To summarise, you need a mix of business and analysis skills to succeed in process intelligence projects, but you do not need hard to find and expensive specialists. By changing perspectives and looking at the broader set of relevant skills, you can grow your capabilities and help your employees develop theirs through experience.