Digital transformation is an easy phrase to throw around, but many companies are finding it much harder to achieve in practice. I caught up with Hadley Christoffels, CEO of Global SAS Technology Partner Boemska, to find out more about the company’s approach to rapid analytics app development.
Hadley, what is Boemska’s guiding principle for solution development?
We see ourselves as an enabler to digital transformation through analytics. The approach, centered around our software, is to help organizations overcome challenges in scaling the adoption of enterprise analytics. We do this by enabling robust analytic platforms and building rich, business-driven user experiences.
From your experience working with customers, what is the secret to successful digital transformation?
One of the key challenges with digital transformation is the sheer breadth of the concept. It is, therefore, easiest to start with the challenges. Perhaps the first challenge is availability of time and money, and also generating value as soon as possible. To overcome this, the secret is to approach it in bite-sized chunks. The platform and app development combination makes this much easier. Once you have the platform, with access to the data, you can start to transform the enterprise one app at a time. You can also deliver value with each app. We’ve found that once you have deployed one app, it’s easy to identify linked processes that can be improved, too. So the whole process snowballs.
How does this fit into the analytics journey for customers?
Digital transformation can be very daunting for enterprises, especially large enterprises. The big challenge comes when the focus moves from technology to people, what Chris Bahm calls “the last mile of analytics.” You need a way to quickly and effectively get insights provided by analytical models across the organization. We develop applications on the SAS Platform to help surface those insights in a much more understandable way and embed them in the day-to-day work of the business. To achieve this, we use our app development platform, AppFactory.
Why is this important for innovation?
Innovation in the enterprise can often be dampened by red tape and process. Using SAS as the enterprise analytics layer ensures that important factors, such as security and access to data, are already taken care of. While apps built with AppFactory enable those who understand the business through their data to develop complex workflow, data processing and visualization applications exceedingly quickly. The result is that ideas can be tested quickly. and successful apps can be deployed across the enterprise within minutes.
And the app development is completely driven by business needs?
Yes, this is key. Analytical models are created by those who understand the problem the business is trying to solve with it. It therefore makes sense that these same people also drive the development of applications used by the business to solve those problems.
Could you give us an example?
Yes, we have a German customer in the tourism sector. They had a complex, Excel-based planning process which was time-consuming and performed in silos across the business. Led by their data science team, we developed a modern web-based forecast adjustment and approval workflow with visualizations for the key metrics. The unified role-based solution is integrated directly with their SAS forecasting models and is used by people across the organization, including the CEO. The app has transformed their seasonal planning process, a process which is crucial to their business.
What about the cloud? How does that fit in?
I think that this pandemic has put digital transformation at the top of every executive agenda. And you can't really talk about digital transformation without considering cloud. I believe that soon there will not be many organizations left without cloud as part of their operational strategy. While not the silver bullet to every problem, the cloud can provide the flexibility and agility required to remain competitive in an ever-changing market. Maintaining control of cost, performance and efficiency of cloud workloads with a tool such as ESM will, however, become increasingly important.
Explore discoverability, scalability, and interpretability
Unlocking insights from data is key to powering transformation. Take Natural Language Processing (NLP) for example. It is about understanding, interpreting and emulating human language. Text and increasingly voice data is abundant and yet under-exploited. Machine learning makes keeping pace with conversations more realistic. Boemska and SAS teams got together in a #SASchat to discuss exactly this continuum. Follow the discussion here.