EconPapers    
Economics at your fingertips  
 

Building a Revenue Engine – Scaling Up Sales Automation

Storbacka Emma () and Storbacka Kaj ()
Additional contact information
Storbacka Emma: CEO, Avaus Ltd., Stockholm, Sweden
Storbacka Kaj: Hanken Foundation Professor, Hanken School of Economics, Helsinki, Finland

NIM Marketing Intelligence Review, 2022, vol. 14, issue 2, 31-35

Abstract: The scalability of sales automation is dependent on a company’s capacity to create and operate use cases. For businesses not systematically scaling up data utilization and automation, increasing levels of “digitalization” may negatively impact financial performance. Successful companies focus on building a revenue engine to achieve a scaled impact and a flat or even declining cost base. To scale, companies need to stop structuring their digital transformation initiatives via the platforms they are implementing and start using a use-case-centric lens. In a use-case-centric logic, business priorities and applications are the starting point. Use cases leverage the available data through automation and employ digital platforms as supporting tools to drive specified business objectives. In most companies, existent practices need to be challenged, and the methodology and process will require leadership skills. Managers need to understand the effort required to reach the target automation level, and to keep the engine running, marketing and sales need to improve their data literacy.

Keywords: Sales Automation; Use Case Centricity; Scaling Digitalization (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2478/nimmir-2022-0014 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:gfkmir:v:14:y:2022:i:2:p:31-35:n:5

DOI: 10.2478/nimmir-2022-0014

Access Statistics for this article

NIM Marketing Intelligence Review is currently edited by Christine Kittinger-Rosanelli

More articles in NIM Marketing Intelligence Review from Sciendo
Bibliographic data for series maintained by Peter Golla ().

 
Page updated 2025-03-20
Handle: RePEc:vrs:gfkmir:v:14:y:2022:i:2:p:31-35:n:5