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REVENUE INTELLIGENCE: Analyst team and resource requirements vs. 180ops data factory

 

The purpose of this article

This article concentrates on analyzing the strengths, weaknesses and potential synergy for collaboration between analyst teams and intelligence platforms when discussing revenue operations and growth.

THE RISE OF ANALYTICS AND THE TWO WAYS TO APPROACH IT; TEAMS VS. MACHINES

At the peak of AI, we see mid-cap and large enterprises recruiting analytics teams and hiring consultants to iterate and develop new ways of turning data into valuable insights. On the flip side of the coin, this, on the surface ‘good’ resolution, results in companies checking the box and considering the challenge now fully solved and the team to take care of it independently. In this article I look deeper at the challenge at hand and what truly is needed to solve it. 

By solving the problem with a team of analysts, companies miss a very valuable, often low-hanging fruit; they are not looking for or considering options that are already developed intelligence platforms and ready to serve faster, with lower investment level and with lower risks.  

For people working to solve analytics challenges, on the other hand, these efficient machines and platforms often represent a threat and cause fear over one’s own job security. 

 

What makes matters worse is when people are paid by the hour, causing their primary motivation not to be fast delivery of results – this is especially problematic with consultancy or external talent-based solutions. There is a clear conflict in the incentive model.

This is why management needs to keep their eyes open and constantly consider what is in the best interest for the business to grow and thrive. The solution is not this or the other but rather a combination building on human-platform synergies.  

 

The financial and timeline consideration

This is a very crude table that outlines the cost structure between a company's own work and 180ops Revenue Intelligence platform use. What’s additional to the points mentioned is the cost internal meetings needed to make decisions on all the different factors as well as possible recruitment costs in case the internal team is not yet in place. 

FACTOR 

(ANALYST) TEAM AND RESOURCE REQUIREMENTS 

180ops PLATFORM 

Iteration and learning to get started 

Large investment (consulting, analyst, design, coding and tool costs as well as hiring costs for internal capability creation) 

Included in the fee (onboarding) 

Data model and tech dev. costs 

Large investment (design, coding, tech, licenses, tools...) 

Included in the fee (done and tested) 

Architecture and infra 

Large investment (consulting, design, technology, license and coding costs) 

Included in the fee (done and tested) 

Analyst tools and AI (ML/neural/NLP) development 

Tool & Dev cost + running costs 

Included in the fee (done and tested) 

Development of data recipe, iteration and learning 

Running development and analyst cost  

Included in the fee (Customer success collaboration. We have a lot to contribute to the data recipe development) 

Delivering data to other systems 

Integration and development cost 

Add-ons and ready-made API included in the fee 

Reporting tool development 

Investment + tool costs  

Included in the fee (done and tested) 

People onboarding and education 

Educational Material production and training costs 

Onboarding, training and tutorials included in the fee 

Data security 

Needs to be designed and built. Requires tech investments, development and licenses. 

Included in the fee (SSO, data security in full solution including encryption, secure data model, anomaly detection, intruder detection and extraction) 

Data ownership  

Fully owned  

Fully owned by customer

Continuous analysis 

Mainly driven by analysts, distribution and design for users' needs to be designed and built 

UI included in the fee (done and tested)
Personalized views to stake holders and customer facing professionals in understandable format so that users can make choices and get advice individually. Analyst collaboration for further and deeper analysis. Views also available in CRM where customer facing organization uses them.

The cost of external data 

According to use cases and needs (the same as platform use) 

According to use cases and needs (the same as internal dev.) 

Support and documentation 

Who has the ownership of the overall solutions? Who owns the roadmap? What about documentation of various self-developed tools? What if the key person(s) decides to leave the company 

Included in the fee (support channels and tools, customer success responsible, full documentation) 

Regulatory compliance Internal requirements to stay compliant Included in the fee

 

Timeline and development perspectives

The comparison is like comparing an architect and construction company that are promising to design and build you a factory against leasing a ready-made factory with existing production, assembly, packaging and delivery processes and channels. When we talk about midcap and large enterprises, this is indeed comparable to industrial production facilities. The volumes of data are vast, and the complexity of this challenge is very difficult to understand before actually entering the process. This is also important to understand from an investment budgeting point of view: when entering this process without a platform, you cannot know what the investment will eventually be and how much value you can derive from it. 

180ops has been developed with modular production capacities with capability to customize the data recipe, ETL process and the production process for the customer's individual needs, but the end products have been pre-decided, and they are in standardized format. This makes the industrial production process scalable, fast and still individually valuable and capable of adapting to the customer's business model and needs at offering level. We do mass customization instead of tailored construction. We can do this, because we've done artesan type of insight and advanced analytics work for decades and are now industrializing it. 

How the 180ops revenue intelligence factory actually works:

180ops DATA FACTORY approach

The timeline for these two options is completely different.

For a platform like 180ops it takes about three months to be in full operation compared to custom development that takes years to truly deliver value.

Even then, the user experience is way behind 180ops experience, which is constantly improved and developed further and not at the customer’s cost. From the running cost point of view, if the customer company has internal people to keep the engines going and develop the tech further, the running cost also exceeds the cost of 180ops license cost.  

In case the company has already worked in custom development for e.g. Risk, NBA or Potential and has produced valuable tools, these can be deployed in the 180ops factory and solve distribution and usability challenges as well as the challenge of running costs. Collaboration builds on top of the capabilities you already have.  

Getting the right answer from AI or analytics isn't enough though. The platform is an answer to a much taller order. We need to get the right answer, to the right person, at the right time, in an understandable format, in the technologies they are using to make decisions. This has to do with data delivery and user experience which are crucial factors for scalability in corporate wide operational guidance. The purpose of this approach is to help people thrive in their roles, become smarter, feel confident and more creative by making sense of what is happening with their markets and customers. 

180ops scalability and data distribution approach

 

What you see is less than you will get

The strength of 180ops revenue intelligence platform is that the customers know in advance what they will get. Although 180ops is capable of offering incredibly valuable insights with very easy to understand user interfaces, it doesn't answer all questions. To go even deeper with further analytics or with qualitative and quantitative research, companies still need internal resources or help from partners. This is where we work in synergy with internal teams and consultants. 

 

A platform is the fastest, cheapest, and most robust way to get you the insights you need. Your team is the best at turning those insights into stories that change how you’re doing things.   

 

180ops is collaborating with multiple industries and constantly learning and iterating how we can best deliver value for customer's use cases. This is something that accelerates our capacity to stay ahead of the curve, optimize solutions for different customer verticals. The capacity to learn and improve is simply much stronger than individual companies have. As a customer, you will be aware of our development roadmap, and you can contribute to it with your use cases and challenges that need to be solved. We are constantly working towards new epics and features that you will enjoy as our customer. 

 

 

WANT TO SEE HOW THE 180OPS REVENUE INTELLIGENCE PLATFORM WORKS IN REAL LIFE? 

Words are cheap, seeing is believing. This guides our work and is the best way to prove what we say is what we do. So, book yourself a demo and see how our revenue intelligence platform could radically improve your B2B business starting today.

 

 

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