Building the new ecosystems & service offerings with Advance Analytics and AI

The thing I am seeing more of is pressure and demands on organisations to innovate and pivot towards digital and AI driven initiatives with little guidance and support to do so. I help organisations build new service offerings with embedded AI in multiple industries across EMEA and Asia Pacific.

The Mckinsey State of AI in 2021 survey stated that the adoption of AI continues to grow with 56% of respondents reporting AI projects in at least one business function within their organisation. Despite this being predominantly from emerging economies that include China, the Middle East & North Africa, the rest of the world are trying hard to build out their own business models but are more stifled by cultural change than younger enterprises.

Across the globe, I see organisations from a wide range of industries asking for help with understanding where AI fits in and adds value. The Mckinsey survey sights the most commonly adopted AI user cases relate to services enabling; automation, optimisation and predictive capabilities to enhance an existing or new service offering.

Many new partnerships and eco-systems I help build have the following attributes: Strong domain or market understanding, Definitive Intellectual Property (IP), Unique Selling Point (USP) and the ability to execute an existing or new ‘as a Service’ offering..

At the start of evaluating a collaborative partnership it is important to ensure all parties are aware what each business brings to the table with regards to these attributes. This may sound simple but you would be surprised in how many conversations I hear the comments, “I thought your business did that?" From this starting point we can assess how Advanced Analytics fill the gaps in automation, scalable AI driven service offerings and analytical platform capabilities.

Historical challenges have been not knowing what the art of the possible is. When and where to co-develop is a key step in getting the right level of funding based on a strong Return on Investment (ROI). This has now changed with more successful projects being published that have paved the way for better understanding and funding of AI initiatives over and above the usual underfunded ‘science projects’ most businesses have been guilty of in the past.

With reference to the IDC's Worldwide Semi-annual Artificial Intelligence Systems Spending Guide. AI is expected to increase from a forecast spend of $85.3 billion in 2021 to $204.5 billion at a Compound Annual Growth Rate (CAGR) of 24.5% through to 2025.

One question I get asked often is, should we build, buy or outsource? This is a question that has been raised by many businesses over the years in relation to the application of software. Independent Software Vendors (ISV’s) have not had a shortage of answers. In 2016 Gartner published their research on this very question with specific reference to analytics.

Gartner captured some of the challenge’s organisations often experience. 

Source: Gartner Machine-Learning and Data Science Solutions: Build, Buy or Outsource? 

So, what are the pro’s and con’s of each approach?… More importantly what has changed in recent years to enable companies to find the right answer?

It is my opinion that the growth in cloud capabilities, the rapid development of “marketplaces” and new partner eco-systems are key. These factors have presented a great opportunity for organisations to lower centralised operating costs, increase flexibility, improve collaboration, and importantly access containerised solutions for enhanced interoperability. 

Taking into account these considerations, will in turn shift organisations towards the “App culture” of enterprise software. I believe in the not-too-distant future companies will have similar flexibility in their operating models to how you run your personal mobile phone. This will focus on specific apps or micros services for certain capabilities that are interchangeable, subscription and/or consumption-based models.  

According to Accenture, 76% of CEOs think the current business model will be unrecognizable in five years. They see partnerships and ecosystems as the way of the future.

I don’t believe industry will divert completely from the need for core platforms like operational (i.e. ERP) and productivity (i.e. CRM) systems. With a growing need for analytical capabilities BUILD, BUY or OUTSOURCE remains very topical.

For ERP & CRM systems tier 1 companies have the choice of 2-3 offerings from large ISV’s. Tier 2 have options of 10-20 ISV’s and lower down the food chain options are far wider but driven by lower cost with limited functionality. As we now see a very broad landscape for AI vendors there are no doubt to be many more mergers and acquisitions to be done in the coming years to result in a similar choice for businesses.

The key to evaluating your companies’ options will always remain unique to your industry. If history has taught us anything growth only comes from focus. Make sure you don’t lose sight of what is core to your business success and use advances in technology, ecosystems, and new working models to help you achieve these objectives.

Focusing on your core capabilities (leveraging IP, USP’s, market knowledge and data) to drive growth should be paramount. Leaving operational enablers such as ERP, CRM and Analytical platforms to be provided by ISV’s along with partnerships, ecosystems and marketplaces. This will help in accelerating opportunities, increase time to value, reduce costs, increase revenues and increase profitability. In short, don’t build anything from the ground up that is not core to your business, “there’s and app for that!” For further insight on this topic reference: How ‘Digitisation’ can drive ‘Servitisation’. 

To buy? or to outsource? 

As Gartner rightly observed how do businesses filter through the plethora of choice, good advice and avoid failure? My recommendation is having an iterative process to diagnose and clarify direction. Understand what fits between Business Need & Business Value. This will help you evolve your proposition. Listed below are a few considerations I find useful.  

At each stage you should be able to tie each consideration back to success in reaching the business value as your strategy evolves. As you design and build out your new service offerings you may evolve with more considerations than I have listed above. Be consistent with having a clear plan, choose your people wisely, fail quickly, be responsive to change, and think big!

“Think little goals and expect little achievements. Think big goals and win big success.”

- David Joseph Schwartz -

This may not explicitly answer the question of buy or outsource but as you go through each step you will start to see what makes sense to invest in and what makes sense to outsource. By following these basic steps SAS has helped hundreds of companies around the world develop new service offerings, business models and develop new partnerships to accelerate growth.  

SAS helps transform a world of data into a world of insights.

For more information on how SAS are helping business integrate advanced analytics and AI capacities into new markets, ecosystems, partnerships, and business models go to SAS Partnerships